the competition is now closed. All usra/lura spots have been filled and confirmed.

NOTE THAT NOT ALL PROJECTS ARE LISTED HERE. STUDENTS ARE ENCOURAGED TO ALSO LOOK UP AND CONTACT PROFESSORS WHOSE WORK THEY FIND INTERESTING - THEY MAY HAVE A PROJECT AVAILABLE:

o   http://mech.lassonde.yorku.ca/people/

o   http://civil.lassonde.yorku.ca/faculty/

o   http://eecs.lassonde.yorku.ca/research/research-labs/

o   http://esse.lassonde.yorku.ca/people/faculty/


DEVELOPMENT OF CONTROL ALGORITHMS FOR SATELLITE RENDEZVOUS AND AUTONOMOUS SPACE ROBOTIC MANIPULATOR

Position type: NSERC USRA

Department: Mechanical Engineering

Professor: George Zhu

Number of positions available: 2

Contact: gzhu@yorku.ca

Summary of project: 

The project deals with control of satellite rendezvous and autonomous robotic manipulator in space. It will focus on the development of a real-time and vision-based pose and motion estimation control algorithm of a non-cooperative target by photogrammetry and extended Kalman filter for robotic manipulators to perform autonomous capture. Optical flow algorithm will be used to track the target to increase the image processing efficiency for real-time pose and motion estimation of the target. Close-loop position-based visual servo control strategy will be used to control a robotic manipulator to capture target autonomously.

The position will be focused on hands-on experimental works. We want to test our control algorithms using two air-bearing satellite simulators in zero-gravity condition. One satellite simulator will move along a pre-defined path and attitude with star-tracking navigation system and cold-gas thrusters. Another satellite simulator with a robotic arm will track the moving satellite and capture it autonomously.

Duties and responsibilities:

Implement control algorithm, conducted the experiments and improve the hardware of testing system if needed.

Requirements for technical skills: Dynamics, mechanical and electronic hardware, Matlab and Labview coding, data acquisition and analysis.

Requirements for interpersonal skills: Team worker

Degree, courses and discipline prerequisites: Mechanical and space engineering programs


microfluidic devices for disease diagnosis and drug screening applications

Position type: NSERC USRA

Department: Mechanical Engineering

Professor: Pouya Rezai

Number of positions available: 2

Contact: prezai@yorku.ca

Summary of project: 

Our lab focuses on developing microfluidic devices for disease diagnosis and drug screening applications. We are interested in investigating the interactions between fluids and microscale objects in microenvironments at the fundamental level. We use the knowledge for developing miniaturized devices for various health and environment monitoring applications.

On the diagnostics side, we make miniaturized devices and use inertial, magnetic, elastic and other forces to sort and separate micro-particles and cells in multi-phase flows with various Newtonian and non-Newtonian properties. Our current interest is in sorting and separation of magnetic microparticles in non-Newtonian ferrofluids. These devices will have applications in point-of-care detetction of biohazards and diagnosis of disease biomarkers.

On the drug screening side, we develop Lab-on-a-Chip (LoC) devices for manipulation, chemical exposure, and neuronal and behavioral screening of various biological models of human disease. Our current projects involve testing C. elegans, D. melanogaster, D. rerio and various cells in LoC devices to enable automated and quantitative investigation of protein aggregation in neurodegenerative diseases like Parkinson's disease. Our technologies will have applications in chemical screening and toxicology in the drug discovery industry.

Duties and responsibilities:

We are seeking candidates who are highly motivated and ambitious for research in bioengineering and multi-phase micro-flows. Students in our lab will be responsible for defining research milestones, microfabrication of devices, testing the devices with various biological samples, interpretation of results and weekly delivery to the group, writing reports, and working in teams of graduate and undergraduate students.

Requirements for technical skills: Work well in a team. High level of attention to details. Strong communication skills.

Requirements for interpersonal skills: Highly motivated, organized, and punctual.

Degree, courses and discipline prerequisites: Knowledge of fluid mechanics and general understanding of biology are assets.


Development of Navigation and Control System for Unmanned Aerial/Ground Vehicles

Position type: LURA, NSERC USRA

Department: Earth and Space Science and Engineering

Professor: Jinjun Shan

Number of positions available: 2

Contact: jjshan@yorku.ca

Summary of project: 

This project is to develop control and navigation algorithms for multiple unmanned aerial-ground vehicles currently available at Spacecraft Dynamics Control and Navigation Laboratory (SDCNLab). Artificial Intelligence may be employed to improve the control and navigation accuracy.

Duties and responsibilities:

(1) Development of control and navigation systems for unmanned vehicles;

(2) Experimental studies;

(3) Prepare technical report.

Requirements for technical skills: Good programming skills

Requirements for interpersonal skills: Good communication skills

Degree, courses and discipline prerequisites: Engineering students, completed ENG 4550


Fan-assisted solar walls for building heating applications

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Paul O’Brien

Number of positions available: 2

Contact: paul.obrien@lassonde.yorku.ca

Summary of project: 

A solar-heated wall (Trombe-Michel wall) will be fabricated with a ventilation channel sandwiched between an insulating wall (inside the building) and an outer wall that contains a thermal energy storage (TES) medium. Experiments will be performed wherein the wall comprising the TES material (e.g. a phase change material for latent heat storage) is heated with solar simulated light, and the heat stored in the wall is transferred through the ventilation channel to the “building interior”. The heat will be transferred through the ventilation channel to the building interior using Smart Booster Fans, which are quiet, low-powered fans equipped with temperature sensors. In general, Smart Booster Fans can be installed in vents throughout a home to measure the local temperature at different locations and, through wireless communication, operate in concert to optimize air flow to efficiently achieve the desired temperature at different zones throughout a home. The objective of this research project is to use a Smart Booster Fan (integrated into the solar-heated wall) to offset the buildings heating load to the greatest extent possible.

Experiments will also be carried out to determine the duration and extent to which thermal energy can be stored and subsequently delivered to the interior of the building at a later time (in these experiments the Smart Booster Fan will be turned on after a variable period of time, t, has elapsed since the solar-simulator was turned off). This experiment will also involve optimizing the control algorithm that operates the Smart Booster Fan in order to deliver heated air from the ventilation channel within the solar-heated wall into buildings with different heating loads. Here again, the objective of these experiments is to offset the building’s heating load to the greatest extent possible, although this time the emphasis is on storing heat (e.g. after solar energy is no longer available) as efficiently as possible and subsequently delivering it to the building interior according to the occupants requirements.

Duties and responsibilities:

The successful candidate will work with graduate students to perform the following tasks: (1) Purchase materials to fabricate a solar-heated wall that contains thermal energy storage materials (2) Fabricate the solar-heated wall with Smart Booster Fans integrated into its ventilation channel. (3) Perform experiments wherein the effects of changing the width of the ventilation channel on the temperature and intensity of the airflow delivered by the Smart Booster Fan are measured (4) Characterize the optical properties of the materials used to build the solar-heated wall (5) Develop a model to simulate and numerically analyze the amount of solar energy stored in the TES medium and to calculate the expected rate at which heat will be delivered from the ventilation channel to the interior of the building.

While the successful candidate is expected to be capable of working independently, the hired student will work with graduate students from the Advanced Materials for Sustainable Energy Technologies Laboratory (AM-SET-LAB) and will receive training on performing optical materials characterization, carrying out detailed experiments, and developing numerical models.

Requirements for technical skills: Machine shop skills and laboratory skills are an asset.

Requirements for interpersonal skills: Motivated, strong communication skills, team member.

Degree, courses and discipline prerequisites: Applicants from any engineering discipline may apply, although mechanical engineering students are preferred (training will be provided).


Enhanced Low-emissivity Coatings

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Paul O’Brien

Number of positions available: 1

Contact: paul.obrien@lassonde.yorku.ca

Summary of project: 

Transparent low-emissivity coatings transmit solar radiation, with wavelengths ranging from ~ 0.3 μm to ~ 4 μm, but have a high reflectivity (or low-emissivity) for thermal infrared radiation on the order of ~ 10 μm. Thus, transparent low-emissivity coatings, such as those typically found on building windows, can be used to “trap” solar thermal energy. That is, solar radiation can pass through a window coated with a low-emissivity film to heat objects within a building. However, these coated windows reflect the thermal radiation emitted from the heated objects to prevent radiative heat losses to the building’s exterior. Low-emissivity coatings are also applied to solar thermal collectors for residential heating applications (e.g. rooftop solar water heater) and to receivers in solar thermal power generation plants.

The goal of this project is to fabricate and characterize low-emissivity coatings with exceptionally high transmittance for solar radiation and extremely high reflectivity towards thermal radiation. This will be achieved by depositing thin-film optical materials that have nanoscale features (e.g. less than 100 nm). These optical films can be designed to cause wave interference effects for incident light and radiation, which can be used to tailor their transmission and reflectivity.

A second goal of this project is to use the fabricated transparent low-emissivity coatings to heat highly absorbing “black” materials to the highest temperature possible. Experiments will be performed wherein an absorber material is placed in an insulating cavity and subjected to solar-simulated radiation through a window coated with the nanostructured low-emissivity film while measuring its temperature.

Duties and responsibilities:

This research project is focused on developing new low-emissivity coatings comprised of nanostructured layers. The student will calculate the transmission and reflectance of nanostructured low-emissivity coating using a computer program provided to them. Furthermore, the student will analyze, plot and present the results. The student will also fabricate and characterize nanostructured low-emissivity coatings. That is, the student will be trained to fabricate nanoparticle films using wet-deposition methods such as spin-coating, or dip-coating of pre-formed nanoparticles dispersed in solution. The student will characterize the nanostructured films using UV-Vis spectroscopy, SEM imaging, and by measuring their infrared reflectivity.

The student will work closely with graduate students in the Advanced Materials for Solar Energy Technologies Laboratory (AM-SET-LAB). The student will be trained on the different classifications of solar simulators and relevant lighting technologies. The student will also improve their analytical skills and benefit from participating in group meetings and discussions about how to optimize the performance of transparent low-emissivity coatings.

Requirements for technical skills: Laboratory experience, analytical and critical thinking skills, experience with SEM imaging and spectrophotometry are an asset, although training will be provided.

Requirements for interpersonal skills: Motivated, strong communication skills, team member.

Degree, courses and discipline prerequisites: Applicants from any engineering discipline may apply, although mechanical engineering students are preferred (training will be provided).


Software analytics

Position type: NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Zhen Ming (Jack) Jiang

Number of positions available: 1

Contact: zmjiang@cse.yorku.ca

Summary of project: 

Software engineering data (e.g., source code repositories and bug databases) contains a wealth of information about a project's status and history. The research on Mining Software Repositories (MSR) aims to transform the data from static record-keeping repositories into knowledge, which can guide the decision processes in modern software development process. For example, one can derive correct API usage patterns and flag anomalous (and potentially buggy) API usages by mining the source code across many projects in GitHub or Google Code. In this project, the student(s) will research and develop an efficient infrastructure, where MSR researchers and practitioners can share and analyze the MSR data.

Duties and responsibilities:

The student will be responsible for designing, executing and analyzing the experiment in a collaborative setting with other graduate students.

Requirements for technical skills: Proficient in Java and Python programming.

Requirements for interpersonal skills: Good communication skills, have the ability to work independently, willing to learn new technology.

Degree, courses and discipline prerequisites: At least 3rd year in CS or SE or CE.


Building the World's Largest Dynamic Scenes Video Database

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Richard Wildes

Number of positions available: 1

Contact: wildes@cse.yorku.ca

Summary of project: 

Scene classification is a fundamental challenge to the goal of automated visual perception. Although humans are proficient at perceiving and understanding scenes, making computers do the same poses a challenge due to the wide range of variations in scene appearance. Currently, there are a variety of algorithms available to attack this problem; however, algorithmic advances in this area are being held back by the lack of adequate video databases on which to train and test. This project directly addresses this shortcoming by building a video database to support the training and testing of dynamic scene recognition algorithms. The main goal of this project involves developing a large dataset with videos of a variety of dynamic scenes. This task can be categorized into the formulation of scene categories, design and implementation of tools for video collection, annotation of collected videos and testing of scene recognition algorithms on the constructed video database. By the end of summer, this project will yield a new database for release to the computer vision community that can serve as a novel benchmark to help researchers from around the world and thereby contribute to the advance of computer vision.

Duties and responsibilities:

The research in this project focuses on collecting high-quality videos from the web based on formulated scene categories, as well as annotating and analyzing them. To achieve these results, the student will: (i) Develop and use software tools to crawl popular video websites for videos of desired scene categories and their automatic download. (ii) Develop and use semi-automated software tools to select useful video frames for segmentation into scene components (e.g., sky vs. trees vs. roadways, etc.) (iii) Statistically analyze the collected videos to highlight various aspects of the database.

Requirements for technical skills: Web (e.g., PHP) and python and C programming experience; familiarity with UNIX.

Requirements for interpersonal skills: Ability to work in a small team.

Degree, courses and discipline prerequisites: EECS 4422 or other experience working with images desired, but not required.


MANUFACTURE AND ANALYSIS OF BIO-BASED BRAIDED COMPOSITES STRUCTURES

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Garrett Melenka

Number of positions available: 2

Contact: gmelenka@yorku.ca

Summary of project: 

Natural fiber (NF) and bioplastics/bio-resins can be adapted to braided composite (BC) manufacturing. Combining NF and bioplastics/bio-resins with braiding will lead to a sustainable, automated, near-net-shape fabrication method with configurable material properties. Bio-based composites are an emerging alternative to conventional composites that can be produced sustainably while yielding comparable mechanical properties. Presently, bio-composites are regularly formed using short fibers but higher strength and stiffness is achieved with continuous fibers. Combining BC with NF and bio-matrix could lead to an automated and sustainable production method for lightweight structures that require high impact resistance like automotive front side rails or door pillars.

Duties and responsibilities:

Finalize the design and manufacture a small scale Maypole braiding machine using a low cost digital fabrication techniques like: desktop 3D printing, laser cutting and CNC machining.

This project entails unique design challenges as braiding machine components must be miniaturized and optimized to allow for manufacture using additive manufacturing processes. The braiding machine will be used for a micro-braiding process in order to produce PLA/natural fiber yarns.

Once completed mechanical testing and evaluation of the resulting micro-braided structures will be performed.

Requirements for technical skills:

• Solidworks for component design

• Matlab, Python or other similar programming languages

• 3D Printing/ Manufacturing skills/ Hands on manufacturing

• Ability to work with electronics: i.e Arduino, Raspberry Pi

Requirements for interpersonal skills: Student should be able to work within a team environment.

Degree, courses and discipline prerequisites: MECH 2301, MECH 2302, MECH 2401


autonomous surface vessel development

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Michael Jenkin

Number of positions available: 2

Contact: jenkin@eecs.yorku.ca

Summary of project: 

This project involves developing a software infrastructure for Eddy II, an autonomous surface vessel. A video of the robot operating can be found here - 2018 November Eddy II trials in King City.

Programming will be in Python primarily, using the Robot Operating System middleware. Students will be expected to not only write code to drive the robot but also to help deploy the robot in off-site and on-campus water trials. The robot uses a collection of on-board computers to power two thrusters that provide motion of the vehicle and utilizes cameras, GPS, a compass, depth sensor and IMU to drive the vehicle. If possible, communication with an underwater vehicle operating in proximity to Eddy 2 will also be examined.

Duties and responsibilities:

Software and hardware development of an autonomous surface robot.

Requirements for technical skills: 3rd/4th year student in CS or CE.

Requirements for interpersonal skills: Ability to work independently.

Degree, courses and discipline prerequisites: N/A


Mechanical and structural properties of boiler grade steel

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Aleksander Czekanski

Number of positions available: 1

Contact: alex.czekanski@lassonde.yorku.ca

Summary of project: 

Steels containing chromium, nickel and molybdenum are proposed as materials with good mechanical properties combining high temperature strength and creep resistance, additionally they characterize a good thermal conductivity and corrosion resistance. These properties of such steels have attracted special interest for application in energy industrial processes where they are used as heat exchangers, walls of boiler and pipes.

Unfortunately, boiler steel and others parts of energy plants are exposure on high temperature and pressure for the long period of time, and corrosion environment connected with fuels combustion. During combustion of solid fuels there are generated solid, liquid and gaseous compounds that can be corrosive to heat-transfer surfaces. Coal and biomass can contain significant amount of sulphur or chlorine which can accelerate steel corrosion leading to important operating problems because of the degradation of metallic material. Moreover the chemical composition of coal and biomass ashes can cause operating problems like slagging, fouling, agglomeration leading to degradation of metal surface as well. Thus, the strength of boiler steel decreases with the time under high temperature and corrosion environment.

In this project at least two kinds of boiler steel with different amount of chromium (from 2 % to c.a. 10 % of Cr) and corrosion resistant will be studied. The main aim of this project is to study the mechanical and structural properties of boiler grade steel. The study the influence of temperature, the studied steel samples will be heated in muffle furnace at 700C through 2 months and then they will be investigated. The following mechanical properties are planned to study of the reference and after the temperature tests steel samples: hardness of steel, tensile strength, flexural strength, yield stress, dynamic strength and dilatometry investigation. Furthermore, the structure analysis of steel will be carried out using scanning electron microspore with EDS detector and the thermal analyser will be used to study the thermal behaviour under oxidizing/reduction atmosphere.

Duties and responsibilities:

1. Student will do the literature review of boiler steel properties investigation.

2. Student will carry out the long term high temperature tests of studied steel samples.

3. Student will characterize the mechanical properties doing selected tests.

4. Student will study the structural changes using electron microscope and thermal properties using thermal analyzer.

5. Student will summarize his outcomes in a report.

Requirements for technical skills: Office Skills (Word, Excel); Matlab; Conducting tests (material characterization) skills are an asset.

Requirements for interpersonal skills: Ability to work in team environment; Ability to work with minimum supervision.

Degree, courses and discipline prerequisites:

1. Mechanics of materials (MECH 2301)

2. Macro-and-Micro Manufacturing Methods (MECH 3503)

3. Solid Mechanics and Materials Laboratory (MECH 3502)


RESEARCH AND DEVELOPMENT OF A CLOSED LOOP WIND TUNNEL

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Ronald Hanson

Number of positions available: 2

Contact: hansonre@yorku.ca

Summary of project: 

The objective of this project is to contribute to the design and manufacture of a custom closed-loop wind tunnel. The main components of a closed-loop wind tunnel include the test section, settling chamber, contraction, diffuser(s), blower/fan, turning vanes, flow conditioning, and heat exchanger. Careful design considerations to the aforementioned components are necessary to achieve a low level of flow turbulence and high uniformity that is required to simulate atmospheric conditions for aerodynamic measurements. Closed-loop systems provide recirculation of air that can be seeded for purposes of optical-based measurements and reduced system losses.

The key goals of this project include research, development and manufacturing of two wide-angle diffusers, one downstream of the test section, and the other downstream of the fan. Wide-angle diffusers are an important component of a wind tunnel to make economic use of space and design is critical to ensure attached flow. Since the diffusers are part of a larger system, computational fluid dynamic simulations will be used to determine the performance of the diffusers in the wind tunnel circuit. A second related project includes the design of a test section with variable pressure gradient adjustment to account for boundary layer growth of the tunnel walls. Many experiments are sensitive to pressure gradients that can alter flow characteristics. Analysis of the boundary layer growth and simulations are required to design sufficient variability of the test section dimensions.

The successful applicants will gain skills in computational fluid dynamics, engineering design/analysis and practical manufacturing skills, which will support future employment in a range of Ontario companies in the aerospace, wind engineering, and consulting sectors.

Duties and responsibilities:

(a) Research wide angle diffuser shapes and profiles to obtain attached flow.

(b) Apply computational fluid dynamics (CFD) to model flow performance.

(c) Prepare engineering drawings.

(d) Prepare a final report of the design.

Requirements for technical skills: Experience with Solidworks or other CAD packages Mechanically oriented, i.e. ability to work in machine shop 3D Printing/ Manufacturing skills LE/MECH 3202 3.0 Fluid Dynamics / Heat and Flow Engineering Principles, use of CFD Software as an asset.

Requirements for interpersonal skills: Student should be able to work within a team environment. Student should be able to communicate challenges and express problems logically.

Degree, courses and discipline prerequisites: LE/MECH 3202 3.0 Fluid Dynamics preferred.


3D BONE MARROW ENGINEERING

Position type: LURA

Department: Mechanical Engineering

Professor: Terry Sachlos

Number of positions available: 2

Contact: sachlos@yorku.ca

Summary of project: 

Bone tissue contains the bone marrow that houses hematopoietic stem cells (HSC) that are responsible for continuously regenerating blood tissue throughout one’s lifetime. Bone marrow transplants, also called HSC transplants, are life-saving procedures used to treat leukemia patients, but in short supply. Many more patients could benefit from a bone marrow transplant if the number of HSC in each donor sample could actually be augmented. For this advancement to be achieved a more detailed understanding of the interplay between HSC and their native bone marrow environment, or niche, is required. However, experimentation with HSC and progenitors (HSPC) is challenging. When removed from their native bone marrow niche and placed in vitro, HSC and progenitor (HSPC) cells very quickly (24-72h) lose their function. Mounting evidence suggests that the bone marrow extracellular matrix (ECM) is a critical, yet underappreciated, component of the niche that may be instructive to stem cell regulation. If the desire is to expand these cells in vitro, then culture conditions that recapitulate the ECM environment need to be developed. This proposal aims to develop technology that discovers in vitro niche conditions and applies this knowledge to elucidate niche interactions. A combinatorial, bottom-up approach that systematically assembles and tests individual and combinations of ECM components will be developed 3with the intent of elucidating the contribution of each component to HSPC function. In addition, 3D Printing technology will be employed to create a vascular system with the ECM and support HSPC survival in thick 3D constructs. Finally, these technological developments will be implemented in a novel 3D assay able to identify molecular targets that regulate stem cell function.

In the long term, this research can lead to the development of readily available tissue-matched engineered bone marrow tissue to be used for transplantation. Canadian bone marrow transplant patients stand to benefit the most with shorter waiting times. Canadian healthcare savings can also be realized by quickly treating patients and removing them from ever-lengthening transplant waiting lists and the associated healthcare costs in managing sick waiting patients.

Duties and responsibilities:

1) Designing and manufacturing of 3D tissue engineering scaffolds

2) Assisting graduate student with experiments

Requirements for technical skills: Experience with cell culture would be an asset but not essential.

Requirements for interpersonal skills: Strong communication and organizational skills, independent worker.

Degree, courses and discipline prerequisites: N/A


COMPRESSIBILITY AND SHEAR STRENGTH OF SOIL-RUBBER CRUMBS MIXTURES

Position type: LURA, NSERC USRA

Department: Civil Engineering

Professor: Jit Sharma

Number of positions available: 1

Contact: jtsharma@yorku.ca

Summary of project: 

Given the increasing emphasis on sustainable construction practices, recycled materials, such as rubber tire crumbs, are increasingly being used either in place of or in combination with granular fills for the construction of earth structures, such as highway embankments. Rubber tire crumbs have the dual advantage of being lighter than soil while mobilizing comparable shear strength; however, they are also considerably more compressible than soil grains, which can potentially result in serviceability issues emanating from excessive deformation. Existing soil mechanics theories, which assume the soil grains to be incompressible, are unable to explain the stress-deformation and shear strength behaviour of fills that include substantial amounts of rubber tire crumbs in them. The main goal of the project is to correlate the compressibility and shear strength behaviours of soil-rubber tire crumbs mixtures with the amount of rubber tire crumbs in the mixtures. This goal will be achieved using a comprehensive laboratory testing program involving compaction tests, direct shear tests and one-dimensional compression tests with settlement and pore pressure measurements. Two different grades of sand and rubber tire crumbs will be used to ascertain the effect of particle size on the compressibility and shear strength of the mixtures. Findings from this project will be used by the proponent to develop a more comprehensive research program of investigating the stress-deformation behaviour of various kinds of compressible geomaterials, including municipal solid waste, peat, etc.

Duties and responsibilities:

The student will be responsible for: preparing samples; carrying out the laboratory tests; collecting, plotting, analyzing, and reporting test results; and, writing a technical report. The student is expected to work closely with the technical support personnel in the Geotechnical Engineering lab as well as with the graduate students in the proponent's research group.

Requirements for technical skills:

Conducting geotechnical lab tests, including electronic data collection; data plotting and analysis using MS Excel or equivalent (some training in both will be provided at the beginning of the project). Previous experience of working in a geotechnical lab would be an asset.

Requirements for interpersonal skills: Ability to work independently as well as in a collaborative team environment.

Degree, courses and discipline prerequisites:

Ideally, the student should be in Civil Engineering program and have taken CIVL 2120 Civil Engineering Materials and CIVL 3110 Soil Mechanics; however, the proponent is willing to consider a student from another program who is able to demonstrate relevant skills and aptitude that the project needs.


TESTING AND MODELLING OF THE ELASTOMERS IN TENSION AT HIGH STRAIN RATES

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Aleksander Czekanski

Number of positions available: 1

Contact: alex.czekanski@lassonde.yorku.ca

Summary of project: 

The mechanical response of elastomers are greatly dependent on the applied strain rate. Nonlinear constitutive models can be used to model the response of the Elastomers at high strain rates. Experimentally testing the stress strain response of elastomers sample is used to derive the model parameters. To test elastomers at high strain rates a modified Kolsky tension bar is developed at IDEA-Lab.

This research objective is to conduct experiments on the newly developed Kolsky tension bar to evaluate the stress-strain characteristics of elastomer materials. The strain rate at which the testing will be conducted ranges from 100-10000/s.

Duties and responsibilities:

Task 1 - Literature review about Elastomers

  • Student is to run a literature review on various types of rubber, rubber modifiers and their engineering applications.

  • The student will summarize their findings in a report.

Task 2 - Experimental characterization of Elastomers

  • Conduct high strain rate tension experiments on elastomeric samples.

  • Perform FE analysis to validate the experimental design.

  • Extension of the experiment to incorporate the temperature effect.

Requirements for technical skills:

  1. Office Skills (Word, Excel);

  2. Matlab;

  3. Machine shop and prototyping skills

Requirements for interpersonal skills:

  1. Ability to work in team environment;

  2. Ability to work with minimum supervision

Degree, courses and discipline prerequisites:

  1. Mechanics of materials (MECH 2301)

  2. Machine elements design (MECH 2409)

  3. Macro-and-Micro Manufacturing Methods (MECH 3503)

  4. Solid Mechanics and Materials Laboratory (MECH 3502)


THE ENVIRONMENTAL IMPACT OF ENGINEERED MATERIALS DEGRADATION IN POROUS CONSOLIDATED MEDIA

Position type: LURA, NSERC USRA

Department: Civil Engineering

Professor: Magdalena Krol

Number of positions available: 2

Contact: magdalena.krol@lassonde.yorku.ca

Summary of project: 

This project will examine the physical and chemical processes occurring in a deep geologic repository for used nuclear fuel, including the interactions of the containers, corrosion, groundwater, clay, and microorganisms. This project will increase confidence in the plan for safe permanent disposal of Canada's nuclear fuel waste.

Duties and responsibilities:

Lab work, computer modelling, and literature review.

Requirements for technical skills: Good understanding of environmental processes. Computer simulation experience as an asset.

Requirements for interpersonal skills: Good communication skills, team player.

Degree, courses and discipline prerequisites: Completed CIVL 3240 and CIVL 3110.


GREEN WALL EFFECT ON INDOOR AIR QUALITY

Position type: LURA, NSERC USRA

Department: Civil Engineering

Professor: Magdalena Krol

Number of positions available: 1

Contact: magdalena.krol@lassonde.yorku.ca

Summary of project: 

Implementation of indoor and outdoor green walls can be very beneficial to humans and our environment. Therefore, the goal of this project is to determine how common indoor plants would affect indoor air quality; specifically indoor temperature, humidity, and removal of indoor air pollutants.

Duties and responsibilities: Lab work, literature review.

Requirements for technical skills: Good understanding of environmental processes. Previous lab work as an asset.

Requirements for interpersonal skills: Good communication skills (written and oral), team player.

Degree, courses and discipline prerequisites: Completed CIVL 2240.


DEVELOPMENT OF HEALTH MONITORING SENSORS FOR ADVANCED CARBON FIBER COMPOSITE STRUCTURES

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Gerd Grau and Garrett Melenka

Number of positions available: 1

Contact: grau@eecs.yorku.ca

Summary of project: 

Braiding is a high rate fabrication method that produces near-net-shape structures by interlacing continuous fibers into a pre-form architecture. Braided composites are created by impregnating the braid pre-form in a matrix material. Braiding is an attractive manufacturing method since a variety of matrix, fiber and braid geometries can be used to tailor mechanical properties. BC offer improved impact resistance and energy absorption characteristics over conventional laminated composite structures.

A major challenge with braided composites is the measurement and prediction of failure. The difficulty in predicting failure limits the use of braided composites in industrial applications. Structural health monitoring (SHM) is a technique which integrates sensors in advanced engineering structures. The addition of SHM sensors within braided composites will help to increase industrial adoption of braided composite structures.

Duties and responsibilities:

Integrate health monitoring sensors within braided composite structures. Conductive carbon fiber yarns will be incorporated into composite braids to perform health monitoring. Experiments will be required to validate the integrated health monitoring sensors accuracy and repeatability.

This work will involve the fabrication of conductive carbon fiber yarns for integration within braided structures. Mechanical testing will be required to validate in-situ strain measurements for braided composite structures.

Requirements for technical skills:

Working knowledge of chemistry to treat carbon fiber yarns for health monitoring. Experimental data collection and reporting skills. Documentation and analysis of experimental results. Solidworks, MATLAB or similar programming language as an asset.

Requirements for interpersonal skills:

Student should have team working skills to work with a multi-disciplinary team of engineers.

Degree, courses and discipline prerequisites: Mechanical Engineering or Electrical Engineering student.


SOLAR DESALINATION AND STEAM GENERATION

Position type: LURA

Department: Mechanical Engineering

Professor: Thomas Cooper

Number of positions available: 1

Contact: tcooper@yorku.ca

Summary of project: 

Sunlight constitutes a virtually inexhaustible source of clean and freely-available energy. The vast majority of solar energy technologies rely on the photovoltaic effect which directly converts incident sunlight into electricity. However, sunlight can also be efficiently converted into heat, which can then be used for a wide range of applications including: space heating, domestic hot water production, industrial processes, or even to displace fossil fuels as the heat source in conventional power plants. One process of particular interest is solar desalination, where solar heat is used to sustainably convert undrinkable seawater and contaminated water into clean drinking water. A significant challenge of this process is that the salts and impurities in the feed water tend to clog and degrade the system. This project will investigate a new type of solar desalination technology which is inherently resistant to clogging. The goal of the project will be to build a prototype of the new solar desalination system and test it under real outdoor conditions.

Duties and responsibilities:

The student will be responsible for designing a prototype of a solar desalination system, developing a thermal model to predict the performance of the prototype, and ultimately building and testing the prototype under real outdoor conditions.

Requirements for technical skills: Knowledge of heat transfer. Experimental/hands-on experience is an asset.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: N/A


MICROFLUIDIC CELL CULTURE FOR DRUG TEST

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Ebrahim Ghafar-Zadeh

Number of positions available: 2

Contact: egz@cse.yorku.ca

Summary of project: 

Traditional cell culture routine relies on using large petri-dishes and large amount of cell culture medium. This routine allows biologists to study cellular activities using a large number of cells. For instance, in order to test the effectiveness of a drug on cancer cells, the cancer cells should be cultured in a petri-dish and specific amount of drug should be introduced to the cells. In this drug test process, different concentrations of drugs should be tested on cells using a large number of petri-dishes including cells and culture medium. Given the fact, each test requires a 24-hour time for the cell culture and cell viability test, for 100 different petri-dishes, the drug assessment process requires more than 3 months. Therefore, this is a time consuming and expensive procedure. The miniaturization of cell culture is a solution using microfluidic technology. Microfluidic Technology has attracted the attentions for developing micro-scale fluidic capillaries, chambers and other devices suitable for cellular analysis. A microfluidic fabrication process consists of photo-lithography and polymeric techniques to build for instance, an array of microfluidic cell culture wells. As described in [1], a single cell or a limited number of cells (e.g. 100) can be cultured in a microfluidic structure. A large number of micro-chambers in a single microfluidic chip enables high throughput analysis of cells. High-throughput analysis of cellular behavior requires uniform conditions that can be provided using microfluidic structure similar to [2]. High throughput cell culture is a challenging approach suitable for accelerate the drug test an drug discovery.

In this project, the students will first be trained to

1. Design and implement some microfluidic devices

2. Perform the culture, cell counting and cell viability test

Then, they will be involved in team for designing an array of 10x10=100 small chambers for cell culturing purpose.

Duties and responsibilities:

After training ( see the description of project), the students should use design the microfluidic structure ( using CAD tools), implement the device ( using lithography) and culture the cells, The cells in each chamber should be counted after 24 hours. The process should be repeated in order to optimize the cell viability. In this process, N2A cell line is used.

Requirements for technical skills: N/A

Requirements for interpersonal skills: Hardworking and interested in life science applications.

Degree, courses and discipline prerequisites: Second year (or upper) in any field of Engineering/Science.


Embedded Attentive Sensing

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: James Elder

Number of positions available: 2

Contact: kailin@yorku.ca

Summary of project: 

Video cameras generate massive quantities of data, but using these data effectively requires intelligent software and hardware. Inspired by the human visual attention and oculomotor systems, our laboratory has invented and patented a series of attentive sensor devices that automatically orient an attentive camera to capture the most important details in a scene. Last summer, the applicant, Ryan Dowling, co-invented a new form of this sensor that is even faster and more accurate than our previous prototypes. A potential application for this sensor is in small battery-powered unmanned aerial vehicles (UAVs). Given limits on flight time imposed by the battery, it can be vital that maximally informative imagery is extracted on each mission. However, to deploy attentive sensing on a small UAV platform, two technical challenges must be addressed. First, the device must be made much smaller and lighter. Second, the attentive sensing control algorithms must be embedded in the onboard processor, as the bandwidth of telemetric links are too limited to support real-time attentive control.

Duties and responsibilities:

The student will design and build a novel miniaturized version of our attentive sensor suitable for deployment on a small UAV platform, and will port the sensing and control software to the NVIDIA Jetson TK1 platform to allow the attentive sensor to be operated autonomously without telemetric control.

Requirements for technical skills:

  1. Algorithm design

  2. Programming in C++ and MATLAB

  3. Systems hardware/software design

  4. Embedded systems design

  5. Ability to work in a team.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: EECS students (CS, CE, EE) or students with strong programing and mathematics skills preferred.


Application of Attentive Sensing to Surveillance

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: James Elder

Number of positions available: 2

Contact: kailin@yorku.ca

Summary of project: 

Video cameras generate massive quantities of data, but using these data effectively requires intelligent software and hardware. Inspired by the human visual attention and oculomotor systems, our laboratory has invented and patented a series of attentive sensor devices that automatically orient an attentive camera to capture the most important details in a scene. Last summer, we invented a new form of this sensor that is even faster and more accurate than our previous prototypes. This project will address the application of attentive sensing to Surveillance. In particular, the goal is to maximize the rate of accurate fixations of human face in crowded scenes. More information on the lab can be found at elderlab.yorku.ca.

Duties and responsibilities:

The student will assist in fine-tuning the sensor to the application and evaluate its performance and will work closely with graduate students, postdoctoral fellows, software engineers and research scientists in the lab, as well as with the Principal Investigator, Professor James Elder. The student will obtain experience in systems programming in MATLAB and C++, and the design of computer vision algorithms and systems.

Requirements for technical skills:

  1. Algorithm design

  2. Programming in C++ and MATLAB

Requirements for interpersonal skills: Ability to work in a team.

Degree, courses and discipline prerequisites: EECS students (CS, CE, EE) or students with strong programing and mathematics skills preferred.


Application of Attentive Sensing to Sports Videography

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: James Elder

Number of positions available: 2

Contact: kailin@yorku.ca

Summary of project: 

Video cameras generate massive quantities of data, but using these data effectively requires intelligent software and hardware. Inspired by the human visual attention and oculomotor systems, our laboratory has invented and patented a series of attentive sensor devices that automatically orient an attentive camera to capture the most important details in a scene. Last summer, we invented a new form of this sensor that is even faster and more accurate than our previous prototypes. This project will address the application of attentive sensing to Sports Videography. More information on the lab can be found at elderlab.yorku.ca.

Duties and responsibilities:

The student will assist in fine-tuning the sensor to the application and evaluate its performance and will work closely with graduate students, postdoctoral fellows, software engineers and research scientists in the lab, as well as with the Principal Investigator, Professor James Elder. The student will obtain experience in systems programming in MATLAB and C++, and the design of computer vision algorithms and systems.

Requirements for technical skills:

  1. Algorithm design

  2. Programming in C++ and MATLAB

  3. Control systems

Requirements for interpersonal skills: Ability to work in a team.

Degree, courses and discipline prerequisites: EECS students (CS, CE, EE) or students with strong programing and mathematics skills preferred.


Application of Attentive Sensing to Distance Learning

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: James Elder

Number of positions available: 2

Contact: kailin@yorku.ca

Summary of project: 

Application of Attentive Sensing to Distance Learning. Video cameras generate massive quantities of data, but using these data effectively requires intelligent software and hardware. Inspired by the human visual attention and oculomotor systems, our laboratory has invented and patented a series of attentive sensor devices that automatically orients an attentive camera to capture the most important details in a scene. An important potential application of this technology is distance learning. One of the challenges is to allow students to communicate effectively with the lecturer. For example, when a student asks a question, communication will be more effective if the instructor has a zoomed view of the student's face, so that s/he can interpret expressions etc. By the same token, it can be helpful if the students also have a zoomed view of the professor as she moves around the room. The goal of this project is to apply attentive sensing technology (www.elderlab.yorku.ca) to this problem. This technology is able to monitor a large environment such as a classroom and direct a high-resolution 'attentive' sensor to events of interest. More information on the lab can be found at elderlab.yorku.ca.

Duties and responsibilities:

The student will assist in fine-tuning the sensor to the application and evaluate its performance and will work closely with graduate students, postdoctoral fellows, software engineers and research scientists in the lab, as well as with the Principal Investigator, Professor James Elder. The student will:

  1. Study the problem of detecting hand-raises in the preattentive sensor stream

  2. Study the problem of tracking the professor in the preattentive sensor stream

  3. Implement algorithms for detecting hand-raises and tracking the professor based upon these investigations

  4. Evaluate these algorithms in a real-classroom setting, using proprietary attentive sensing technology.

Requirements for technical skills:

  1. Algorithm design

  2. Programming in C++ and MATLAB

Requirements for interpersonal skills: Ability to work in a team.

Degree, courses and discipline prerequisites: EECS students (CS, CE, EE) or students with strong programing and mathematics skills preferred.


Geosensory Internet of Things Network

Position type: LURA, NSERC USRA

Department: Civil Engineering

Professor: Matthew Perras

Number of positions available: 1

Contact: mperras@yorku.ca

Summary of project: 

In geological / geotechnical engineering it is necessary to monitor how the ground is behaving due to infrastructure that has been constructed or natural instability problems. Often these project can be located in remote areas and therefore need to be connected to an Internet of Things network in order to be able to monitor the behaviour in real time. Several existing sites have recently been setup with such networks in Dr. Perras’s research group, one on an island in Finland and the other in the King’s Valley of Egypt. This project will involve modifying the existing operating units, testing sensors and device performance under controlled climatic conditions in the laboratory, and designing new systems as we learn from the existing stations. Programming and soldering experience would be an asset, but not mandatory. Many of the sensors come with existing code that can be integrated easily into the operating code. Two systems are currently being used, the commercial Libelium Smart Agriculture Waspmote and custom Arduino systems. We welcome all backgrounds to apply to this interesting, multidisciplinary project.

Duties and responsibilities:

  • Program commercial sensor data acquisition unit for remote data collection (Libelium) - basic programming experience an asset.

  • Calibrate sensors in the lab to ensure environmental influences are known.

  • Help design, construct (soldering experience an asset), test, and deploy custom built sensor systems using the Arduino platform.

Requirements for technical skills: Programming, Arduino, soldering

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: N/A


Development of a Thermal Analytical Model for an Electrolytic Capacitor-less Photovoltaic Micro-converter

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: John Lam

Number of positions available: 1

Contact: johnlam@cse.yorku.ca

Summary of project: 

In order to reduce global warming, the use of clean renewable energy resources will diversify our energy supply, and relieve the burden of expensive fossil fuel imports. Among all renewable energy resources, photovoltaic (PV) energy has the highest growth rate with its global capacity increased from 5.1GW (Giga-Watts) to 402GW from 2005 to 2017. A power electronic converter (also called a micro-converter) is typically placed at the back of the PV panel to step-up the panel output voltage (~ 30 – 35V) such that it matches that of the grid. The micro-converter also allows the PV energy system to extract maximum amount of energy from the renewable source for different irradiation level. Although the lifespan of a PV panel is expected to last more than 20 years, the limiting factor on the entire PV system lifetime is the micro-converter. In particular, the use of electrolytic capacitors in existing micro-converters has shown to be the most unreliable component that is prone to failure when it operates under extreme temperature. This project is to develop an advanced thermal circuit model that is able to predict the thermal performance, and hence the lifetime expectancy of an electrolytic capacitor-less PV micro-converter. The thermal models of all the semiconductor and magnetic devices used in the micro-converter will be developed in Powersim (an advanced power electronics simulation software) and their performance will be investigated. This research project will be conducted at the Power Electronics Laboratory for Sustainable Energy Research.

Duties and responsibilities:

  • Conduct research in Powersim to develop thermal models for various parts in the micro-converter

  • Analyze the designs, evaluate the performance

  • Report to the supervisor

Requirements for technical skills: MATLAB, electronic devices, circuits

Requirements for interpersonal skills: Time management, communication

Degree, courses and discipline prerequisites: Electrical or Mechanical Eng, prerequisites: EECS 2210 or EECS 3505


Thermal Performance Investigation of a Silicon-Carbide (SiC)-based Step-up Power Converter Module

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: John Lam

Number of positions available: 1

Contact: johnlam@cse.yorku.ca

Summary of project: 

Wind energy is an emerging energy source that is capable of powering millions of homes. For effective long distance power transmission from offshore wind farms, high voltage power transmission is required. To significantly reduce the weight and size of the step-up voltage conversion unit used in offshore wind turbines, the use of medium to high frequency power electronic step-up converters to replace the conventional low frequency power transformers is an attractive solution. Recently, the use of wide-bandgap semiconductor devices (such as silicon-carbide (SiC) devices) has attracted a lot of attention for power electronics research due to their much higher thermal conductivity and operating junction temperature compared to their silicon (Si) devices counterpart. This research project will investigate the thermal performance of a newly developed SiC based medium voltage step-up power converter. The thermal performance of all the semiconductor devices and the converter will be investigated in Powersim (an advanced power electronics simulation software). The thermal behavior of a laboratory-scale prototype of the SiC based converter will also be studied. This research project will be conducted at the Power Electronics Laboratory for Sustainable Energy Research.

Duties and responsibilities:

  • Conduct research in Powersim

  • Analyze the designs

  • Investigate the thermal performance of a hardware prototype

  • Report to the supervisor

Requirements for technical skills: MATLAB, electronic devices, circuits. Power electronics as an asset.

Requirements for interpersonal skills: Time management, communication

Degree, courses and discipline prerequisites: Electrical or Mechanical Eng: prerequisites, EECS 2210 or EECS 3505


Benefits of green infrastructure

Position type: LURA, NSERC USRA

Department: Civil Engineering

Professor: Usman T. Khan

Number of positions available: 2

Contact: usman.khan@lassonde.yorku.ca

Summary of project: 

Green infrastructure is widely used to manage stormwater in urban areas to control flooding, protect downstream infrastructure, provide social and economic benefits, and support natural ecosystems. However, maintenance on these types of infrastructure is not performed frequently enough, leading to reduced performance. This research aims to develop a machine learning approach to identify when maintenance is required on green infrastructure.

Duties and responsibilities:

Conduct infiltration experiments on permeable pavements and collect data to train a machine learning algorithm and develop a supporting smart phone application. Infiltration experiments will be conducted in the field and lab. Some MATLAB experience is necessary.

Requirements for technical skills: Basic MATLAB; Civil Engineering background preferred.

Requirements for interpersonal skills: Teamwork (will work with a team of ~10 graduate and undergraduate students).

Degree, courses and discipline prerequisites: Civil engineering students


Improvement of GPS smartphone positioning

Position type: LURA, NSERC USRA

Department: Earth and Space Science and Engineering

Professor: Sunil Bisnath

Number of positions available: 2

Contact: sunil.bisnath@lassonde.yorku.ca

Summary of project: 

Low-cost GPS, and now broadly GNSS (Global Navigation Satellite System), chips in smartphones are increasing in capabilities. Coupled with users being able to access raw measurements from some models, the York GNSS Lab has recently begun applying high-performance measurement processing techniques to improve positioning accuracy from 10s of metres to the centimetre level. Applications for such performance include navigation, augmented reality apps, gaming, etc. Research areas of interest include: precision of raw satellite ranging measurements, performance of cellphone antennas, availability of measurements in obstructed, urban environments, tuning of processing methods for such measurements, and solution testing.

Duties and responsibilities:

Working with a team of PhD and MSc students in the collection, analysis and processing of smartphone GNSS data, and the tuning of GNSS measurement processing algorithms. This work is globally leading-edge, so there is the high likelihood of conference and journal paper preparation experience as well.

Requirements for technical skills:

Knowledge of GNSS specifically, and Geomatics in general, would be very helpful. As well as the scientific method, and data analysis skills.

Other assets: Highly motivated. Can work independently. Interested in graduate school.

Requirements for interpersonal skills:

A quick learner. Focused and organized. Strong communications skills. Proven ability to work in a group and individually.

Degree, courses and discipline prerequisites:

Current BEng or BSc student in Geomatics or a related field. Having taken ESSE 3670 “Global Navigation Satellite Systems” or equivalent would be very helpful. Strong math and coding backgrounds are significant assets.


Web-based Simulator for Advanced Constitutive Models for Geomaterials

Position type: LURA, NSERC USRA

Department: Civil Engineering

Professor: Jit Sharma

Number of positions available: 1

Contact: jtsharma@yorku.ca

Summary of project: 

The proponent has developed a web application to compare its experimental data with theoretical predictions. It provides an online sandbox for physicists, academics, and engineers to test their predictions of the mechanical behavior of a geomaterial against empirical data obtained in a laboratory. The proponent expects to integrate this web application into a larger system for analysis and design by members of the geotechnical engineering community. The web application consists of two parts: a web interface and a simulator. The interface is the visualization engine for the simulator. The simulator predicts stress histories based on user input and a suite of user-selectable constitutive models. The interface accepts the user input, sends it to the simulator, accepts stress history predictions from the simulator, and displays the output in a graphical format. The interface supports direct user interaction with the graphical output. The current version of this application is a proof of concept implementation. The Department is seeking support for an undergraduate student to complete the next phase in its development.

Duties and responsibilities:

  • Re-factor the existing code to make it more modular, easier to maintain, more efficient in rendering and easier for other developers to pick up.

  • Incorporate leading-edge graphing technologies to display the output from the simulator, compare it to uploaded empirical data collected in the laboratory and improve rendering of the graphical output.

  • Provide proper documentation (both in code and external).

  • Include testing and related utilities to guarantee a robust codebase.

  • Increase security.

  • Include options to save and retrieve projects.

Requirements for technical skills:

Familiarity with modern web development technologies including HTML5, client-side and server-side technologies, JavaScript and the React library; familiarity with modern graphics libraries including Plotly; familiarity with modern C++ programming intermediate level. Assets include some familiarity with theoretical geomechanics.

Requirements for interpersonal skills: Ability to work independently and within a research team environment.

Degree, courses and discipline prerequisites: A completed third year of a computer science or computer engineering degree.


Development of a GPS-reflectometry sensor for soil moisture determination

Position type: LURA, NSERC USRA

Department: Earth and Space Science and Engineering

Professor: Sunil Bisnath

Number of positions available: 2

Contact: sunil.bisnath@lassonde.yorku.ca

Summary of project: 

GPS, and now broadly GNSS (Global Navigation Satellite System), technology is ubiquitous and provides freely-available signals for a multitude of scientific and engineering applications. One scientific application that York’s GNSS Lab has been investigating is the reception of ground-reflected signals for the purpose of inferring properties of the surface, such as surface soil moisture. This science is its early days but represents the opportunity for very low-cost remote sensing of global soil moisture. Students will work on the design, development and testing of our next generation Field Programmable Gate Array (FPGA)-based GNSS-reflectometry receiver that is based on a software-defined radio (SDR) design. And also, the design, development and integration of supporting payload components: development board, PCB design and fabrication, computational testing, radio front-end testing and assembly, communications, data storage, housing, etc.

Duties and responsibilities:

Working with a team of Post-Docs and PhD students in the design, development and testing of one or two specific payload components. This work is globally leading-edge, so there is the high likelihood of conference and journal paper preparation experience as well.

Requirements for technical skills:

Experience with SDR coding, FPGA design, embedded systems, and/or PCB layout. Other assets: Highly motivated. Can work independently. Interested in graduate school.

Requirements for interpersonal skills:

A quick learner. Focused and organized. Strong communications skills. Proven ability to work in a group and individually.

Degree, courses and discipline prerequisites:

Current BEng or BSc student in Space Engineering, Electrical Engineering or a related field. Having taken PHYS 3050 “Electronics I”, PHYS 3150 “Electronics II” or equivalent courses. Strong math and coding backgrounds are significant assets.


Implementing Randomized Algorithms in Java

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Franck van Breugel

Number of positions available: 1

Contact: franck@eecs.yorku.ca

Summary of project: 

"When a field has good benchmarks, we settle debates and the field makes rapid progress." David Patterson

Edmund Clarke, Allen Emerson, and Joseph Sifakis won the Turing award, which is often considered the Nobel prize in Computer Science, for their foundational work on model checking. A model checker is a tool that can find intricate bugs in software that ordinary testing techniques fail to detect. Nowadays, many software systems rely on randomness. For example, it is well known that randomness provides computer games with the ability to surprise players, which is a key factor in their long-term appeal. Randomness is also prominent in machine learning, as exemplified by the use of randomized algorithms such as stochastic gradient descent. Randomness is also ubiquitous in cryptography. These are just three examples that show how pervasive randomness is in today's software. A probabilistic model checker hunts for complicated bugs in software with randomness. Although this field of research is a few decades old, it still lacks good benchmarks. The main focus of my research group for the Summer of 2019 is the development of such benchmarks. You can contribute to this effort by implementing various randomized algorithms in Java.

Duties and responsibilities: Implement randomized algorithms in Java.

Requirements for technical skills: Java

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: EECS 2011 and EECS 3101 are helpful.


'ENAbling MEdia for Literacy' (ENAMEL)

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Melanie Baljko

Number of positions available: 2

Contact: mb@cse.yorku.ca

Summary of project: 

The objective of the 'ENAbling MEdia for Literacy' (ENAMEL) research project is to develop and evaluate innovative technologies to support digital and non-digital literacies in children. The focus is on low-cost, Do-It-Yourself digital technologies, made available as open technologies and with highly accessible instructions. To date, Speech Generating Devices and a Braille teaching devices have been developed. These technologies provide innovative approaches to supporting the development of functional knowledge among users and other stakeholders concerning written and spoken communication and digital literacies. This project espouses user-centered rather than technology-centered design approaches, and seeks to critically reflect on the hidden assumptions, ideologies and values underlying the design of such technologies.

Duties and responsibilities may include*:

  • targeted literature reviews and research syntheses

  • 3D prototyping and 3D printing

  • electronics design and prototyping (Raspberry Pi, sensors and actuators)

  • software design, implementation, and evaluation (Java, python, shell scripting)

  • assisting with developing and conducting evaluation studies, analyses of usability and user experience

  • preparation of data sets, data analysis (qualitative and/or quantitative)

  • development of materials for scientific communication, such as information visualizations, info graphics, diagrams, graphic design of posters and other materials

  • scientific writing

    *Given the scope of the research project, there is flexibility in how each of the two available positions are scoped; the duties and responsibilities of the positions will be adapted as per the successful candidate's background knowledge and skills.

Requirements for technical skills:

Previous experience in at least two of the following:

  • programming and software development;

  • prototyping with Raspberry Pi or other single-board computers using different sensors and articulators;

  • 3D modeling software (e.g., openSCAD, Rhino, SketchUp);

  • interaction/UX design;

  • qualitative and/or quantitative data collection and analysis;

  • technical and/or scientific writing and communication;

  • graphic design or other design.

Other assets: Courses completed in Science and Technologies Studies; Critical Disabilities Studies, Social Determinants of Health and other courses from Sociology.

Requirements for interpersonal skills:

Solid verbal and written communication skills. Ability to work without close supervision. Strong organizational and project management skills. Ability to operate in a interdisciplinary team environment.

Degree, courses and discipline prerequisites:

Flexible: could include Digital Media, Electrical Engineering, Computer Engineering, Computer Science, Education, STS, Sociology, Design, Critical Disability Studies. EECS3461 User Interfaces (or cognate course from other institution) and/or other UI/UX courses strongly preferred.


Software/Firmware Development for a Wearable Brain EEG monitoring device

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Hossein Kassiri

Number of positions available: 2

Contact: hossein@eecs.yorku.ca

Summary of project: 

Brian injury is the leading cause of death and disability in North America. The annual cost of hospitalization alone is 31 billion dollars. This is partly due to the fact that there is currently no validated method for monitoring of the brain activity in the ER (emergency room). As such, the “wait and see” approach results in lost opportunities to treat brain injury complications, thus contributing to poor outcome and increasing the length of hospital stay. Today, around 40% of brain injury patients in coma experience seizures that go untreated. When anti-seizure medication is not provided, there is the risk of increased morbidity, prolonged stay, poor outcome and increased long term socioeconomic burden. Studies have shown that shortening the hospital stay of patients with brain injury by 1 day could save the health care system $400 million annually.

In integrated Circuits and Systems Lab, we have developed a wearable device that will be used as a low-cost brain monitoring solution in the emergency room. The device will host a proprietary algorithm for early detection of epilepsy seizures. It will be used to monitor real-time brain activity of the patients who come to the ER with brain injury, to identify cases that require immediate care and treatment.

Duties and responsibilities:

The student will be responsible for the design and testing of a printed circuit board (PCB) that receives brain electrophysiological signals from multiple recording sites; analyze, decode, and organizes them; and transmit them through a wireless link to a handheld (e.g., cellphone) or stationary (e.g. a laptop) device. The board must be designed while the strict power and area budgets of a medical device taken into account.

Requirements for technical skills:

  • Experienced in Verilog programming.

  • Familiarity with electronic circuits and systems.

  • PCB design experience is a plus.

  • Self-driven and interested in the field of biomedical electronics.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites:

  • Electronic circuits

  • Verilog coding

  • Prerequisite: EECS 2210 and 3201 or equivalent.


Wireless implantable Optical Brain Stimulators

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Hossein Kassiri

Number of positions available: 2

Contact: hossein@eecs.yorku.ca

Summary of project: 

Current treatment options for epilepsy are inadequate as too many patients suffer from uncontrolled seizures and from negative side effects of treatment. For years, electrical stimulation was the solution to suppress undesired neurological events. However, electrical stimulation methods strongly suffers from lack of specification. Likewise, while stimulation is relatively efficient at exciting neural activity, inhibiting network activity is often an indirect and power inefficient process in electrical stimulation approaches.

Optogenetics is a biological technique that involves the use of light to control cells in living tissue, typically brain neurons that have been genetically modified. The major benefit of this technique is the unprecedented specificity it provides, allowing spatial, temporal, and cell-type selective modulation of neuronal circuits. Equipped with such tools, it is now possible to begin to address some of the fundamental unanswered questions in epilepsy, to dissect epileptic neuronal circuits, and to develop new intervention strategies.

In Integrated Circuits and Systems Lab, we are developing a wireless optical stimulation device to enable fully-implantable optogenetics experiment in living tissues.

Duties and responsibilities:

The successful candidate will work closely with a Master’s student to develop and test the first prototype of the above-mentioned optical stimulation device using off-the-shelf electronic components.

Requirements for technical skills:

  • Experience with electronic circuit analysis, test, and debugging.

  • Familiar with Verilog coding.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites:

  • Electronic circuits (at least EECS 2210)

  • Verilog coding (at least EECS 3201)


Brain EEG Signal Processing Using Hyperdimensional Computing: Combined Machine Learning and Classification

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Hossein Kassiri

Number of positions available: 2

Contact: hossein@eecs.yorku.ca

Summary of project: 

Accurate detection and efficient control of neurological disorders require sophisticated algorithms that can adjusts themselves from patient to patient and from time to time. Machine learning allows us to accurately classify neural activity data recorded from the brain and decide whether it can be counted as an abnormal activity for a specific patient.

In Integrated Circuits and Systems Lab (ICSL), we are developing/optimizing such algorithms to detect neurological events using brain electrophysiological signals. This interdisciplinary research requires students with solid math and algorithms background who are interested in medical applications of artificial intelligence.

Duties and responsibilities:

There are two positions for this project. The successful candidates will be responsible for either of the following, depending on their experience and interest:

1. Design and development of an ML-based algorithm for brain neural data classification

2. Efficient Bio-signal Processing Using Hyperdimensional Computing: Combined Learning and Classification of EEG Signals

Requirements for technical skills:

  • Both positions require basic programming skills and familiarity with MATLAB.

  • Strong math background is required.

  • The candidates are preferred to have completed a course in signals and systems as well as introduction to machine learning.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: N/A


Software/Firmware Development for a miniature Bluetooth wireless data communication module

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Hossein Kassiri

Number of positions available: 2

Contact: hossein@eecs.yorku.ca

Summary of project: 

Implantable brain neural interfaces are considered as one of the most promising treatment options for over 100 million patients of neurological disorders such as Epilepsy, Parkinson and Alzheimer’s disease who are refractory to pharmacological medications. These devices are used to monitor brain activity and suppress undesired neurological events using detection-triggered electrical stimulation. In Integrated Circuits and Systems Lab (ICSL), we are developing various implantable brain neural interface microsystems used for various applications. A common need for all of these devices is the ability communicate data wirelessly at a high data rate and with low energy consumption. We have developed a miniature circuit board capable of communicating data wirelessly at high data rates. The goal of this project is to develop software/firmware that controls the wireless data communication module and characterize its performance.

Duties and responsibilities:

The successful candidate(s) will work closely with a Master’s student to understand, simulate, program, and test the required firmware for the data communication module.

Requirements for technical skills:

  • Familiarity with electronic circuits and systems (EECS2210).

  • Experience in FPGA programming (EECS3201).

  • Experience with microcontroller programming is a bonus.

  • Self-driven and interested in the field of radio-frequency electronics.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: Required: EECS2210 or equivalent, EECS3201 or equivalent.


Sampling Graph Signals for Big Data Correlation Mining

Position type: LURA

Department: Electrical Engineering and Computer Science

Professor: Gene Cheung

Number of positions available: 1

Contact: genec@yorku.ca

Summary of project: 

Although "big data" is synonymous with the availability of large information set, very often only unlabeled data are available in great quantity, while the task of labeling remains expensive and/or time-consuming. In this project, we study the problem of actively selecting samples for labeling in a large dataset, leveraging on recent advance in graph spectral analysis. In particular, we assume that the targeted signal is smooth (or bandlimited) with respect to an undirected graph containing edge weights that reflect pairwise correlation among samples. We then select nodes on the graph for sampling that best reduce expected reconstruction error given a biased estimator used for signal restoration. We study both the case when the correlation graph is known a priori, and the case when the graph must be estimated from available data. We derive the relationship between the common graph-signal smoothness prior and low-rankness of a matrix. We design fast algorithms to solve the sampling problem based on numerical linear algebra that require neither full eigen-decomposition or inverse of large matrices. The theoretical problem has ample applications in practice, such as sparse image representation, wireless sensing, semi-supervised classifier learning, and matrix completion (including the well-known Netflix Challenge). A student is expected to have basic understanding in digital signal processing, linear algebra and convex optimization, and is proficient in programming in C and MATLAB.

Duties and responsibilities:

The student is expected to develop software algorithms, in C or in MATLAB, in collaboration with other members of the research team, to solve the graph sampling problem for large-scale datasets. The student will pre-process large datasets for core processing, and post-process the computed results for evaluation and presentation. The student will summarize the conducted research in an international conference paper or an internal research report.

Requirements for technical skills: Signal processing, linear algebra.

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: N/A


Highway mapping appliCations using small UAV

Position type: LURA, NSERC USRA

Department: Earth and Space Science and Engineering

Professor: Costas Armenakis

Number of positions available: 1

Contact: armenc@yorku.ca

Summary of project: 

Unmanned Aerial Mapping Systems (UAMS) are now enjoying wide popularity, featuring different types of platforms, for numerous civilian applications such as scientific, commercial, public safety, and recreational activities. They are effective aerial platforms carrying imaging and ranging sensors for geospatial data collection. Usually UAMS are used for generating rapid 3D mapping products over relatively small, remote and inaccessible areas. UAVs can be used in many diverse applications Work on this project includes:

a) UAV-based mapping tasks for typical highway design, planning or as-built elements and report on the practicality and advantages of expanding the use of UAV hardware, sensor, and software technologies and the accuracies obtained and assess them with respect to the accuracies and standards for photogrammetric or engineering / topographic surveys used at the Ministry of Transportation;

b) UAV-based typical inspection projects for bridge, signs, COMPASS cameras poles and other infrastructure and report on the practicality and advantages of applying existing UAV hardware, sensor, and software technologies required to meet current MTO standards and specifications;

c) Investigation of UAV technologies regarding safety, rapid and automated processing, and autonomy of UAV operations;

d) evaluation of current standards and specifications with respect to the application of UAV technologies. The project involves field and office work.

Duties and responsibilities:

The student will involve in field tests (establishing test sites and UAV data acquisition) and in data processing and analysis.

Requirements for technical skills: Photogrammetry, surveying, image processing, sensor integration, data analysis, programming.

Requirements for interpersonal skills: team player, problem solving, communication.

Degree, courses and discipline prerequisites: Geomatics Engineering / Science


Human-Computer Interaction in Virtual Reality

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Rob Allison

Number of positions available: 2

Contact: allison@cse.yorku.ca

Summary of project: 

Students will help design, develop and conduct experiments related to human-computer interaction in virtual environments and digital media. In our lab we have a wide range of apparatus to study human perception in computer-mediated worlds including a new and unique fully immersive virtual environment display. The student would develop interactive 3D virtual worlds and conduct experiments to study self-motion perception, visual perception and human computer interaction in these virtual worlds. In particular, working with a senior graduate student or postdoctoral fellow, the successful applicant would model 3D environments, render them in a virtual reality or other digital media display, develop/implement interaction methods to control and interact with the simulation, and/or develop and run experimental scenarios to investigate these issues with human participants.

Duties and responsibilities:

Depending on skills and preparation the student would be responsible for:

  • Literature reviews and research

  • Design of virtual environments

  • Computer programming

  • Testing

  • Recruiting participants

  • Conducting user studies

  • Modeling and Data analysis

  • Preparation of reports, graphics and presentations

Requirements for technical skills:

Good programming skills, previous work with computer graphics or virtual reality would be helpful, as would basic mechanical skills. Students with background in Psychology and interest in Experimental Psychology are also welcome to apply. Artistic background or skill would be an asset but is not required.

Requirements for interpersonal skills: Students should be self-directed and work well in a team environment.

Degree, courses and discipline prerequisites: Digital Media, Electrical Engineering, Computer Engineering, Computer Science, Psychology, Vision Science


Green method for precipitation of heavy metals in municipal wastewater sludge

Position type: NSERC USRA

Department: Civil Engineering

Professor: Satinder Brar

Number of positions available: 2

Contact: satinder.brar@lassonde.yorku.ca

Summary of project: 

In recent time, concerns have been raised about the contamination of the environment with heavy metals. Municipal waste water originates from both industrial and domestic sources. Municipal waste water poses a significant threat to the aquatic environment due to the presence of toxic metals like copper (Cu), lead (Pb), nickel (Ni), zinc (Zn) and mercury (Hg) etc. These metals can cause phytotoxicity and bioaccumulation which potentially pose major environmental and health issues. Canada dumps approximately 3.9% of untreated waste water into rivers and oceans in 2015 (https://www.cbc.ca). Most of the metal removal processes, such as coagulation, advanaced chemical reactions, operated at acidic pH that cause corrosion of digesters and pipes could become a significant limiting factor (Kurniawan et al., 2006). Thus, there is a need to develop an environmentally friendly process over conventional methods which shows high metal binding capacity, selectivity, rapidity, recovery of metals in concentrated form and no generation of toxic wastes. Mammalian alkaline phosphatases and enzyme from calf intestinal mucosa is one of the most active members of alkaline phosphatase which can be effectively adopted for the precipitation of heavy metals in its crude form. The novelty of the study is built on the hypothesis that enzyme inhibitory effect will act as positive modulator/regulator to precipitate heavy metal and easy removal from municipal wastewater. The specific objectives of the project are:

  • Production of glycosyl hydrolases using selected fungal strain on lignocellulosics biomass.

  • Estimation of enzyme activities of glycosyl hydrolases will be carried out.

  • Optimization of effective heavy metal ions precipitation via crude enzyme extracts using readymade heavy metal solution with response surface methodology (RSM).

  • Estimation of heavy metals present in collected municipal wastewater.

  • Treatment of municipal wastewater with crude enzyme extracts and to optimize parameters to enhance heavy metals recovery/precipitation. Tangible outcomes: This study is expected to make substantial headway in developing a novel process/technology and improving the removal of heavy metals from municipal effluent. The utilization of residual waste for the production of glycosyl hydrolases will make the process cost effective and develop a robust and futuristic technology.

The following are the anticipated results/innovations:

  • Reduction in overall solid waste: As residual biomass waste will be utilized for glycosyl hydrolases production, this will be helpful in overall reduction of solid waste.

  • Environmental friendly: This process will be environmentally friendly because of no generation of acidic or basic wastewater at the end of the process. This process will be developed at neutral pH or near to neutral pH.

  • Cost reduction: Utilization of easily available residual waste, instead of readymade ingredients for enzyme production will lead to a reduction in production cost of glycosyl hydrolases and this will further reduce the municipal wastewater treatment cost.

  • Non-corrosive: Municipal wastewater treatment with fungal glycosyl hydrolases which are stable and efficient to work at neutral pH, diminish the corrosion problem of pipes and digesters.

Duties and responsibilities:

  1. Wastewater sampling and analysis;

  2. Fermentation to produce specific enzymes;

  3. Mixing wastewater with the enzyme cocktail for precipitation;

  4. Analysis of metals and optimizaton of the overall process;

  5. Interpretation of results through statistical analyses;

  6. Report writing and initiate a research publication;

  7. Presentation of results at suitable platform: workshop or conference.

Requirements for technical skills: Basics in environmental engineering; applied chemistry. Knowledge of statistical tools for effective interpretation of results as assets.

Requirements for interpersonal skills: Team work and effective communication.

Degree, courses and discipline prerequisites: Civil and environmental engineering.


Hydraulic Modelling & Hydro-climate Hazards

Position type: LURA

Department: Civil Engineering

Professor: Shooka Karimpour

Number of positions available: 1

Contact: shooka.karimpour@lassonde.yorku.ca

Summary of project: 

From the dangers of flooding to harvesting tidal energy potential, the sustainable management of water resources presents unique opportunities and challenges to engineers. With urban development mostly along the floodplains and shorelines, and shifting weather patterns due to climate change, we are very susceptible to the rising risks of hydrological hazards. Hydrodynamic modelling provides sets of tools to study the nature of complex free surface flows, which will help us develop resilient infrastructure in the face of such hazards. Through development and application of 1D and 2D hydrodynamic finite volume models, along with data mining, this research project aims to shed light on the influence of extreme hydro-climate events on some of key flow features and evolution.

Duties and responsibilities: Literature review – Data collection and analysis – Coding – Participating meetings with PI

Requirements for technical skills: Coding experience (e.g., Fortran, Matlab, Python); Fluid Mechanics and Open Channel Hydraulics background

Requirements for interpersonal skills: Strong work ethic; Ability to work in a team; Ability to conduct literature search; Effective written skills

Degree, courses and discipline prerequisites: Third year students and higher in Civil and Mechanical Engineering


DEVELOPING A NEW CLASS OF SUSTAINABLE CONCRETE STRUCTURES

Position type: LURA

Department: Civil Engineering

Professor: Liam Butler

Number of positions available: 1

Contact: liam.butler@lassonde.yorku.ca

Summary of project: 

Concrete is the most widely used building material in the world. It supports the durable functioning of our built environment (e.g. bridges, tunnels, buildings, roadways and foundations). Typically composed of aggregate (stone/gravel), sand, water and cement, high-quality concrete relies on steady sources of these non-renewable resources. However, new alternatives to natural aggregates and ordinary cement such as recycled concrete aggregates (RCAs) and silica fume, respectively, are becoming more widely available. Producing concrete incorporating supplementary cementitious materials and locally-sourced RCAs can significantly reduce the amount of embodied CO2 associated with Portland cement production; alleviate the burden placed on non-renewable aggregate resources; increase the service life and capacity of landfill sites; and reduce the CO2 emissions and traffic congestion associated with the transport of natural aggregates from remote sites. This project is focused on developing alternate classes of concretes which replace natural aggregate and ordinary cements with recycled or alternate source materials. Although numerous past experimental studies have confirmed the suitability of these materials for structural applications, very limited data has been recorded on their in-situ and long-term durability performance. This project will focus on developing suitable methods for characterizing variability and classifying recycled materials (and the resulting concrete) for specific applications.

Duties and responsibilities:

  • Performing laboratory work in the High Bay Structures Laboratory independently and under the supervision of graduate students and technicians.

  • Carrying out classification and mechanical properties testing of various concrete materials and developing new and optimized classes of sustainable concrete.

  • Undertaking a review of current research literature pertaining to sustainable concrete materials.

  • Analyzing and interpreting testing data using statistical and other analytical approaches.

  • Reporting on experimental findings through report and/or technical article writing.

  • End of term presentation of research project and findings.

Requirements for technical skills:

Basic knowledge of concrete materials and properties; Basic statistical and data analysis skills; Working knowledge of MS Excel; Knowledge and/or previous experience of working with concrete materials would be considered an asset; Excellent written and verbal communication skills.

Requirements for interpersonal skills: Highly-motivated self-starter, organized and punctual.

Degree, courses and discipline prerequisites: Civil engineering student who has successfully completed CIVL 2120 (Civil Engineering Materials).


DETECTION OF LOW ALTITUDE CLOUDS IN MARS POLAR REGIONS

Position type: LURA

Department: Earth and Space Science and Engineering

Professor: Isaac Smith

Number of positions available: 1

Contact: ibsmith@yorku.ca

Summary of project: 

Previous studies have found that low altitude clouds in the polar regions of Mars interact with the surface. They are caused by adiabatic expansion of fast moving air as it travels over a topographic change in slope. This converts water vapor to solid in the form of snow, which in turn reaches the surface - enhancing the topographic feature. The previous detections were up through 2013, and many more images have been collected since then. This project will update the search for low altitude polar clouds and help determine their significance and the magnitude of their effects on the surface.

Duties and responsibilities:

Student will work closely with the professor to learn what to look for and then examine thousands of Mars images in search of clouds. Student will keep a log of positive and negative detections for statistical analysis.

Requirements for technical skills: Basic computer knowledge. Basic Unix skills as an asset.

Requirements for interpersonal skills: Work with up to 2 others

Degree, courses and discipline prerequisites: Physics, Astronomy, Earth and Space Science


Web Application Development for Simulation of Electric and Hydrogen Transit Bus Systems

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Hany Farang

Number of positions available: 2

Contact: hefarag@yorku.ca

Summary of project: 

This project aims to propose an interactive web-based toolbox for battery and hydrogen electric bus transit systems. The developed toolbox facilitates conducting electrification studies of transit buses through a user-friendly interface. The toolbox comprises two main modules: the first module aims at evaluating the energy consumption performance of the electrified buses (e-Bus); the second module allows to benchmark the performance and feasibility of the e-Bus to electrify a transit network based on the daily operational constraints and scheduling identified by the transit network operator. The toolbox generates detailed reports of the e-Buses charging/fueling profile and the state of charge of the bus battery/tank after each trip.

Duties and responsibilities:

Work with senior researchers on converting ideas to successful inventions by developing, designing, and building front- and back-end applications. Assist with the design of user interface and experience, documentation, business analysis and research. Other duties as assigned.

Requirements for technical skills:

  • Strong skills in HTML5, CSS3, Responsive Design, Node.js, Angular, jQuery, PHP, MySQL, and WordPress.

  • Strong in technical documentation and business/system analysis to support the design process.

  • Ability to develop effective workflow and procedures.

Requirements for interpersonal skills:

  • Works closely with project and team leaders in developing project plans.

  • Excellent time management skills and strong written and verbal communication skills.

  • Computer science, software engineering.

Degree, courses and discipline prerequisites: Computer science, software engineering


MultiObjective Resource Optimization for 5G-enabled Vehicular Networks

Position type: LURA

Department: Electrical Engineering and Computer Science

Professor: Hina Tabassum

Number of positions available: 1

Contact: hinat@yorku.ca

Summary of project: 

Fifth-generation (5G) wireless networks will serve as a key enabler for a variety of wireless network applications such as vehicular networks and Internet-of-Things (IoT) networks. 5G networks are anticipated to be enabled with the traditional sub-6 GHz radio frequencies as well as higher transmission frequencies (such as millimeter-waves and optical frequencies). While higher frequencies offer ample low-cost wireless spectrum, they are vulnerable to severe transmission blockages and penetration losses. Therefore, the higher frequency wireless transmissions are typically successful only for small distance ranges with directed antenna transmissions. Although, higher frequency spectrum is relatively less expensive (in some cases free of cost) compared to traditional radio frequencies, the coexistence of diverse set of frequencies will lead to disparate challenges such as traffic load imbalance among different frequency channels, newer interferences due to beamforming patterns/misalignments, and frequent handovers of users depending on their velocity. Subsequently, the collective impact of the aforementioned factors on the dynamics of the transmission signals and interferences, network traffic offloading and resource allocation mechanisms is largely unknown. In this context, this project will be conducted in two stages.

The first stage will focus on developing multi-objective optimization algorithms for coexisting mmWave and sub 6GHz networks to enhance the network resource efficiency (weighted function of spectral and energy efficiency) and deployment cost efficiency (weighted function of spectral efficiency and network deployment cost) with transmission delay and user fairness constraints. Optimal and near-optimal solutions will be investigated to understand the trade-off between resource consumption and network performance. Low complexity heuristic algorithms will also be designed. The traffic offloading, power, and spectrum allocation solutions will be derived using tools from optimization theory, dynamic programming, and/or game theory. The results will be generated through optimization functions in MATLAB. In the second stage, the developed algorithms will be extended for a vehicular network where the users are analogous to vehicles and follow a specific mobility pattern. The movement of vehicles will be modeled using spatiotemporal correlated mobility models and location of multiple vehicles will be modeled using stochastic processes. In this stage, our focus will be on minimizing the handover rate of vehicles with network rate constraints.

Duties and responsibilities:

The student will first conduct a survey of existing dynamic programming and optimization algorithms and develop an understanding of creating such algorithms. Then, the student will simulate a general purpose coexisting mmwave and sub-6GHz network model on MATLAB and develop an algorithm to optimize traffic load balancing, spectrum and power allocations in this networks. Finally, the developed algorithms will then be extended for vehicular networks taking into account mobility related parameters.

Requirements for technical skills: MATLAB, Algorithm design

Requirements for interpersonal skills: N/A

Degree, courses and discipline prerequisites: EECS 3213


Development of Clean Technologies for Renewable Resources and BioEnergy Recovery from Municipal Waste Streams

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Ahmed Eldyasti

Number of positions available: 2

Contact: ahmed.eldyasti@lassonde.yorku.ca

Summary of project: 

In Canada, the clean and renewable technology industry is currently valued at over $10 billion and is set to double over the next five years. Concurrently, an estimated $16 billion is spent annually to remediate hazardous waste and over $15 billion are spent annually for operating and maintaining of conventional waste treatment plants. This represents sizable development costs and therefore research into shifting these conventional clean and renewable technology into Water Resources Recovery Facilities of waste streams would not only help to reduce the total budget and O&M expenses but also generate profit and provide the required water quality level to maintain a clean and healthy environment for Canada. The research aims to develop commercially feasible engineering processes and cost-effective technologies that can maintain water quality and recover value-added products, which can be practical to integrate it into the existing conventional processes or the development of new WRRF plants.

Duties and responsibilities:

  1. Conduct experimental develop an economical, robust and efficient process to recover chemical resources in the form of methanol or other chemicals during the treatment of high strength organic municipal streams. These specific objectives for this research project will be undertaken by 1 Ph.D and 1 master students to optimize the laboratory-scale systems and evaluate the performance of this technology

  2. Analyze the designs, evaluate the performance

  3. Report to the supervisor

    Priority will be given to the students with an experimental background and hands on experience.

Requirements for technical skills:

  • Ability to prepare written materials

  • Ability to problem solve

  • Creativity and innovation

  • Goal orientation

  • Interpersonal skills

Requirements for interpersonal skills:

  • Positive attitude and behaviour

  • Sense of responsibility

  • Strong work ethic

  • Willingness to keep learning

  • Ability to manage and organize information

  • Effective oral and written communication skills

Degree, courses and discipline prerequisites: Civil engineering, Mechanical engineering, Chemistry, and Biology or equivalent.


DEVELOPMENT OF MACHINE LEARNING FOR HEART ARRHYTHMIAS CLASSIFICATION

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Peter Lian

Number of positions available: 3

Contact: peterlian@eecs.yorku.ca

Summary of project: 

This project aims to develop a machine learning algorithms to extract heart information from biosignals recorded by wireless wearable electrocardiogram (ECG) sensors. The biosignals recorded by a wearable biomedical sensor normally contain motion artefacts and other noises, which greatly reduce the diagnostic value of these recordings. Traditionally, the recorded biosignals are processed by digital signal processing algorithms to remove noises before extracting useful information. With the advancement of machine learning techniques, it is possible to extract useful information directly from noise corrupted biosignals. These algorithms are very useful in detecting heart condition from ECG signals. Knowing the heart condition will be a great help for patients with cardiovascular diseases, especially for heart failure (HF) patients. Heart failure is a growing epidemic in Canada. It is a significant health issue for hundreds of thousands of Canadians and their families, and its reach is expanding according the 2016 Report on the Health of Canadians from HEART & STROKE Foundation. 600,000 Canadians are living with HF. 50,000 Canadians are diagnosed each year with the HF. One in two Canadians has been touched by the HF. HF costs more than $2.8 billion per year. HF, in simple terms, arises due to damaged valves or heart muscles. HF normally leads to reduced pumping capacity of the heart (cardiac output) that can reduce exercise capacity and cause fatigue. HF can also result in an imbalance of blood pressure leading to fluid retention in the body, particularly congestion in the lungs, which can cause breathlessness. An acute episode of breathlessness typically sends the HF patient to the emergency department. The patient then spends on average five days in the hospital to stabilize his/her condition but remains susceptible to future decompensation. Prior to discharge, patient gets some time to learn a huge list of HF self-care instructions, which is usually overwhelming to the sick patient. This in turn leads to poor self-care at home and poor compliance to medication and diet, which are common causes for the patient’s HF rehospitalization. Thus, the rehospitalization rate is high, in the range of 14% to 24%, in Canada. With the machine learning based heart rate detection algorithm and wearable wireless sensors, it is possible to allow doctor to remotely access patient’s heart condition, which may provide just-in-time help for patient. It will also empower patient, their home-caregivers and practitioners to achieve better home care, and reduce rehosptialization rate.

Duties and responsibilities:

The successful candidate will be responsible for the development of machine learning algorithm, neural network training, and APP development.

Requirements for technical skills:

  1. Basic knowledge of digital signal processing.

  2. Good knowledge in programming and APP development.

  3. Knowledge in machine learning or AI is a plus.

  4. Passionate about programming.

Requirements for interpersonal skills: Team work

Degree, courses and discipline prerequisites: EECS3062 or EECS3451


DEVELOPMENT OF WEARABLE WIRELESS ELECTROCARDIOGRAM SENSOR

Position type: LURA, NSERC USRA

Department: Electrical Engineering and Computer Science

Professor: Peter Lian

Number of positions available: 3

Contact: peterlian@eecs.yorku.ca

Summary of project: 

This project aims to develop a wireless non-contactable electrocardiogram (ECG) sensor that is able to monitor changes in cardiac function of heart patients. Non-contactable ECG sensing means to measure ECG (or heart beats) without attaching multiple electrodes on the chest. Such sensors are more acceptable by patients, which may improve care compliance. It is also possible to provide real-time information remotely to doctors when the patient needs attention or help, especially for HF patient. Heart failure (HF) is a growing epidemic in Canada. It is a significant health issue for hundreds of thousands of Canadians and their families, and its reach is expanding according the 2016 Report on the Health of Canadians from HEART & STROKE Foundation. 600,000 Canadians are living with HF. 50,000 Canadians are diagnosed each year with the HF. One in two Canadians has been touched by the HF. HF costs more than $2.8 billion per year. Heart failure, in simple terms, arises due to damaged valves or heart muscles. HF normally leads to reduced pumping capacity of the heart that can reduce exercise capacity and cause fatigue. HF can also result in an imbalance of blood pressure leading to fluid retention in the body, particularly congestion in the lungs, which can cause breathlessness. An acute episode of breathlessness typically sends the HF patient to the emergency department. The patient then spends on average five days in the hospital to stabilize his/her condition but remains susceptible to future decompensation. Prior to discharge, patient gets some time to learn a huge list of HF self-care instructions, which is usually overwhelming to the sick patient. This in turn leads to poor self-care at home and poor compliance to medication and diet, which are common causes for the patient’s HF rehospitalization. Thus, the rehospitalization rate is high, in the range of 14% to 24%, in Canada. With the proposed wireless non-contactable ECG sensors, it is possible to monitor the heart condition of HF patients during daily activities, which may achieve better compliance to self-care instructions and reduce the HF rehospitalization.

Duties and responsibilities:

The successful candidate will be responsible for the design of PCB, building circuit board, and firmware development.

Requirements for technical skills:

  1. Basic knowledge of circuits and PCB design.

  2. Knowledge in microcontroller programming.

  3. Knowledge in Bluetooth is a plus.

  4. Passionate about biomedical circuits and systems.

Requirements for interpersonal skills: Team work

Degree, courses and discipline prerequisites: EECS2200, EECS2210 or equivalent Preferred: EECS3602, EECS3215


Fabrication and Testing of 3D Printed Carbon Fibre Composite Heat Exchangers

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Roger Kempers

Number of positions available: 1

Contact: kempers@yorku.ca

Summary of project: 

Initial research has resulted in the development of a novel 3D printing technique for high thermal conductivity continuous fiber polymer composites using pitch-based carbon fibres. The objective of this project will be to design, fabricate and experimentally characterize the thermal performance of a wide range of 3D printed carbon fiber composite heat exchangers for applications ranging including EV battery thermal management, electronics cooling and waste heat recovery. Students will modify and adapt existing 3D printing technology to fabricate and characterize 3D printed samples and heat exchangers. They will develop technical drawings, perform engineering design calculations and simulations, fabricate the components, and characterize and assess the performance of these components and printing technologies. They will communicate their findings orally during weekly meetings and will author a final paper which for submission to a conference or a journal at the end of their project.

Duties and responsibilities:

  • Hands-on experimental research and testing

  • 3D printing and processing of materials

  • CAD and simulations

  • Data collection and analysis

Requirements for technical skills: Good working knowledge of Mechanical Engineering and hands-on ability.

Requirements for interpersonal skills: Good verbal, written and presentation communication skills. Able to self-motivate and work well with limited direction.

Degree, courses and discipline prerequisites: N/A


Development of an Apparatus for the Thermal and Electrical Characterization of Thermal Interface Materials

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Roger Kempers

Number of positions available: 1

Contact: kempers@yorku.ca

Summary of project: 

The objective of this project is to re-design, develop and construct an extremely accurate apparatus used for the mechanical, thermal and electrical characterization of thermal interface materials and other conductive materials. This will involve the re-design and calibration of critical components, apparatus assembly and control, setup of data acquisition hardware, the development of a temperature-controlled water-cooling loop, and the development of IR thermal instrumentation. The work will culminate with the testing of a new kind of metal-based thermal interface material. Students will develop CAD models, perform engineering design calculations and simulations, fabricate and assemble hardware and instrumentation. They will communicate their findings orally during weekly meetings and will author a final paper which for submission to a conference or a journal at the end of their project.

Duties and responsibilities:

  • Hands-on experimental fabrication and testing

  • Data acquisition and instrumentation setup

  • CAD and simulations

  • Data collection and analysis

Requirements for technical skills: Good working knowledge of Mechanical Engineering and hands-on ability; MATLAB

Requirements for interpersonal skills: Good verbal, written and presentation communication skills. Able to self-motivate and work well with limited direction.

Degree, courses and discipline prerequisites: N/A


Design and Development of Portable Devices for Detection of Cannabis Consumption

Position type: LURA, NSERC USRA

Department: Mechanical Engineering

Professor: Nima Tabatabaei

Number of positions available: 2

Contact: nimatab@yorku.ca

Summary of project: 

The project involves design and manufacturing of portable thermo-photonic devices for roadside detection of cannabis consumption. Student(s) will be working with graduate students and post doctoral fellows at the Hybrid Biomedical Optics Lab and will gain experience in instrumentation, optics and infrared imaging. For more information contact professor Tabatabaei.

Duties and responsibilities:

  • Mechanical design

  • Manufacturing of prototypes

  • Performing validation experiments and data processing

Requirements for technical skills: Skill in SolidWorks design as well as basics of instrumentation

Requirements for interpersonal skills: Teamwork

Degree, courses and discipline prerequisites: Preferably have taken MECH 2502


Laboratory Investigations of the Optical Properties of CO2 ice

Position type: LURA, NSERC USRA

Department: Earth and Space Science and Engineering

Professor: Isaac B. Smith

Number of positions available: 1

Contact: ibsmith@yorku.ca

Summary of project: 

We are developing the equipment and techniques to measure the optical properties of exotic ices in the solar system (carbon dioxide, carbon monoxide, nitrogen, methane, anything except H2O). This project involves working with CO2 ice in particular. We will build and modify chambers capable of attaining the same temperatures and pressures found at the polar ice caps of Mars in order to generate CO2 ice from the chamber atmosphere. The final part is to observe changes in the crystalline structure of the ice when interacting with incident illumination.

Duties and responsibilities:

This project would entail laboratory setup, data collection, and data analysis while working with a graduate student who's research topic is the same project.

Requirements for technical skills: Mechanical skills to work with tools and equipment

Requirements for interpersonal skills: Work under the guidance of a graduate student

Degree, courses and discipline prerequisites: First year physics