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Faculty of Engineering and Applied Science Project Summaries

Supervisors

Supervisor name: Aaron Yurkewich

Project title: Hand Exoskeleton Design and Intelligent Control

Summary of research project: The long-term objective of this research is to develop functional clothing that is widely accessible and enables humans to reach new levels of performance, accuracy, endurance and strength in manufacturing and rehabilitation applications. The objectives for this research project are to:

1) Enhance the HERO Glove hand exoskeleton's grip force assistance capabilities through the design and creation of continuum linkages and smart material actuators.

2) Enhance the HERO Glove hand exoskeleton's knowledge of its environment through the creation of a machine learning and vision-based control system that determines the optimal grasp posture and grip force.

Student responsibilities/tasks:

The ideal student will have a strong interest in designing robots and control systems and deploying these systems into real-world applications.
The student will utilize their knowledge of NX software, kinematics models, control systems and programming to design optimal linkage structures, build their new exoskeleton robot design, and develop a vision system that enhances the exoskeleton’s intelligence and usability.

Student qualifications required:

B average
Completion of CAD and Control Systems courses (MECE 3030, MECE 3350)
Participation in an engineering club (e.g. robotics, auto) is a plus!

Expected training/skills to be received by the Student:

Robot Design.
Advanced Control Systems.
Machine Learning.
Biomedical Engineering.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Aaron Yurkewich

Project title: Powered Pants: Designing Lower-Limb Exoskeletons for People with Neurological and Musculoskeletal Injuries

Summary of research project: The long-term objective of this research is to develop functional clothing that is widely accessible and enables humans to reach new levels of performance, endurance, recovery and independence after neurological and musculoskeletal injuries. The objectives for this research project are to:

1) Develop powered pants that help users to stand up, walk and run with less joint loading and muscular requirements

2) Develop engaging exercise environments for a virtual reality robotic treadmill training system to enable human participant experiments and tele-rehabilitation opportunities.

Student responsibilities/tasks:

The student will utilize their knowledge of NX software, kinematics models, control systems and programming to design high-performance and ergonomic cable-driven actuation systems and exercise environments for evaluating the performance of the exoskeleton system and the human.

Student qualifications required:

B average or above.
MECE 3030 (CAD).
MECE 3350 (Control Systems).
Proficient in creating robotic systems.

Expected training/skills to be received by the Student:

Research and technical training and mentorship from Supervisor (Aaron) and Graduate student (Daimen).
Technical training in biomedical engineering aspects such as biosignal analysis, motion analysis and myoelectronics.
Hands-on training in building and evaluating wearable robots.
Communication skills through report writing and laboratory presentations.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Akramul Azim

Project title: ML-Based Test Case Prioritization in Continuous Integration Environments

Summary of research project: Test case prioritization is of great importance in test process optimization to make efficient use of testing resources, especially when it comes to regression testing for different code submissions in continuous integration environments. Appropriate knowledge processing and learning techniques to deal with numerous and versatile sources of information can be used to address efficiently the peculiarities of each code submission and evaluate their quality characteristics. In this research, we aim to develop a machine learning based strategy that can automatically select the test suites that could be impacted by a change and identify the most likely ones to fail based on a given change.

Student responsibilities/tasks:

Research and development.

Student qualifications required:

Programming skills.

Expected training/skills to be received by the Student:

Research and development.
Programming skills.
Presentation and Communication.
Writing.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Atef Mohany

Project title: Active vibration control with application to a robotic manipulator

Summary of research project: Active vibration control is a technique that is used in a variety of applications to mitigate undesired vibrations. In robotic manipulator, which consists of multiple interconnected joints and links, vibrations can adversely affect precision, accuracy, and overall performance. Active vibration control plays a crucial role in enhancing the operational efficiency of robotic manipulators by minimizing oscillations induced during movements. These oscillations can be further amplified if the robotic manipulator is subjected to wind. Therefore, the main objective of this project is to develop an active vibration control technique and apply it on a robotic manipulator subjected to external flow.

Student responsibilities/tasks:

The successful candidate will be working in a team to help with the following:

Design and manufacture the experimental test section required for this work.
Perform experimental measurements.
Analyze the results and present them.
Assist with any other tasks as needed.

Student qualifications required:

The successful candidate should have:

A minimum GPA of 3.7.
Good background in mechanical vibrations, control, and fluid mechanics.
Good hands-on experience.
Good communication skills.
Ability to function well in a team.

Expected training/skills to be received by the Student:

The successful candidate will gain valuable knowledge solving real-life engineering problems.
Training on measurements and data acquisition.
Training on communication skills through the presentation of results.
Training on different aspects of flow-induced vibration and control.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Brendan MacDonald

Project title: Development and testing of Stirling engines for sustainable energy

Summary of research project: Stirling engines are capable of providing power from a wide range of heat sources since the heat is external to the piston cylinders. This can include sustainable sources such as wood, waste, solar, etc., which means these engines have a high potential to provide sustainable power. The Stirling engine is an external heat engine with high promise, and we are developing prototype engines with some new technological advantages to produce competitive and commercially viable engines. The prototyping includes design work, analysis, and experimental testing.

Student responsibilities/tasks:

There are many tasks required for our current Stirling engine prototyping, mainly related to examining specific aspects of the engine design and improving the design. This can include things like numerical modelling, building experimental test rigs to analyze design changes, developing generators for electrical output, or testing with our current prototypes.
Specific tasks will be determined with the student to ensure interest and compatibility.

Student qualifications required:

Most importantly students should be curious, have a passion for discovery, and be honest.
It is beneficial for students to have thermodynamics, fluid mechanics, and/or heat transfer knowledge.
Hands-on experience is also beneficial for the engine building and testing aspects.

Expected training/skills to be received by the Student:

Students will be trained in solving engineering problems, and most importantly diagnosing the causes of problems.
Students will be trained in engine cycles, and the thermodynamics of engine cycles, and how the theory can be applied to improve actual physical engines.
Students will be trained in critical analysis of engineering designs, through brainstorming sessions and experimentation.
Students will be trained in sustainability and the different ways technology can improve our sustainability.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Daniel Hoornweg

Project title: A Sustainability Assessment of the Taylor Swift Eras Tour - NSERC

Summary of research project: With 151 concerts over 5 continents, the Taylor Swift Eras tour will be the highest-grossing tour ever. This research will provide a comprehensive assessment of the tour’s overall sustainability. In each city, the tour’s economic contribution will be weighed against 14 sustainability sectors. The research objective is to be able to credibly answer the question of “how sustainable is the Eras tour?” The methodology to assess sustainability uses 24 bio-physical indicators (e.g., climate change, biodiversity, freshwater use, pollution) and 40 socio-economic indicators (e.g., youth opportunity, economy, energy access and intensity, basic services, public safety).Sustainability, by definition, encompasses bio-physical (typically NSERC research areas) and socio-economic components (typically SSHRC research areas). This NSERC-supported student is expected to focus on the bio-physical aspects of sustainability such as climate change (mitigation and adaptation), water and wastewater, and overall energy systems.As a result, this project will advance our NSE knowledge of sustainability.

Student responsibilities/tasks:

The student will provide research on key aspects of the overall Taylor Swift Eras tour and conditions unique to each of the 40 venue cities.
Information will include energy used, emissions generated (GHG, solid waste, wastewater), primary and secondary economic impacts, attendance, etc.
This is part of an international research group addressing the research question.

Student qualifications required:

The student should be comfortable searching multiple sources for key information, sufficiently numerate (e.g., understanding of statistics), and able to work on their own.
Excellent data management skills are very helpful.
Ideally third year and above.
An interest in sustainability and Taylor Swift a plus.

Expected training/skills to be received by the Student:

Using at least 40 cities across 5 continents, how does sustainability vary by community.
Appreciation for detailed breakdown of what determines overall sustainability at the urban level.
Energy demands for key economic activities, and associated greenhouse gas emissions.
Data management and Excel skills (with Word).
Defining and appreciating the various quality measures of broad data sets.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Daniel Hoornweg

Project title: A Sustainability Assessment of the Taylor Swift Eras Tour - SSHRC

Student responsibilities/tasks:

The student will provide research on key aspects of the overall Taylor Swift Eras tour and conditions unique to each of the 40 venue cities.
Information will include primary and secondary economic impacts, security and safety, equity, and fan attendance (ticket allocation).
This is part of an international research group addressing the overall research question.

Student qualifications required:

The student should be comfortable searching multiple sources for key information, sufficiently numerate (e.g., understanding of statistics), and able to work on their own.
Excellent data management skills are very helpful.
Ideally third year and above.
An interest in sustainability and Taylor Swift a plus.

Expected training/skills to be received by the Student:

Using at least 40 cities across 5 continents, how does sustainability vary by community. Key focus on Toronto and Vancouver.
Appreciation for detailed breakdown of what determines overall sustainability at the urban level.
Data management and Excel skills (with Word).
Defining and appreciating the various quality measures of broad data sets.
Local government and revenue sharing across various government levels.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: SSHRC USRA (exclusively for Black students) or Ontario Tech STAR Award

Supervisor name: Ghaus Rizvi

Project title: Design and Development of a Volumetric Additive Manufacturing System

Summary of research project: The VAM method is a revolutionary additive manufacturing process that reduces the product built-time by orders of magnitude - from hours to minutes. VAM uses principles similar to Computed Tomography, where X-ray images projected at different angles are recorded as Radon Transforms (RT) of the sliced images. The RT represents the cumulative intensity attenuation as the light pass through the object at each angle. The original image is reconstructed by using inverse RT and image processing techniques. With help of a digital light processing DLP projector this image is used to build a physical object in a photo-curable resin using a process somewhat similar to stereo-lithography method.

Student responsibilities/tasks:

Improve the design of the VAM setup.
Prepare CAD images and convert them into RTs.
Prepare resin formulations and use them for producing parts by projecting the RTs with a DLP onto a rotating vial filled with resin.
A number of parameters that affect the image formation will be studied using the design of experiments methodology and statistical software will used to analyze the results obtained.

Student qualifications required:

The student should have completed two years of engineering education with good grades.

Expected training/skills to be received by the Student:

Image processing techniques.
Mechanism design capability
Design of experiment methodology
CAD software usage
Hands on experience with a number of lab equipment

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Glenn Harvel

Project title: Development of Mobile Platform for the Capture of Radioactive Liquids

Summary of research project: Currently, our research group is studying new methods for the capture of radioactive spills. We are developing several methods that can be applied for different types of spills. We need to develop a mobile platform that will support the delivery and capture mechanisms and that will be able to travel over various differences. For this project, we are specifically examining smooth surfaces. The mobile system will require working with graduate students to ensure their mechanisms can be supported. The mobile system also needs to consider different load categories and personnel protection. The work will also need to consider radiation concerns.

Student responsibilities/tasks:

Follow all lab safety protocols
Work with others as members of a team
Prepare all drawings in advance of construction
Recommend items for procurement
Assist in construction and testing of mobile platform

Student qualifications required:

Required: Minimum 2nd year nuclear engineering or radiation science (for shielding work)
Preferred: practical experience in a lab/shop setting

Expected training/skills to be received by the Student:

Safety related training: The student will obtain knowledge and experience for working in a safe environment where the following hazards are likely to be present: radiation, electrical shock, mechanical pinch, falls and slips.
Instrumentation and Control training: The design being produced will need to monitor the status of the system and the control of the system. This will involve development of instrumentation and controls, possibly arduino systems.
Radiation Shielding training: The intent is for the design to be used in radiation environments. The student will learn the ability to calculate radiation fields and radiation shielding to support the design.
Robotics training: The base platform will provide the opportunity to learn about loads, motors, structural support, and other elements necessary for the platform to work.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Glenn Harvel

Project title: Development of a Simulation Tool for Nuclear Data Analysis

Summary of research project: Our group is exploring the application of data analysis in nuclear facilities. To assist in the testing of various processes, we are developing a nuclear simulation platform. The work will require primarily a software development or coding of a simple system for use in testing. The work may eventually lead to a hardware interface. Software development may be in simulink, python, or other similar codes. Basic research into software technologies is expected. The successful candidate will work with graduate students in the development of the system. A theory manual and user manual will also be created. The software is required to work dynamically.

Student responsibilities/tasks:

Comply with all laboratory safety protocols.
Work with graduate students as members of a team.
Prepare a theory manual and a user manual of the system under guidance from the graduate student.
Develop elements of code that can be included in the system.
Prepare a final report.

Student qualifications required:

Nuclear Engineering, Gaming, or Computer Science/Engineering Student that has completed 2nd year.
Ability to code in a language.
Good writing and communication skills.

Expected training/skills to be received by the Student:

Safety Training: The student will be trained on working in a safe environment where the following hazards may occur: radiation, electrical shock, mechanical pinch, slips and falls.
System Training: The student will be trained on system design, system development, and interfaces.
Coding Training: The student will be trained related to coding, specifically dynamic coding, and interfacing with other coding systems.
Instrumentation Training: The student will be trained on typical instruments that may be used in the simulation.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Haoxiang Lang

Project title: Interactive General AI in Robotics

Summary of research project: The project aims to design and develop an AI platform that can be used by robotic applications. The project will explore the current techniques of understanding language, music, and arts using Machine Learning and seek ways of interaction between human and robots.

Student responsibilities/tasks:

Set up and test the current AI framework.
Run test scenarios.
Write a technical report of the findings.

Student qualifications required:

Students from Mechatronics, or Computer Science or Computer Engineering with Python and Ubuntu experience.
Music or Arts background will be needed.

Expected training/skills to be received by the Student:

Experience cutting edge Machine Learning platforms and applications.
Programming skills.
Robotic applications.
Writing skills.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Hossam Gaber

Project title: Nuclear Waste Management and Characterization

Summary of research project: This project aims to design waste management process for SMR nuclear wastes. The project will engage students to analyze SMR waste streams throughout their operation lifecycle, it will assess the related waste properties and characteristics (radioactivity source terms and intensity), and develop best practices for the treatment and management. Students will design radioactivity models for the waste management process. Students will characterize different relevant surrogate waste materials from different stream using TGA/FTIR/GCMS systems in the lab. Students will use simulation code to evaluate possible properties and treatment scenarios and evaluate performance measures.

Student responsibilities/tasks:

Activity models for SMR waste management processes
SMR waste analysis and characterization for lifecycle of SMR
Investigate waste due to reactor plant operation activities (characterize all intermediate waste forms (i.e., solid/liquid)
Estimate wastes resulting from decommissioning (spent fuel and activated component).
Assessment of waste inventory & radiological characteristics for all structures based on SMRs conceptual study.

Student qualifications required:

Modeling and simulation.
Knowledge of nuclear waste.
Process modeling.

Expected training/skills to be received by the Student:

Process modeling.
Modeling and simulation of nuclear waste treatment with COMSOL.
COMSOL Multiphysics simulation.
Nuclear waste characterization.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Hossam Gaber

Project title: Design of Digital Control Room for SMR Deployments - Group (B): Co-Simulation of SMR with Real Time Operation Verification

Summary of research project: The planned deployment of SMRs require design of new digital control rooms that will have advanced monitoring technologies for remote operations. There are key challenges to design practical digital control rooms in view of design and operation uncertainties and human factors. The project aims to study the design of a digital control room with multidimensional views and human considerations to support the safe deployments of SMRs.

Student responsibilities/tasks:

Study human factors related to control room design.
Conduct a thorough analysis of the operational requirements, safety regulations, and industry standards for SMRs.
Identify the key parameters, control variables, and data interfaces required for real-time operation verification and co-simulation integration.

Student qualifications required:

Matlab.
Human factor and human performance knowledge.
Human health monitoring technologies.
Data analysis.
Python.

Expected training/skills to be received by the Student:

Human health analysis and monitoring.
Study human factor and reliability and error.
Python and data analytics.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Jennifer McKellar

Project title: SMR Supply Chain Sustainability

Summary of research project: The development of a small modular reactor (SMR) sector in Canada will require the development of a supporting supply chain. At this early stage, there is an opportunity to design that supply chain to achieve net-positive sustainability. This project explores potential opportunities to develop a more sustainable SMR supply chain, through a combination of economic, environmental and social analyses.

Student responsibilities/tasks:

The student will examine the results of existing analyses to identify opportunities for sustainability improvements.
They will then conduct their own analyses of those improvements to verify net gains.
The analytical techniques may include life cycle assessment, and life cycle costing, for example.
The work will be computer-based and will require searching for information and data online and in the literature, basic calculations and analysis.

Student qualifications required:

Completion of second year in an engineering or science program preferred, but not required.
Knowledge of nuclear energy and/or industrial activities would be an asset.
Required: Familiarity with Microsoft Excel and comfort with spreadsheet operations; strong independent work and communication skills; general knowledge of energy and enviro. issues.

Expected training/skills to be received by the Student:

Familiarity with sustainability concepts.
Familiarity with the broader nuclear sector.
General research skills e.g., literature searches.
Familiarity with analytical techniques such as life cycle assessment.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Martin Agelin-Chaab

Project title: Multiphase flow processes in adverse weather

Summary of research project: Emerging vehicles, such as self-driving vehicles, entirely depend on a network of sophisticated sensors to provide environmental data for navigation. However, adverse weather, such as rain and snow, can contaminate the external surfaces of these sensors, which can impair their performance, leading to accidents. The proposed research will focus on developing rigorous techniques for characterizing and providing physical insight into these complex processes of surface contamination of optical sensors. This will lay the groundwork for developing fundamental concepts and novel mitigation strategies and devices.

Student responsibilities/tasks:

Perform experiments with simulated rain on model vehicles and optical sensors.
Develop concepts of passive aerodynamic devices and strategies to minimize surface contamination of the sensors.
Use CFD to evaluate the effectiveness of all concepts and strategies.
Conduct 3D printing of the most effective concepts for future wind tunnel testing and validation.

Student qualifications required:

Students must finish 2nd year with a GPA of 3.5 or better.

Expected training/skills to be received by the Student:

The applicant will work closely with a Ph.D. student who is working on this project, as well as students in the researcher's team. So the student will learn teamwork and technical communication skills.
The methods to be employed for the proposed research are wind tunnel testing and computational fluid dynamics (CFD). Therefore the student will develop skills in wind tunnel testing and CFD.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Masoud Makrehchi

Project title: AI-Powered Personalized Assessment for Active Learning

Summary of research project: This research proposal aims to integrate generative AI and large language models to develop personalized assessment tools for students engaged in active learning. Leveraging technologies like GPT-3.5, the study will create adaptable assessment approaches tailored to diverse active learning strategies. The research involves a comprehensive literature review, followed by the development and testing of prototype tools, with the goal of revolutionizing assessment methods to capture the nuanced skills and competencies fostered through active learning experiences. The outcomes are expected to contribute to the intersection of AI and education, enhancing student-centered learning approaches.

Student responsibilities/tasks:

Conduct an in-depth review of existing literature.
Contribute to the development of the research design.
Participate in the design and development of prototype assessment tools using generative AI algorithms.
Collaborate with the research team.
Take responsibility for documenting the development process and publication.
Participate in the analysis and interpretation of research findings.
Contribute to the preparation of reports and presentations.

Student qualifications required:

Programming Proficiency: Strong proficiency in coding, particularly using Python
Generative AI and Language Models: Good familiarity with Generative AI techniques and Large Language Models, with the ability to apply these technologies to the research objectives.
Academic Performance: A GPA greater than 3.5

Expected training/skills to be received by the Student:

Python Programming for AI: Training in Python programming with a focus on AI application, covering relevant libraries and frameworks used in the development of AI-powered tools.
Generative AI Techniques: In-depth training on generative AI techniques, exploring algorithms, models, and methodologies applicable to the creation of personalized assessment tools.
Large Language Models (LLMs): Specialized training in understanding and working with Large Language Models, such as GPT-3.5, to leverage natural language processing capabilities for assessment tool development.
Ethics in AI and Education: Training on ethical considerations related to AI in education, emphasizing responsible AI usage, privacy concerns, and fairness in algorithmic decision-making.
Research Methodology and Data Analysis: Comprehensive training in research methodologies, including data collection, analysis, and interpretation, to equip the student with the necessary skills for robust empirical research in the field of AI in education.

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Meaghan Charest-Finn

Project title: Design and Development of a pilot manufacturing line

Summary of research project: Automated Intelligent Inspection of manufactured parts has become commonplace in modern manufacturing lines. To achieve accurate inspection quality, it is essential to consider multiple mechatronics systems and their interactions. These mechatronics systems comprise of sensors, actuators, control systems and intelligent software. The research project involves the design and construction of an inspection cell to simulate a real-world production environment. The objectives of the research project are to 1) Review state-of-the-art automated inspection cells, 3) Design an inspection cell that can be used to test systems being developed by graduate students 3) Build the inspection cell.

Student responsibilities/tasks:

Connecting with graduate students in the lab to identify user requirements and engineering specifications for the inspection cell.
Reviewing state-of-the-art inspection cells available in industry.
Designing and sourcing components required to build the inspection cell.
Building and Testing the inspection cell with other students' projects.
Producing a user manual for the inspection cell.

Student qualifications required:

Students who can display practical skills through a history of completed projects will be considered strong candidates.
The completion of actuators and power electronics as well as control systems is considered an asset.
This project will require strong communication skills and an entrepreneurial spirit.
Some basic coding skills are necessary.

Expected training/skills to be received by the Student:

The student will be trained in engineering design.
The student will be trained in instrumentation and control.
The student will receive training in programming with MATLAB and Python.
The student will receive preliminary training in Data Science and Machine Learning in the context of Industry 4.0, and intelligent inspections.
The student will receive training in knowledge transfer and technical communication.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Mennatullah Siam

Project title: Towards a Comprehensive Endoscopy Video Segmentation Tool

Summary of research project: AI-enabled technology in diagnostic and therapeutic endoscopy is widely used, but usually studied separately without having a holistic view. Tasks in endoscopy include detection of pathological findings, anatomical landmarks and instruments. The goal from these AI-assisted systems is to aid physicians and reduce miss rates for lesions or polyps. We propose to extend the computer vision foundation model, Segment Anything (SAM), towards segmenting endoscopy videos. We will rely on publicly available datasets. Our research objectives include: (i) extending SAM for video segmentation, (ii) benchmarking state-of-the-art video segmentation methods on publicly available endoscopy datasets.

Student responsibilities/tasks:

Gathering list of endoscopy video datasets available with annotation types.
Parsing publicly available endoscopy datasets with their corresponding annotations.
Collaborating with MSc/PhD interns on benchmarking state-of-the-art video segmentation methods on the available datasets.

Student qualifications required:

MATH 1850U - Linear Algebra: Min grade A
STAT 2800U - Statistics and Probability: Min grade A
SOFE 2710U - Object Oriented Programming and Design: Min grade B+
SOFE 3770U - Design and Analysis of Algorithms: Min grade B+

Expected training/skills to be received by the Student:

Working with large-scale datasets and parsing the corresponding annotations.
Training and benchmarking existing state-of-the-art deep learning models.
Collaborating with other graduate students in my IVU lab.
Improve python programming in real-world machine learning applications.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Mitchell Rushton

Project title: Development and Testing of a Cable-Driven Parallel Robot Experimental Testbed

Summary of research project: Cable-driven parallel robots (CDPR) are a unique class of robotic manipulators made up of a rigid end effector suspended by multiple winch-driven cables.

What makes CDPRs attractive are the many advantages of using cables. Cables are extremely lightweight, allowing CDPRs to produce high accelerations and span distances that would otherwise be impossible using rigid structures. They are also very low-cost and easy to reconfigure. To develop and validate novel CDPR control algorithms and investigate the potential of novel CDPR forms, this project focuses on developing and testing a versatile experimental testbed specifically designed to study CDPRs.

Student responsibilities/tasks:

Take part in the development and testing of a cutting-edge robotic system
Develop control software in Matlab and Python
Design, assemble, and integrate mechanical and electrical components

Student qualifications required:

Essential:

Matlab and/or Python experience
Basic knowledge of Kinematics and Dynamics
Confident working hands-on with electrical and mechanical systems

Non-Essential (but nice to have):

Experience with embedded systems
CAN Bus experience
CAD experience
Soldering skills
Machining skills
Controls knowledge

Expected training/skills to be received by the Student:

Gain hands-on experience working with all aspects of a complex robotic system.
Gain practical skills essential for prototyping mechatronic systems.
Improve software skills, such as programming and CAD modelling.
Advance personal knowledge of robot kinematics, control systems, and mechatronics design.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Mohamed Youssef

Project title: Oil/Gas Plant Backbone Power Supply

Summary of research project: This Project is to design, model, simulate, and build a hardware prototype for the oil/gas power plant. This design requires mandatory harsh weather compliance.

Student responsibilities/tasks:

The students will be required to understand the industry requirements to develop a sound design for a power plant power supply that allows remote connectivity and monitoring for a sound healthy operation.

Student qualifications required:

Third year with PSIM/ORCAD simulation capabilities.

Expected training/skills to be received by the Student:

The student will go through a complete design cycle for the power supply.
IEEE Writing Skills.
Prototyping.
Hands-on experience.
Modeling Studies.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Qusay Mahmoud

Project title: Generative AI for Design and Development of IoT Applications

Summary of research project: The objective of this research project is to investigate how generative artificial intelligence (AI) can be used to design and develop internet of things (IoT) applications, and design and develop a framework for building IoT applications.

Student responsibilities/tasks:

Research and development.
Literature review.
Writing.
Design and development of software - i.e. programming.

Student qualifications required:

Completion of 2nd year of the Software Engineering program, with excellent communication (writing and oral) skills.
cGPA >= 3.7.

Expected training/skills to be received by the Student:

Research skills, including critical and creative thinking and writing of research papers.
Implementation and evaluation of software systems.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Ramona Fayazfar

Project title: Low carbon materials for 3D printing

Summary of research project: The shortage of materials for additive manufacturing and environmental concerns hinder its widespread adoption. To address this, my research focuses on sustainable additive manufacturing and circular materials principles. I aim to develop environmentally friendly feedstock materials for cost-effective 3D printing, utilizing waste and recycled materials like biomass, industrial discards, ocean plastic waste, and recycled metal powders.

Student responsibilities/tasks:

The student is required to optimize the formulation of newly developed recyclable materials compatible with 3D printing, using low carbon filler and recycled plastic waste, etc., and conduct advanced characterization to understand the structure-property-processing interrelationship.

Student qualifications required:

Courses: materials and preferably any course in polymer and polymer composite.
Minimum grade: 3.5.
Skills: has hands-on experience working with materials and characterization techniques in the lab.

Expected training/skills to be received by the Student:

The student understands how to develop novel material out of waste and optimize formulation for 3D printing.
The student gets skills on how to characterize a newly developed material in the lab space.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Scott Nokleby

Project title: Coordinated Control of UGV-UAV Systems

Summary of research project: This project explores the coordinated control of systems comprised of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) where data is shared amongst the UAVs and UGVs and remote operators (or overseers). Ideally, the human overseers should be minimally involved in the functioning of the system, providing overall goals and tasks. The system will autonomously determine which mobile robot or robots are best suited for the desired task and determine the best path to reach the goal and execute the tasks. The various systems will all contribute data to an overall map of the environment that will be used by the human overseer(s) to monitor the global picture.

Student responsibilities/tasks:

The student will work on tasks related to the design and development of advanced robotic systems. Duties include, but are not limited to:

Designing, developing, programming, and building prototypes.
Designing and conducting experiments.
Analyzing experimental results.
Writing reports and peer-reviewed publications.
In addition, the candidate is expected to collaborate with other personnel working in the Mechatronic and Robotic Systems Laboratory.

Student qualifications required:

The successful candidate must have strong engineering, design, mathematics, programming, and written/oral English communication skills.
Robotics experience is an asset including experience with Robot Operating System (ROS).
Minimum GPA B+ and completion of second year of their engineering program are preferred.

Expected training/skills to be received by the Student:

Designing, programming, building, and testing/debugging robotic systems.
Learning how to operate and program a Boston Dynamics Spot robot.
Learning how to use Robot Operating System (ROS).

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Shahram ShahbazPanahi

Project title: Bot Trader Automation

Summary of research project: In this project, the candidate will write different functions and code in Matlab and Python to submit, monitor, report, cancel trade orders to an investment broker platform.

Student responsibilities/tasks:

The student will write code to interact with the API of an investment platform with the aim to automate daily trading algorithms developed by the supervisor.

Student qualifications required:

The student should be proficient in Matlab and Python and be able to learn how to work with the API of an investment platform.

Expected training/skills to be received by the Student:

Financial market.
Trading.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Zeinab El-Sayegh

Project title: Thermal Analysis of a Winter Passenger Car Tire Model

Summary of research project: This research aims to implement a thermal analysis feature into an existing winter passenger car tire model. The analysis will be done utilizing a 235/55R19 tire model previously modeled and validated. Upon completion of this project, it is expected to have a computational tire model with a thermal analysis and variable friction features.

Student responsibilities/tasks:

Learn the Finite Element software "Pam-Crash".
Perform a literature review of recent research in tire mechanics.
Develop a thermal card model for the existing tire model.
Analyze the new thermal model using several tire-terrain interaction tests.

Student qualifications required:

Student should be third or fourth-year automotive engineering.
Should have knowledge of CAD design and software.
Should have a minimum GPA of 3/4.3.
Should be willing to come to work from office at least 3 days a week.

Expected training/skills to be received by the Student:

Student will get training on FEA software.
Student will learn how to perform a literature review.
Student will learn how to write conference papers.

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Zia Saadatnia

Project title: Smart Wearable Medical Devices for Sleep Disorder Diagnosis and Monitoring

Summary of research project: Smart wearable medical systems rose to prominence recently such as motion tracking, health monitoring, biomedical signals, and diagnosis systems. We are seeking a passionate candidate for a project on the development of a smart wearable medical device (mouthpiece) for sleep disorder diagnosis and therapy. The candidate will work on the design and development of various sensing modules and embedded systems and their integration into the structure of a wearable device as well as assessing the functionality of the wearable device. By joining our team, the candidate will have the opportunity to work on a demanding research area, expand their hands-on lab skills, and fortify their resume.

Student responsibilities/tasks:

Working on the mechatronics design of the project such as microcontrollers, embedded systems, and real-time signal acquisition and processing.
This includes both hardware (e.g., microcontrollers) and software (e.g., MATLAB/Python programming of the hardware and signal analysis) aspects.
Working on the structural design of the prototype via Computer-Aided Design and Manufacturing tools such as 3D Drawing, Design Assembly, 3D scanning/printing.

Student qualifications required:

Knowledge of mechatronics (e.g., microcontrollers, embedded systems).
Knowledge of computer-aided design, Drawing, Assembly, and 3D scanning/printing.
Understanding of computer hardware, device drivers, and programming languages (e.g., MATLAB/Python).
Understanding of real-time signal acquisition and processing systems is an asset.

Expected training/skills to be received by the Student:

Training on the wearable technologies for biomedical systems such as sleep apnea diagnosis.
Training on the design and application of smart materials and structures for sensors developments.
Training on the integration of mechatronic systems in a closed-loop fashion for real-time monitoring systems.
Experiencing collaboration with a team from an industry partner, a hospital research center, and researchers from academic institutions.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR