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Faculty of Engineering and Applied Science Project Summaries

Supervisors

Supervisor name: Aaron Yurkewich

Project title: HERO Glove - exoskeleton design for enhanced grip force, dexterity and robustness

Summary of research project: Investigate passive-active mechanisms that enhance force and dexterity

This student will explore the use of a hybrid of passive and active systems for the HERO Glove, utilizing OpenSim musculoskeletal hand modelling, computer-aided design software (CAD), prototype construction, system identification, dynamics modeling and healthy subject evaluation.

To evaluate the performance of this Hybrid HERO Glove, this student will recruit a gender-balanced sample of 10-20 healthy subjects to simulate hand paralysis. Subjects will be outfitted with hand motion trackers and EMG sensors, while their hand is actuated, using button control, by the original HERO Glove or the Hybrid HERO Glove.

Student responsibilities/tasks:

The student will use OpenSim musculoskeletal hand modelling, computer-aided design, prototype construction, system identification, dynamics modeling and healthy subject evaluation. The planned innovations are:

Passive-active thumb mechanism for passive palmar abduction support and series-elastic thumb extension-flexion assistance.
A differential gripping mechanism that equalizes the force that each finger applies to an object.

Student qualifications required:

Mechatronics or Mechanical engineering student with a grade of B or higher in MECE 3030U CAD.

Expected training/skills to be received by the Student:

Research: Student will complete literature reviews on hand robots.
Design: Student will design passive-active mechanical systems.
Tools: Student will complete experiments with healthy subjects using EMG and motion capture.
Writing: Student will prepare documents for Health Canada approvals and research articles.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Ahmad Barari

Project title: Metal 3D Printing of Complex Parts

Summary of research project: Advanced Digital Design, Manufacturing, and Metrology Laboratories (AD2M Labs) actively research in area of additive manufacturing. The objective in this project is to find the best parameters of the machine for metal 3D printing of complex parts.

Student responsibilities/tasks:

Working with their research mentors.
Conducting experiments.
Setting up the machines and maintenance of the research equipment.
Collecting data.
Inspection.
Validation tests.
Verification analysis.
Documentation.
Presentation.

Student qualifications required:

Students familiar to computer programming and CAD/CAM software tools.

Expected training/skills to be received by the Student:

Metal 3D printing.
Digital metrology and inspection.
Advanced simulation software tools.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Akramul Azim

Project title: Machine Learning-Based Test Case Elimination in Continuous Integration Environments

Summary of research project: Test case elimination is of great importance in test process optimization to make efficient use of testing resources, especially when it comes to integration testing for different code submissions in continuous integration environments. Machine learning can be used to identify the patterns of each code submissions and evaluate their quality characteristics. In this research, we aim to develop a machine learning based strategy that can automatically eliminate the test suites that would not be impacted by a change and identify the most likely test suites 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: Experimental Flow Control in Aerospace Applications

Summary of research project: When decommissioning nuclear power plants, there is a significant amount of steel, concrete, rebar, or other supports that need to be removed. Determining the optimal techniques for dismantling (demolition) and the factors that may affect choices for waste handling is a challenge. This work will develop a model that can be used for assessing different civil structures and determining options for dismantlement and handling waste streams.

This may include assessing the radiological hazards associated with the type of structural material and consider commercial and research based techniques for addressing the problems. The student will work in a team environment to develop a computer model.

Student responsibilities/tasks:

Perform literature review of the subject.
Design and build experimental setup.
Run the experiments and report the results.
Present results of the work.

Student qualifications required:

High GPA (above 3.7).
Strong background in fluid mechanics.
Hands-on experience with power tools is preferred.
Strong communication skills.

Expected training/skills to be received by the Student:

Training in wind tunnel facility operation.
Training in data acquisition.
Presentation skills training.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Brendan MacDonald

Project title: Analysis of Steel Mill Waste Heat

Summary of research project: The production of steel results in a substantial amount of waste heat generated, which presents an opportunity for capturing and using the waste heat energy to save money and offset the greenhouse gas emissions. It is currently not well understood how much waste heat is generated by each process in steel production and how it could be captured. This project is a partnership between Ontario Tech University and the Gerdau Whitby Steel Mill. The objective of this project is to measure and analyze the waste heat generated at the steel mill. The undergraduate research will support this measurement and analysis.

Student responsibilities/tasks:

There are many tasks required for this project, particularly involving energy balances and measuring of the thermal properties of the exhaust from the steel making processes.
This can also include things like calculations, numerical modelling, and building instrumentation systems.
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.

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 thermodynamics and energy balances, and importantly how the theory can be applied to analyze actual real-world systems.
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 Detailed Analysis of Ontario Tech's GHG Emissions

Summary of research project: Like many post-secondary institutions Ontario Tech University has a good greenhouse gas (GHG) emissions inventory (Scopes 1 and 2). The university has also committed to an aggressive GHG mitigation target of â€˜net-zeroâ€™ by 2040. This target however is believed to encompass all GHG emissions, i.e., Scopes 1, 2 and 3 (upstream and downstream). The researcher would complete a comprehensive 2024 GHG inventory (Scopes 1, 2 and 3). The methodology would be consistent with inventories for Durham Region, City of Oshawa, Ontario Power Generation and possibly the Great Lakes Region. The inventory would be peer reviewed and presented to the Region of Durhamâ€™s Regional Council.

Student responsibilities/tasks:

The student will meet with Ontario Tech staff and academics, review existing literature, and provide a research plan for completing the inventory (particularly Scope 3 emissions). This first part is expected to take 2-3 weeks.
After that, the student would complete data acquisition and use industry-accepted practices to estimate data when required. The draft inventor would be discussed with key stakeholders.

Student qualifications required:

A course(s) in statistics would be useful, as well as exposure to data systems, energy management, environmental science, and climate change mitigation.

Expected training/skills to be received by the Student:

Literature Review: learn where credible information sources might be found, how to differentiate quality, and how to properly reference.
Greenhouse gas (GHG) inventories: training in inventories (availability, terminology, comprehensiveness).
Data systems: learn how to complete data tables, including the need and application of estimations and deriving values from first principles.
Understand the main drivers of GHG emissions in Canada, and how they might best be mitigated.
Stakeholder consultations: gain familiarity with corporate and municipal stakeholders as well as individual staff members and faculty.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Ghaus Rizvi

Project title: Advancing Volumetric Additive Manufacturing System for Complex Geometries

Summary of research project: The volumetric additive manufacturing (VAM) method is a novel additive manufacturing process that drastically reduces build time from hours to minutes. In this process, a photocurable resin is exposed to images from different angles, generating accumulated light intensity. Once the energy of the light reaches the critical exposure dose for the resin, it allows the resin to solidify in complex 3D shapes all at once. Currently, a lab-scale VAM setup is developed for producing simple shapes. The overall objective of this project is to improve the existing setup for building complex-shaped objects and investigate the process parameters controlling the size and features' accuracy.

Student responsibilities/tasks:

Improve the design of the VAM setup.
Prepare CAD file of the object and process the images (radon transform).
Prepare resin formulations and use for producing objects.
Several 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:

Should have completed 2nd year of an Engineering program.

Expected training/skills to be received by the Student:

CAD software usage and image processing by MATLAB.
Enhance skills in mechanical design.
Statistical design of experiment methodology.
Hands-on experience in using a digital microscope for 3D printed object analysis.
Experience with material design (polymer resin preparation by controlling initiator amount).

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Ghaus Rizvi

Project title: Development of Flexible Nanofiber-Based Piezoelectric Sensors for Tactile Sensing in Soft Robotics

Summary of research project: The piezoelectric sensing mechanism is self-powered, highly sensitive, and robust. Flexible sensors based on polymer nanotechnology are preferred in many applications specifically in robotics. Nanotechnology-based sensors have high sensitivity, softness, wider dynamic range of measurement, low hysteresis, and smaller device size. A combination of piezoelectric polyvinylidene fluoride (PVDF) and highly flexible thermoplastic polyurethane (TPU) can offer tactile sensors with high flexibility, more mechanical recovery and improved sensitivity. The primary objective of this project is to utilize nanofiber-based sensing materials within electronic skin applications for soft robotics.

Student responsibilities/tasks:

Making flexible and piezoelectric electrospun mat.
Preparing sensors using the nanofiber scaffold.
Fabrication of device with multiple tactile sensing elements acting as skin.
Testing of the prepared device

Student qualifications required:

Should have completed 2nd year of an Engineering program.

Expected training/skills to be received by the Student:

Gain knowledge about flexible sensors.
Gain familiarity with smart and advances material.
Enhance skills in mechanical design and digital electronics.
Hands-on experience with signal measurements and analysis.
Experience with nano materials.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Glenn Harvel

Project title: Data Analysis of Nuclear Airlock Operation

Summary of research project: The NDL lab has built an airlock simulating those used in nuclear power plants. The intent is to use the airlock to create databases for analysis related to maintenance. The work will include generation of data based upon daily operation of the facility, analysis of the data, and creating deterministic and machine learning models appropriate for analyzing the data.

Student responsibilities/tasks:

Student will utilize the airlock to generate data on a daily basis.
Student will conduct preliminary data analysis to confirm adequacy of the data.
Student will develop machine learning and deterministic models to match the data.
Student will prepare a final report of the summer work.

Student qualifications required:

Completion of 3rd year in either a nuclear engineering or a computer science program.
Student must also have good knowledge of computing skills and programming skills.
Student must be able to work in a physical laboratory.

Expected training/skills to be received by the Student:

Student will receive safety training for working in a lab environment.
Student will receive advanced training on coding.
Student will learn about the nuclear industry and applications within the nuclear industry.
Student will practise presentation and report writing skills.
Student will practise team 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: Decommissioning modelling of nuclear civil structure

Student responsibilities/tasks:

Perform literature review related to the topic.
Develop a numerical model of the radiological aspects of the structure.
Link numerical model with a database on dismantling, decontamination, and demolition techniques.
Run the model for different scenarios.
Prepare a written report summarizing the findings.

Student qualifications required:

Nuclear engineering student. Completion of 3rd year is an asset but 2nd year students will be considered as well.
Ability to code. There will be assistance in coding provided but the student is expected to have some existing capability.
An interest in decommissioning technology.

Expected training/skills to be received by the Student:

Student will receive training in nuclear decommissioning technologies that currently exist and their application to the problem.
Student will also receive support in additional code training and working with databases.
Student will have access to research group and experience additional training related to other projects as well as training supporting teamwork.
Student will be given feedback related to communication and writing skills regarding their reports and presentation discussions.
Student will receive training related to working in the nuclear field.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Haoxiang Lang

Project title: Design and Development of a Robotic Arm

Summary of research project: The project aims to design and develop a mechanism for surgical robotic arm that can firmly hold surgical needles and can sense force while operation. The specific objectives are:

To design a robotic arm and end-effector that can firmly grasp and easy-to-release different types of surgical needles with high precision and stability.
To design a sensing device that can measure and adjust the force applied by the end-effector on the needle and the tissue during operations.
To evaluate the performance and usability of the mechanism in terms of accuracy, safety, dexterity, and haptic feedback.

Student responsibilities/tasks:

A prototype of A robot that meets the functional and technical requirements.
A user manual that explains how to use its features.
A test report that evaluates the performance and usability.
A presentation that showcases the robot and its benefits.

Student qualifications required:

Mechatronics background.
CAD.
Programming experience.

Expected training/skills to be received by the Student:

Fundamental Knowledge of Robotics.
Mechatronic Design.
Programming skills.
Team work and communication.
Technical writing.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Horia Hangan

Project title: Aerodynamic Impacts of Severe Weather Conditions on Autonomous Vehicle Performance

Summary of research project: New-generation vehicles, like autonomous cars, rely heavily on advanced sensor networks to gather environmental information for navigation. However, challenging weather conditions such as rain and snow can contaminate sensor surfaces, compromising their functionality and increasing accident risks. This research aims to develop robust methods for analyzing and understanding the intricate processes of sensor surface contamination. The findings will establish foundational concepts, leading to innovative strategies and devices to mitigate these challenges effectively.

Student responsibilities/tasks:

Perform experiments with simulated rain and snow 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.
Applying machine learning techniques for data post-processing

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: Hossam Gaber

Project title: Modeling and Experimental Testing of Plasma-Based Waste Treatment

Summary of research project: The project is aiming to develop models and experimental tests for plasma-based waste-to-energy. The work includes the use of engineering design tools, modeling and simulation, and experimental test.

Student responsibilities/tasks:

Engineering design.
Modeling.
Simulation.
Experimental work.
Write reports.
Develop presentations.
Collect and analyze data.
Literature review.

Student qualifications required:

Understanding of electric circuits/electronics.
Engineering design.
Modeling and simulation.
Material properties.
Control systems.

Expected training/skills to be received by the Student:

Plasma systems.
Electronics and control system design.
TGA-FTIR-GCMS.

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 with human factor considerations for nuclear power plants

Summary of research project: The project is aiming to design digital control room for nuclear power plants and SMR with considerations of human factors. Model plant operation activities and map to digital control room design, and model human activities and behavior and evaluate performance for different operation scenarios. Design human performance monitoring tools and analyze data for different test scenarios.

Student responsibilities/tasks:

Design digital control room for SMR and nuclear power plants. Evaluate human factors involved in control room activities for different operational scenarios. Model plant operation activities and map to digital control room design. Model human activities and behavior and evaluate performance for different operation scenarios. Design human performance monitoring tools and analyze data for different test scenarios.

Student qualifications required:

Engineering design.
Modeling and simulation of plant operation.
Modeling of human activities and performance.
Python programming.
Data analytics.
User interface design.

Expected training/skills to be received by the Student:

NPP simulation.
AI and machine learning.
Sensors integration and IoT.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Hossam Gaber

Project title: Development of Hybrid Fueling and Charging Stations

Summary of research project: This project is aiming to designing hybrid fueling and charging station that include hybrid energy system, hybrid energy storage, and interfaces with energy supply from hydrogen, gasoline, diesel, and electricity supply systems. The design is based on demand profiles, hybrid energy system, hybrid energy storage (flywheel), greenhouse gas emissions, cost of energy, and mobility requirements.

Student responsibilities/tasks:

Design models of hybrid charging station.
Modifications to existing gasoline and diesel fueling stations.
Control strategy and system architecture.
Energy management.
Performance measures for different mobility demand profiles.
Design the target energy system for the hybrid charging station, with monitoring and control systems.
Design data and control to monitor and plan the operation of the hybrid charging station.

Student qualifications required:

MATLAB.
Python.
Electric circuits.
Embedded control system.
Energy systems.
Modeling.
Simulation.

Expected training/skills to be received by the Student:

HOMER simulator.
Data analytics and AI algorithms.
Energy system modeling and simulation.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Martin Agelin-Chaab

Project title: Strategies for Cleaning Autonomous Vehicle Sensors 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 have finished 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: Mitchell Rushton

Project title: Investigations into Novel Forms of High-Speed Robotic Manipulators

Summary of research project: The scope of this project is to design and develop a specific component or subsystem and is part of a larger research program that aims to develop novel forms of high-speed and low-cost robotic manipulators. The specific component to be designed will depend on the specific interest and expertise of the student: for the more mechanically inclined, the focus will be on mechanism/actuator design. For those with a more electrical-focused background, the focus will be on design of a custom power supply/motor control solution.

Student responsibilities/tasks:

Perform independent background research to understand the current state-of-the-art related to the Project area.
Design and analyze A new solution using Computer-Aided-Design tools and simulations.
Arrange manufacturing of designed parts as needed.
Have A functioning system assembled and tested by the end of the term.

Student qualifications required:

To be eligible, the student should at minimum have completed second-year of a related engineering program (mechatronics, mechanical, electrical), although having completed third year is strongly preferred. Exceptions may be considered in the presence of other relevant experience (such as co-op or relevant past work experience).

Expected training/skills to be received by the Student:

Independent Research/Self-Study.
CAD modelling and analysis of mechanical components.
Prototype development.
PCB design and assembly.
Concepts in high-speed motor control and real-time embedded systems.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Mohamed Youssef

Project title: Power Supply for the Telecom Applications

Summary of research project: This project will describe a novel concept to build a power supply suitable for low power applications like laptops or desktops. The circuit is intended to be compact but efficient with optimized cost. This can be a multiphase buck or forward converter. This is essential for futuristic telecom activities.

Student responsibilities/tasks:

PSIM Simulations.
Prototyping and writing papers.

Student qualifications required:

Incoming fourth year preferred with high GPA

Expected training/skills to be received by the Student:

PSIM Simulation.
Hardware Prototyping.
IEEE Writing Skills.
Presentation Skills.
Team player.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Noha Hassan

Project title: Privacy-Preserving Machine Learning for Cyber Threat Intelligence

Summary of research project: This research project aims to develop privacy-preserving machine learning techniques to enable effective cyber threat analysis through collaborative data sharing while preserving privacy.
Objectives:
1. Develop ML models for intrusion detection, malware analysis, botnet/DDoS detection
2. Advance privacy-preserving techniques like federated learning and homomorphic encryption
3. Enable collaborative threat modeling without revealing private data

Student responsibilities/tasks:

Literature Review.
Algorithm Development.
Simulation and Testing.
Data Analysis.
Model Validation.
Documentation and Reporting.

Student qualifications required:

Optional: SOFE 3720U Introduction to Artificial Intelligence
Technical Skills:
- Proficiency in programming languages like Python, with a focus on data analysis
- Strong background in conducting literature reviews and synthesizing research findings.

Expected training/skills to be received by the Student:

Students will receive foundational training on implementing machine learning (ML) models for cyber security threats.
Students will develop skills in advanced privacy preserving methods like federated learning and homomorphic encryption.
Students will learn to evaluate and improve security defenses using ML.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: PROJECT IN REVIEW

Supervisor name: Noha Hassan

Project title: Towards Engineering Hybrid Convolutional Systems for Software Optimization

Summary of research project: As software systems continue growing in size and complexity, developing reliable and efficient solutions requires powerful techniques for program analysis, verification and optimization. Our vision is to explore how hybrid classical machine learning (ML) can address these challenges.
Objectives:
1. Design convolutional neural networks (CNNs) for code characterization and defect prediction
2. Combine ML methods with advanced optimization techniques for optimizing software compilation, memory management, and software performance
3-Develop systems that assist in automated code reviews

Student responsibilities/tasks:

Literature Review.
Algorithm Development.
Simulation and Testing.
Data Analysis.
Model Validation.
Documentation and Reporting.

Student qualifications required:

SOFE 2720U Principles of Software and Requirements Engineering.
Optional: Min Grade: B.
Technical Skills:
- Proficiency in programming languages like Python, with a focus on data analysis.
- Strong background in conducting literature reviews and synthesizing research findings.

Expected training/skills to be received by the Student:

Hands-on experience in designing, training, and optimizing convolution neural networks.
Understanding of code refactoring process and defect prediction.
Skills in collecting and cleaning code for machine learning training.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: PROJECT IN REVIEW

Supervisor name: Ramona Fayazfar

Project title: Recycling Waste Plastic Stream via 3D Printing

Summary of research project: This project aims to develop a sustainable method for reprocessing plastic waste streams into materials compatible with 3D printing. Through material formulation, we will incorporate targeted additives to enhance the mechanical, thermal, and flow properties of recycled plastics, making them suitable for additive manufacturing. Research Objectives:
We formulate 3D-Printable Materials: Assess Material Properties: Test printability, durability, and mechanical properties to ensure reliable performance.

Student responsibilities/tasks:

The student will prepare plastic waste samples for reprocessing, create and test material formulations by incorporating additives to enhance 3D printing compatibility, produce and evaluate 3D-printable samples using a 3D printer, and (4) conduct mechanical, thermal, and structural analyses to assess material performance, supporting a sustainable approach to additive manufacturing (AM).

Student qualifications required:

Courses in Materials Science; Chemistry or Polymer Engineering preferred.
Familiarity with additive manufacturing (AM) and 3D printing.
Basic lab skills in material prep and testing.
Experience with mechanical and thermal analysis.
Minimum B+ in relevant coursework.
Strong attention to detail, time management, and problem-solving skills.

Expected training/skills to be received by the Student:

Hands-on experience in material formulation and additive manufacturing (AM) processes, including 3D printing and extrusion.
Training in mechanical, thermal, and structural analysis techniques for evaluating material performance.
Skills in sustainable materials research, focusing on transforming waste into high-value, 3D-printable products.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Ramona Fayazfar

Project title: Low Carbon Material for 3D Printing Construction

Summary of research project: This research project aims to develop low-carbon material formulations tailored for 3D printing in construction, focusing on reducing the carbon footprint in building materials. By integrating sustainable additives and binders, we will formulate eco-friendly composites that meet the structural and functional demands of construction applications. The project will include comprehensive mechanical and functional testing to ensure durability and load-bearing capacity, along with extensive printability tests to assess the compatibility of formulations with advanced 3D printing equipment.

Student responsibilities/tasks:

Develop and prepare low-carbon material formulations for 3D printing construction applications.
Conduct mechanical tests to assess strength, durability, and structural performance.
Perform functional and printability tests to ensure material compatibility with 3D printing equipment.
Document and analyze test data, reporting findings to the research team.
Collaborate on improvements to material formulations based on test results.

Student qualifications required:

Courses in Materials Science, optional in Chemistry, or Polymer Engineering.
Familiarity with 3D printing processes.
Basic lab skills in material preparation and testing.
Experience with mechanical testing methods preferred.
Minimum B+ average in relevant coursework.
Strong attention to detail, time management, and problem-solving skills.

Expected training/skills to be received by the Student:

Hands-on experience in developing and optimizing low-carbon materials for 3D printing applications.
Training in advanced mechanical, functional, and printability testing methods.
Skills in data analysis, documentation, and reporting of experimental results.
Enhanced problem-solving abilities through iterative material formulation and testing.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Sanaa Alwidian

Project title: Development of a Voice-driven Requirements Elicitation Tool

Summary of research project: This project focuses on developing a voice-driven tool for Requirements Elicitation in Safety-Critical Systems (SCS), such as autonomous driving systems. The tool will use speech-to-text and Natural Language Processing (NLP) to capture user requirements through verbal input. The project has the following objectives:

1) Enable real-time organization and tagging of elicited requirements for clarity and traceability.
2) Enhance the requirements elicitation process by allowing hands-free, intuitive interaction for diverse stakeholders.
3) Simplify documentation of requirements for Safety-Critical Systems (SCS) through automated transcription and categorization.

Student responsibilities/tasks:

Perform literature review related to the topic.
Design and implement a voice-driven tool using speech-to-text APIs (e.g., Google Speech-to-Text) and NLP frameworks.
Develop a mechanism to classify requirements as functional, or performance-related in real-time.
Create a user interface for stakeholders to interact with the tool, ensuring accessibility and usability.
Conduct tests with sample scenarios from e.g., healthcare or autonomous systems.

Student qualifications required:

Excellent Programming experience (C++, Java, Python).
Software Engineering or Computer Science background.
Completion of 3rd or 4th year is an asset, but 2nd year students will be considered as well.
A min grad of A- in the Requirements Engineering course if applicable.

Expected training/skills to be received by the Student:

Student will gain hands-on experience with speech-to-text APIs and Natural Language Processing (NLP) frameworks for building interactive, AI-driven applications.
Student will learn techniques for eliciting, organizing, and classifying requirements in safety-critical domains, emphasizing real-world applicability.
Student will enhance their skills in designing, implementing, and testing functional prototypes with a focus on user-centric design and usability.
Student will develop expertise in maintaining project documentation, conducting user testing, and effectively presenting technical outcomes to diverse stakeholders.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Scott Nokleby

Project title: Multi-Modal Robots

Summary of research project: The goal of this project is to develop a proof-of-concept multi-modal robot that is equally effective in operating on land and in air. The project will focus on developing a legged robot that can also fly. In essence, a Pegasus robot will be developed that is equally capable of moving on the ground as it can in the air. Such a robot must easily transition between walking and flying modes. To achieve stable flight, some form of multi-rotor design will be utilized. However, this multi-rotor system will need to be stowed in as a compact manner as possible when in walking mode to ensure that it does not interfere in the robot's ability to navigate on the ground.

Student responsibilities/tasks:

The student will work on research 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 MARS Lab.

Student qualifications required:

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

Expected training/skills to be received by the Student:

Learning Robot Operating System (ROS).
Designing, programming, building, and testing/debugging robotic systems.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Shabnam Pejhan

Project title: User-Adaptive Framework for a Robotic Assistive Cane

Summary of research project: Instrumented canes aim to provide navigation assistance and fall prevention. Current challenges in designing such canes include their bulky structure, added weight, and adaptation to user motion. This project aims to improve the robotic cane based on inverted pendulum theory and a novel adaptive system. The objectives are to (1) Integrate sensors to capture real-time user input, including pressure distribution and applied forces, (2) Analyze signals to detect shifts in user stability and provide input to adapt the cane's response to optimize support, and (3) Develop an algorithm to estimate risk of fall or loss of stability. This will enable natural synchronization with the user's motion.

Student responsibilities/tasks:

Install and calibrate pressure and motion sensors on the robotic cane.
Verify sensor functionality and synchronize with the system.
Process data to detect changes in user balance and stability.
Implement filtering techniques to improve data quality.
Develop an algorithm to assess fall risk based on data.
Troubleshoot issues during testing.
Collaborate with team for feedback.
Document design and prepare progress reports.

Student qualifications required:

Minimum overall GPA: 3.0 out of 4.3 (B).
Completed Courses: Control Systems, Sensors and Instrumentation, and Actuators and Power Electronics, each with a minimum grade of B-.
Skills:
- Sensor integration and calibration.
- Data processing.
- Programming (Python, C, MATLAB, etc.).
- Troubleshooting technical issues.
- Work effectively in a team.

Expected training/skills to be received by the Student:

Hands-on experience with sensor fusion design and integration within a robotic system, including signal calibration and filtering techniques.
Skills in developing algorithms that translate sensor data into risk of falls or instability assessment and generate inputs for control actions.
Training in the use of interdisciplinary design tools and techniques to enhance the overall functionality of a device based on human-centered inputs.
Hands-on training in programming languages commonly used in robotics, such as Python or C++.
Enhancing teamwork and communication skills by collaborating with team members throughout design process.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Shabnam Pejhan

Project title: Human-Centered Framework for Designing Robotic Walking Aids

Summary of research project: The aging global population is driving demand for mobility aids that support elderly independence. While technological advancements offer new possibilities, many devices fail to meet usersâ€™ needs or gain acceptance. This project aims to develop a user-centric framework for designing a walking aid with integrated control modules for elderly users. The objectives are to address: (a) What key factors, informed by available interview results and user reports, can refine mobility aid designs? (b) How can integrating user study analysis, quality function deployment, and simulation-based design advance smart walking aids? This will establish a set-up to assess the human-centered design solutions.

Student responsibilities/tasks:

Create mind maps from available user reports to obtain mobility needs and user attributes.
Translate user needs into technical specifications via Quality Function Deployment.
Create system models for customized walking aid solutions.
Create visual/functional prototypes of the proposed solutions.
Present prototypes to stakeholders, using a questionnaire to gauge acceptance.
Document design and prepare progress reports.
Collaborate with team.

Student qualifications required:

Minimum overall GPA: 3.0 out of 4.3 (B).
Completed Courses: Engineering Design, Control Systems, Sensors and Instrumentation, Computer Aided Design, each with a minimum grade of B-.
Skills:
- Sensor integration and calibration.
- Data processing.
- Simulation software (e.g., MATLAB, Simulink, etc.).
- Troubleshooting technical issues.
- Teamwork.

Expected training/skills to be received by the Student:

Hands-on skills in systematic human-centered design approach, merging quality function deployment, inventive problem solving, and mind map analysis.
Practical experience in simulation tools to test and optimize designs under different conditions.
Training in conducting usability testing, collecting user feedback, and applying it to improve design solutions.
Skills in working with users and stakeholder, cultivating a transdisciplinary skillset essential for the design of assistive devices.
Enhancing teamwork and communication skills by collaborating with team members throughout design process.

Length of award: 16 Weeks

Location of award: Hybrid

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

Supervisor name: Tao Liu

Project title: Design of lightweight passive exoskeletons for low back pain prevention in lifting tasks

Summary of research project: In Canada, despite automation and mechanization of work settings, approximately 60%-80% of people acquire LBP due to their involvement in manual materials handling (MMH) tasks at work. This results in individual disability and work-related injuries, which translates into decreased productivity and increased healthcare costs. The proposed study will use innovative computational approaches to design personalized lightweight passive exoskeletons to decrease risk of LBP.

Student responsibilities/tasks:

Design mechanism and structure of passive exoskeletons to lessen spinal load during lifting tasks.
Manufacture passive exoskeletons.
Validate the effectiveness of exoskeleton design through pilot study.
Deliver project finding to stakeholders and researchers through presentations.

Student qualifications required:

Proficient understanding of course concepts from Mechanical Design (MECE3220) and Computer Aided Design (MECE 3030).
Experience with SolidWorks and MATLAB is required.
Strong oral and written communication skills are required.

Expected training/skills to be received by the Student:

Learn about spine biomechanics and evaluate spinal load using computational modelling.
Gain valuable hands-on experience in exoskeleton design and manufacturing.
Participate in pilot study to validate exoskeleton design.
Develop excellent communication skills through presentations and conferences.
Strengthen written communication and professional writing by preparing technical reports and papers.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

Supervisor name: Zia Saadatnia

Project title: Development of a Wearable Mouthpiece for Tongue Movement Monitoring and Sleep Apnea Therapy Application

Summary of research project: This project aims to develop a wearable mouthpiece (similar design to mouthguards or dentures) with embedded pressure sensors and electrodes for tongue movements monitoring and electrical stimulation for sleep apnea diagnosis and therapy. The project has two objectives:

The design of the mouthpiece including CAD (e.g. by SolidWorks), finite element modeling (FEM) e.g. by ANSYS or other FEM software, tongue motion analysis, and 3D printing;
The mechatronics of the mouthpiece including embedded systems, sensors and microcontroller interfaces, data collection (wireless or SD card modules) and potentially using AI/ML for predicting pressure distribution in the tongue-jaws interactions.

Student responsibilities/tasks: The candidate may be involved in either objective of the project (or both) based on their skills:

Objective 1- Design of the mouthpiece:
- CAD (e.g. SolidWorks).
- Finite element modeling (FEM).
- Tongue motion analysis.
- 3D printing.
Objective 2- Mechatronics of the mouthpiece:
- Designing embedded systems.
- Sensors and microcontroller interfaces.
- Data collection (wireless or SD card modules).
- Using AI/ML for predicting pressure distribution.

Student qualifications required:

Computer Aided Design.
Mechanical Engineering Design.
Finite Element Modeling and Analysis.
Electronics Applications in Mechatronics.
Programming skills.
Mechatronics Design.
Sensors and Embedded systems.

Expected training/skills to be received by the Student:

Gain expertise in CAD design and Finite Element Modeling for complex mechanical systems.
Gain experience in embedded systems design, electrodes and sensors integration, and data collection techniques.
Hands-on experience in 3D printing, mechatronics design, and prototyping of functional devices.
Strengthen teamwork and communication through collaborative problem-solving in engineering projects.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR