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Faculty of Business and Information Technology Project Summaries

Supervisors  

Amirali Salehi-Abari | Andrew Hogue | Bill Kapralos | Bin Chang | Julie Thorpe | Khalil El-Khatib | Loutfouz Zaman | Pejman Mirza-Babaei | Pooria Madani | Salma Karray | Shahram Shah Heydari | Steve Marsh

 

Supervisor name: Amirali Salehi-Abari

Project title: Graph Neural Networks for Recommender Systems

Summary of research project: Recommender systems are prevalent in our day-to-day life. They intelligently recommend desirable options to us (e.g., books in Amazon, movies in Netflix, etc.), which are consistent to our own taste or preferences.  Several recent developments have been made in applying deep learning in recommender systems. Of important and promising direction is utilizing graph embedding and graph convolutional networks for empowering recommender systems with graph-structured side information (e.g., social networks). Our goal is to develop effective deep learning algorithms for large-scale recommender systems in the presence of graph-structured side information. 

Student responsibilities/tasks:

  • The Student is expected to review the relevant research literature along with other team members.
  • The Student also will be heavily involved in development of the AI technologies and will co-author the consequent paper written from his involvement in this Project.
  • This Project provides a unique opportunity to the candidate for fostering his/her knowledge in AI, graph neural networks, and deep learning.

Student qualifications required:

  • The Student is expected to have familiarity with PyTorch and Deep Learning and be excellent in programming in Python.

Expected training/skills to be received by the Student:

  • Graph Neural Networks.
  • Programming in PyG.
  • Literature Review.
  • Academic Writing.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Andrew Hogue

Project title: Exploring 4D Video & Avatar Realism for Games

Summary of research project: This project will have a student work with a Masters student on a project exploring how we perceive game characters, volumetric video recordings, and dynamic Gaussian splatting technologies.  The student will be involved in learning about the technology, and building tools that enable us to study their effects in Unreal and Unity.

Student responsibilities/tasks:

  • The student will collect and read graphics research papers, summarize them, find and run existing codebases and develop a set of tools for Unity/Unreal to load and manipulate recorded data.

Student qualifications required:

  • Familiarity with Unity and/or Unreal.
  • Problem solving skills.
  • Independent worker.

Expected training/skills to be received by the Student:

  • Software Development.
  • Game Engine Tool Development.
  • Research skills.
  • Problem solving & Critical Thinking.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Bill Kapralos

Project title: Immersive Technologies for Medical Education

Summary of research project: Working with an interdisciplinary team of medical professionals, educators, and game developers/computer scientists, this position will involve either the development of, or modification of an existing virtual simulation/serious game for medical education.

Student responsibilities/tasks:

Responsibilities/tasks may include the following:

  • Development of modification of a virtual simulation(s)/serious game(s).
  • Conducting an internet search.
  • Prepare a manual describing the work conducted (e.g., describing the use of any developed serious game/virtual simulation).

Student qualifications required:

The ideal candidate will:

  • Have knowledge/prior experience with game development.
  • Knowledge with the Unity game engine.
  • Ability to work in a team environment.
  • Although the position is listed as Hybrid and thus some work from home is fine, there are times where work in-person (on-campus) is required.

Expected training/skills to be received by the Student:

  • How to conduct a search on a particular topic.
  • How to write and present a technical report.
  • Experience in working in an interdisciplinary team.
  • Experience in developing real-world virtual simulations/serious games.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Bin Chang

Project title: Directors' and Officers' Liability Insurance and Corporate Finance Decisions

Summary of research project: This project studies the impact of directors’ and officers' liability insurance on corporate finance decisions. Shareholder litigation is important for investor protection and can impact a firm’s corporate finance decisions. However, scant evidence exists regarding how firm-level mechanisms affect the discipling role of shareholder litigation and consequently, corporate finance decisions. Directors’ and officers’ insurance covers the defense cost and potential damage when its directors and officers are sued, and thus reduces the disciplining effect of shareholder litigation. Consequently, this project sheds light on its impact on corporate finance decisions. 

Student responsibilities/tasks:

  • Literature Review: Review assigned literature critically for a comprehensive understanding.
  • Data Collection: Gather directors’ and officers' insurance data from a reliable government site.
  • Data Analysis: Merge data, analyze cross-sectionally and over time to identify trends.

Student qualifications required:

  • Enrollment in the 2nd year or above in a Commerce program with a major or minor in finance.
  • Minimum GPA of 3.0 or above.
  • Excellent proficiency in English, both written and verbal.
  • Demonstrated ability to work independently.

Expected training/skills to be received by the Student:

  • The professor guides the student to access government websites, identify needed documentation, and compile the data needed.
  • The professor trains essential analytical skills for the project.

Length of award: 14 Weeks

Location of award: Remote

Available Award: Ontario Tech STAR

 

Supervisor name: Julie Thorpe

Project title: Secure Use of Password Managers and Passkeys

Summary of research project: Password managers and passkeys are considered useful solutions to the problem of remembering unique passwords across a multitude of accounts. However, their adoption is not widespread. Recent literature suggests that even when people adopt password managers, they are often not using the password generation features and still reusing some passwords. Passkeys are underutilized for a variety of reasons. This project aims to design and evaluate novel user interface enhancements for password managers and/or passkeys, as well as awareness tools to increase their secure use.

Student responsibilities/tasks:

  • Designing new user interfaces
  • Web programming of prototypes
  • Database design
  • Writing analysis scripts
  • Running user studies to collect data
  • Analyzing results
  • Writing
  • Reading relevant papers
  • Participating in meetings

Student qualifications required:

  • Programming course (Min. grade of A-)
  • Web programming experience or course(s).

Expected training/skills to be received by the Student:

  • Software design and development
  • Research methods
  • Security knowledge

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Khalil El-Khatib

Project title: Design and development of automated intrusion detection systems for 6G and Zero-Touch Networks (ZTNs)

Summary of research project: The 6G networks require network automation to meet the rapidly increasing demands and reduce operating costs. To achieve this, the concept of Zero-Touch Networks has been proposed, where AI/ML techniques play crucial roles in optimizing network performance and enabling automated decision-making. This project aims to develop autonomous security solutions in 6G networks using Automated ML (AutoML) techniques, which can adapt to new types of cyber threats more efficiently and with minimal human intervention. 

Student responsibilities/tasks:

  • The students will be responsible for performing literature review on the threat landscape of 6G networks, as well as helping with the prototyping and testing of proposed ML model, as well as helping with the interpretation of the results. 
  • The student will participate as well with the dissemination in the research work.

Student qualifications required:

  • Third or fourth year Student in networking and security, with a strong background in machine learning.
  • Good analytical and listening skills.
  • Strong oral and written communication skills.
  • A team player.

Expected training/skills to be received by the Student:

  • The student will receive training in developing and testing machine learning models to be used for security applications.
  • The student will be trained on performing research reviews and disseminating research output.

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Loutfouz Zaman

Project title: Visual Game Analytics for Mixed Reality

Summary of research project: This project focuses on improving our existing game analytics tool for Hololens. Objectives include integrating timestamps for precise analysis, refining data aggregation, and enhancing the UI for better interaction. We aim to support customizable game elements, incorporate AI for efficient bug detection, and adapt the tool for real-world game development applications. The project also explores optimizing analysis tasks, representing diverse player types, and extending capabilities to analyze dynamic game spaces. Adapting the tool for various platforms like VR, PC, and AR is also a key goal. This award offers a chance to significantly impact visual game analytics and design.

Student responsibilities/tasks:

Students will select and focus on tasks aligning with their skills and interests from the following: 

  • Enhancing data aggregation, improving user interface, integrating AI for bug detection, researching real-world applications, optimizing analysis processes, and adapting GAMR for various platforms. 
  • Responsibilities include design, development, and collaborative research, contributing to significant advancements in game analytics and design.

Student qualifications required:

  • Currently enrolled in an undergraduate program in Computer Science, Game Development, or related field.
  • Proficiency in programming and software development.
  • Experience with VR/AR/MR, AI, data analysis, or user interface design is a plus.
  • Strong analytical and problem-solving skills.
  • Passion for gaming and technology.

Expected training/skills to be received by the Student:

  • Advanced Data Analysis Techniques: Gain proficiency in handling and analyzing large datasets, learning to identify patterns and insights relevant to game analytics.
  • AI and Machine Learning Skills: Develop skills in AI and machine learning, particularly in the context of bug detection and predictive analytics within gaming environments.
  • User Interface Design and Development: Acquire hands-on experience in designing and improving user interfaces, focusing on usability and user experience in software tools.
  • Real-World Application Research: Learn methods of applying academic research to real-world scenarios, particularly in adapting tools for practical use in game development.
  • Cross-Platform Software Adaptation: Gain experience in adapting and optimizing software for various platforms, including VR, PC, and AR, broadening technical versatility.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Pejman Mirza-Babaei

Project title: Interaction design in live streaming games

Summary of research project: Live streaming platforms, such as Twitch, have rapidly changed the way that people consume and interact with game content. This project aims to improve our understanding of live streaming users and their interactions through profiling users. The student’s work will centre around the design of interactive live streaming mechanics. The primary outcomes of this project will be a set of guidelines aimed at improving the UX of interactive streamed content, such as games and eSports tournaments.

Student responsibilities/tasks:

  • Identify existing streaming games to evaluate their interaction design mechanics
  • Write a summary on the evaluation findings
  • Develop mini-game prototypes on Unity or Unreal

Student qualifications required:

  • This project is most suitable for 3rd or 4th-year students in the game development program. 
  • Candidates need to know Unity or Unreal 
  • Candidates should have completed the Games User Research course (INFR 3350)

Expected training/skills to be received by the Student: 

  • Gain more practical experiences with Unity/Unreal
  • Apply user research methods on real games

Length of award: 16 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Pooria Madani

Project title: Security of Federated Learning Systems

Summary of research project: This student project aims to create a cloud-based federated learning system with a user-friendly web dashboard, API integration, and a Python programming framework. Key features include a real-time monitoring dashboard, secure APIs for data and model transmission, cloud hosting for scalable machine learning models, and a Python framework for developing and testing algorithms. Emphasizing security and privacy, the system will efficiently manage distributed data sources and learning models, showcasing federated learning's potential in cloud environments.

Student responsibilities/tasks:

  • The student's responsibilities include developing a Python-based machine learning framework for federated learning, hosting and managing diverse learning models on a web service, and creating an online dashboard using Python, HTML, and JavaScript for real-time visualization and management of the federated learning system's performance, ensuring ease of use, scalability, and data security.

Student qualifications required:

  • Strong web application development skills and expertise in Python programming are essential. 
  • Additionally, high grades in database systems and computer security courses are a plus.

Expected training/skills to be received by the Student:

  • Learning about Federating Learning Systems.
  • Learning about design and development of cloud-base infrastructure for machine learning models to interact with.

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Salma Karray

Project title: Understanding consumer engagement on social media

Summary of research project: This research project aims to explore consumer engagement in social media campaigns. As a Research Assistant, you will have the chance to contribute to cutting-edge research and gain valuable insights into the world of digital marketing.

Student responsibilities/tasks:

  • Conducting literature reviews to gather relevant research materials.
  • Collecting and analyzing data related to digital marketing trends.
  • Collaborating with the research team to brainstorm ideas and insights.
  • Assisting in the preparation of research reports and presentations.

Student qualifications required:

  • Completed the equivalent of 2 years of undergraduate Commerce program
  • Have taken at least two courses in Marketing
  • Possesses the following qualities:
    • Enthusiasm for digital marketing
    • Excellent research and analytical skills
    • Strong attention to detail and the ability to work independently and in teams
    • Effective communication

Expected training/skills to be received by the Student:

  • Conducting literature reviews to gather relevant research materials.
  • Collecting and analyzing data related to digital marketing trends.
  • Assisting in the preparation of research reports and presentations.
  • Collaborating with the research team to brainstorm ideas and insights

Length of award: 14 Weeks

Location of award: Hybrid

Available Award: Ontario Tech STAR

 

Supervisor name: Shahram Shah Heydari

Project title: P4-Based Programmable Networks 

Summary of research project: The main objective of this research project is to investigate the usability and performance of programmable and protocol-independent packet processing using P4 language, a new concept for implementing network functions in software-defined and programmable networks. This research will include: setting up a development environment for programmable networks; deploy and compare the performance of various network functions such as congestion control, load balancing, network slicing and security attack mitigation in a programmable network vis-Ã-vis traditional network functions; and provide insights into the potential usage of this technology for implementing novel network functions.

Student responsibilities/tasks:

  • Design and implementation of a development/emulation environment for programmable networks, focusing on P4 as the starting point.
  • Researching and/or developing P4 software modules for various network functions.
  • Test P4 network functions on a P4-enabled hardware switch (subject to availability)
  • Preparing reports and presentations with regard to project activities

Student qualifications required:

  • Student in the Bachelor of Information Technology, Bachelor of Computer Science, or Bachelor of software Engineering (2nd year and up preferred).
  • Experienced in programming, Linux operating system and networking (either through coursework or hands-on experience).
  • Motivated, self-directed, and passionate about new technologies.

Expected training/skills to be received by the Student:

  • P4 Network Programming Language.
  • Software-Defined Networking.
  • Linux System Development and Integration.
  • Project Management.

Length of award: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR

 

Supervisor name: Steve Marsh

Project title: Evaluation of Communication Protocols for the EV Charging Infrastructure

Summary of research project: Over the last few years, there has been a tremendous growth in the adoption of electric vehicles and the deployment of charging infrastructure. In parallel, the number of vulnerabilities in this infrastructure and electric vehicle has been increasing exponentially, necessitating a strong adoption of how security testing is performed.  The objective of this project is to perform and threat analysis on the communication protocol that connects an electric vehicle to the charging infrastructure. The growth of electric vehicle adoption is bringing an increased demand for electric vehicles.

Student responsibilities/tasks:

  • Liaising with team, coding and design, statistical analysis.

Student qualifications required:

  • Finished 3rd year, NITS.

Expected training/skills to be received by the Student:

  • Study design.
  • Infrastructure awareness.
  • Risk analysis.
  • Information security.

Length of award: 16 Weeks

Location of award: In-Person

Available Award: NSERC USRA or Ontario Tech STAR