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Faculty of Business and Information Technology Project Summaries

Supervisors  

Amirali Abari | Amir Rastpour

 

Supervisor name: Amirali Abari

Project title: Graph Neural Networks for Recommender Systems

Summary of research project: Recommender systems are prevalent in our day-to-day lives. They intelligently recommend desirable options to us (e.g., books on Amazon, movies on Netflix), which are consistent with our own tastes or preferences. Several recent developments have been made in applying deep learning in recommender systems. A promising direction is to utilize graph embedding and graph convolutional networks, empowering recommender systems with graph-structured side information (e.g., social networks). Our goal is to develop practical 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 will also be heavily involved in the development of the AI technologies and will co-author the consequent paper written from their involvement in this Project.
  • This Project provides a unique opportunity for the candidate to foster their 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: 14 Weeks

Location of award: In-Person

Available Award: NSERC USRA

 

Supervisor name: Amir Rastpour

Project title: A Learning Game for Understand Hypothesis Testing!

Summary of research project: Experience shows that hypothesis testing is one of the most challenging concepts for students because of its abstract nature. This project will develop an educational game that makes hypothesis testing more intuitive through a familiar scenario: a group of students living together uses dice to decide who cleans the house. By analyzing the history of dice outcomes, players determine whether the dice are fair or biased. The game structure has already been designed; this undergraduate project will focus on implementing and refining the game.

Student responsibilities/tasks:

  • The Student will implement and refine the existing game design.
  • Tasks will include developing the game mechanics, implementing dice rolls and hypothesis-testing activities, designing the user interface and narrative, testing and debugging the game, and gathering feedback from undergraduate students.
  • The Student will also document the implementation, gameplay, and educational objectives.

Student qualifications required:

  • Introductory programming and statistics courses completed.
  • Basic knowledge of probability and hypothesis testing.
  • Programming experience in Python, R, C#, or similar.
  • Problem-solving and debugging skills.
  • Interest in educational technology and game development.
  • Ability to work independently and incorporate feedback.

Expected training/skills to be received by the Student:

  • Gain hands-on experience in game development, programming, and implementing an interactive educational.
  • Apply statistical concepts, especially hypothesis testing, to develop meaningful game mechanics.
  • Develop skills in software testing, debugging, and improving game design based on user feedback.
  • Learn to document a software project and communicate technical and educational outcomes.
  • Gain experience designing technology to support student learning and engagement.

Length of award: 14 Weeks

Location of award: Remote

Available Award: NSERC USRA