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Table of Contents
S25 Project Listings
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LLM4SE (Large Language Models for Software Engineering)
[added 2025-04-11]
Course: {EECS4070 | EECS4080}
Supervisor: Zhen Ming (Jack) Jiang
Supervisor's email address: zmjiang@yorku.ca
Project Description: Software engineering data (e.g., source code repositories and bug databases) contain a wealth of information about a project's status and history. With the recent advances of large language models (e.g., GPT and BERT) as well as their applications (e.g., ChatGPT or GitHub Copilot), many software engineering tasks can be automated or optimized. In this project, the student(s) will explore and investigate various software engineering applications which can benefit from the use of LLMs.
Required skills or prerequisites:
- Major in Computer Science/Software Engineering/Computer Engineering
- Third year and up
- At least B+ for EECS 3311
- Proficient in Python and Java-based programming
Recommended skills or prerequisites: Some knowledge in AI would be preferred but not required
Instructions: Send c.v. and unofficial transcript to the supervisor.
FMOps
[added 2025-04-11]
Course: {EECS4070 | EECS4080}
Supervisor: Zhen Ming (Jack) Jiang
Supervisor's email address: zmjiang@yorku.ca
Project Description: Artificial Intelligence is gaining rapid popularity in both research and practice, due to the recent advances in machine learning (ML) research and development. Many ML applications (e.g., Tesla’s autonomous vehicle and Apple’s Siri) are already being used widely in people’s everyday lives. McKinsey recently estimated that ML applications have the potential to create between $3.5 and $5.8 trillion in value annually. Foundation models are large AI models trained on a vast quantity of data at scale. FMs can be used to power a wide range of downstream tasks (e.g., chat bots, code assistants, tutors, etc.). However, there remain many challenges in efficiently training, deploying and monitoring such FM infrastructure. In addition, there is a lack of tools and processes to further develop applications or services on top of such FMs. The goal of this project is to develop engineering tools and best practices to support effectively operationalizing FMs.
Required skills or prerequisites:
- Major in Computer Science/Software Engineering/Computer Engineering
- Third year and up
- At least B+ for EECS 3311
- Proficient in Python and Java-based programming
Recommended skills or prerequisites: Some knowledge in AI would be preferred but not required
Instructions: Send c.v. and unofficial transcript to the supervisor.
AI Safety and AI Alignment
[added 2025-04-11]
Course: { EECS4080 | EECS4070}
Supervisor: Laleh Seyyed-Kalantari
Supervisor's email address: lsk@yorku.ca
Topics of Interest:
- AI safety and AI alignment.
- Evaluating disparity in care in large GEMINI dataset.
Required skills or prerequisite courses:
- You must have completed a Machine Learning course. Total GPA over B+ (Preferably A/A+)
Recommended skills or prerequisite courses:
- A Deep Learning course is strongly preferred.
Instructions: Please fill this form and email me same materials if you are interested: https://docs.google.com/forms/d/e/1FAIpQLSfI_nBfwLKykI0W62J_LJEez-gDrwDxFiSg4RTwNw438v9U1Q/viewform
Computer Architecture & Other Topics
[added 2025-04-11]
Course: { EECS4080 | EECS4480}
Supervisor: Anirudh M Kaushik
Supervisor's email address: kaushika@yorku.ca
Topics of Interest: Computer architecture, embedded systems, compilers, electronic design automation tools, databases, software analysis
Instructions: Please email the professor.
Wearable Biomedical Devices
[added 2025-04-11]
Course: {EECS4080 | EECS4070}
Supervisor: Razieh Salahandish
Supervisor's email address: raziehs@yorku.ca
Instructions: Please email the professor.
AI-Assisted Biomedical Devices
[added 2025-04-11]
Course: {EECS4080 | EEC4070}
Supervisor: Razieh Salahandish
Supervisor's email address: raziehs@yorku.ca
Instructions: Please email the professor.
Image processing for Software Engineering
[added 2025-04-16]
Course: {EECS4080}
Supervisor: Maleknaz Nayebi
Supervisor's email address: mnayebi@yorku.ca
Required skills or prerequisites:
- Proficient in Python programming
Recommended skills or prerequisites: Understanding of Machine Learning and Image Processing
Instructions: Please email your CV and Transcripts to the professor.
Using Generative AI for Compliance Analysis in Health Care
[added 2025-04-16]
Course: {EECS4080}
Supervisor: Maleknaz Nayebi
Supervisor's email address: mnayebi@yorku.ca
Required skills or prerequisites:
- Proficient in Python programming
Recommended skills or prerequisites: Understanding of Machine Learning and Image Processing
Instructions: Please email your CV and Transcripts to the professor.