About Me

I am on the job market looking for Research Scientist and Machine Learning Researcher/Engineer position.

I obtained the Ph.D. in Dec. 2023, under the supervision of Prof. Ping Wang, in the Dept. EECS, York University, Canada. The thesis is about handling federated learning challenges in heterogeneous networks.

I have finished two industrial internships during my Ph.D., where I worked as a research engineer in Sony R&D, Tokyo, and an associate researcher in Noah Ark’s Lab, Montreal Research Centre, Montreal, focusing on applying federated learning to auto-driving systems (applicable), and personalization use-case (theoretical), respectively.

My research interests are in machine learning, optimization, and distributed systems. Specifically, I am interested in

• Designing theoretical frameworks for distributed/federated learning (FL) systems
• Leveraging foundation model for privacy-preserving ML use cases
• Integrating GenAI with FL systems for better robustness and adaptability

Updates:

• Dec 2023: I have defended my Ph.D. thesis.

• Nov 2023: Paper titled “Straggler-resilient Federated Learning: Tackling Computation Heterogeneity with Layer-wise Partial Model Training in Mobile Edge Network” has been submitted to IEEE Transactions Mobile Computing.

• August 2023: I have finished my summer internship at Sony R&D, Tokyo, Japan. Thanks Mr. Shinya Maruyama and Mr. Masanobu Jimbo for hosting me. Such a wonderful experience living in Tokyo!

• March 2023: I have finished my coop in Noah Ark’s Lab, Montreal Research Centre, Montreal. Thanks Dr. Guojun Zhang and Dr. Xi (Alex) Chen for hosting me.