Welcome to Kaiyi Ji's Homepage

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About Me

I am an assistant professor at the Department of Computer Science and Engineering of the University at Buffalo, The State University of New York. I received my Ph.D. degree from the Electrical and Computer Engineering Department of The Ohio State University in December, 2021, advised by Prof. Yingbin Liang. I was a postdoctoral research fellow at the Electrical Engineering and Computer Science Department of the University of Michigan, Ann Arbor, in 2022, working with Prof. Lei Ying. I was a visiting student research collaborator at the department of Electrical Engineering, Princeton University. Previously I obtained my B.S. degree from University of Science and Technology of China in 2016.

Prospective students: I am now looking for PhD and Intern students with rich math and coding experiences in LLMs (optimization, alignment, prompt tuning, etc). Please send me an email with your CV and Transcript.

Research

My current research interests include:

  • Large-scale optimization: bilevel optimization, multi-objective optimization, and optimization for LLMs.

  • Machine Learning and deep learning: multi-task learning, model merging, continual learning and AI4Science

  • Foundation models: progressive prompts, parameter-efficient fine-tuning, multi-objective RLHF

Recent News!

  • [Talk] 03/2025 I will organize a special session entitled “Recent advances in optimization for machine learning and networking” at Asilomar 2025. Please join us if you attend Asilomar at CA.

  • [Manuscript] 02/2025 A new MTL paper is out! We introduce a scalable loss balancing approach for multi-task learning with O(1) time and memory cost, achieving superior accuracy and efficiency. Check out the code GitHub. Please star us if you find it useful!

  • [Services] 12/2024 Couple of upcoming services include NSF panelist, TPC member for ACM Mobihoc 2025 and TPC member for IEEE Information Theory Workshops (ITW’25).

  • [Talk] 12/2024 I gave a talk on bilevel optimization for machine learning at the Computer Science Seminar Series at Johns Hopkins University. Thanks for the invitation!

  • [Talk] 10/2024 I'll be giving a talk at the INFORMS Annual Meeting in Seattle from October 20-23. Love to connect if you are also attending.

  • [Software] 09/2024 Our FairGrad for multi-task/objective learning is now supported by open-source MTL Library LibMTL. Feel free to explore it and see if it can benefit your research!

  • [Job] 05/2024 Peiyao starts his internship at Amazon working on multi-objective optimization for recommendation.

  • [Award] 12/2023 Glad to receive CSE Junior Faculty Research Award from UB CSE. Thanks to the department and my students!

Continual Learning
Multi-Objective/Task Learning
Bilevel Optimization: Theory and Applications
Distributed Learning over Networks