Lisha Chen

Assistant Professor
Department of Electrical and Computer Engineering
Goergen Insitute for Data Science and Artificial Intelligence
University of Rochester

Office: 624, Computer Studies Building
120 Trustee Rd, Rochester, NY, 14620
E-mail: lishachen9577 [AT] gmail.com (preferred);
lisha.chen [AT] rochester.edu

           

About me

I am an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Rochester. I did my Ph.D. at Rensselaer Polytechnic Institute (RPI), fortunate to be advised by Prof. Tianyi Chen (now at Cornell). I obtained my M.S. in Electrical Engineering from RPI in 2021, and my B.S. from Huazhong University of Science and Technology (HUST) in 2017.

My research lies at the intersection of machine learning, optimization, and statistical signal/image processing, with a current focus on the theory and applications of multi-objective and multi-level optimization and learning. Motivated by real-world scientific and engineering systems, I develop foundations to address problems involving competing objectives, resource constraints, multiple data modalities, heterogeneous users and devices, and hierarchical decision-making under uncertain environments. I aim to connect theoretical insights with practical needs.

I am always looking for highly motivated students and postdocs. If you are interested, please check out more details here.

News

  • Nov 2026: I will give a talk at the University of Illinois Urbana-Champaign (UIUC) Machine Learning Seminar. Looking forward to connecting and engaging in discussions!

  • Oct 2026: I will attend Asilomar 2026 at Pacific Grove, CA. Looking forward to meeting old and new friends there.

  • Sep 2026: Our paper on uniform coverage of the Pareto front is accepted by NeurIPS 2026. Congrats to Liuyuan Jiang and Chentong Huang! We will present this work in Atlanta, GA, this December.
    SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front
    Preliminary slides Code

  • Sep 2026: Happy to give a talk at OSU ECE department seminar on our recent works for preference-guided multi-objective learning.

  • Aug 2026: I will present a tutorial at NeurIPS 2026. More information will be available soon.

  • Jul 2026: Two papers accepted by Asilomar 2026. Congrats to Chentong Huang and all other collaborators!

  • Mar 2025: I have successfully defended my thesis. Sincere thanks to my committee members for their guidance and support.

  • Oct 2024: Honored and grateful to receive the IEEE Signal Processing Society (SPS) scholarship.

  • Jul 2024: I co-organize a special session on "Advances in Optimization for Machine Learning and Signal Processing" at IEEE SAM 2024 Workshop with Prof. Tianyi Chen and Prof. Kaiyi Ji.

  • Apr 2024: I present a tutorial at ICASSP 2024 together with Prof. Tianyi Chen and Dr. Xiaodong Cui.

  • Feb 2024: I present a tutorial at AAAI 2024 together with Prof. Tianyi Chen and Prof. Zhuoran Yang.

  • Feb 2024: I am invited to give a talk at the University of Rochester ECE department seminar.

  • Dec 2023: Our paper is accepted by ICASSP 2024.
    Variance Reduction Can Improve Trade-off in Multi-Objective Learning

  • Oct 2023: I am honored to receive the Rensselaer's Founders Award of Excellence.

  • Feb 2023: I am honored to be selected as Top Reviewer for AISTATS 2023.