Quan Xiao
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Ph.D. student in |
About me
I am currently a PhD student at the Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, and am fortunately advised by Prof. Tianyi Chen. Prior to that, I was a visiting student at Data and Computer Science Department of Sun Yat-Sen University during 2020-2021, hosted by Prof. Qing Ling. Previously, I obtained my B.S. degree of Statistics from University of Science and Technology of China in 2020.
Research interests: my work focuses on optimization, particularly bilevel optimization, aiming to develop provably efficient algorithms to drive the generative AI models and in-memory computing.
Education
University of Science and Technology of China, Hefei, China: B.S., Statistics, 2016.9 - 2020.7
Rensselaer Polytechnic Institute, Troy, NY, USA: Ph.D., Electrical, Computer, and Systems Engineering, 2021.9 -
Recent news
Oct 2024: I'll present our recent work on global convergence in bilevel optimization at the Asilomar Conference on Signals, Systems, and Computers and serve as a session co-chair. For a deeper dive, check out the paper: Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
Oct 2024: Our paper on optimization foundation for pipeline analog training is now available. Pipeline Gradient-based Model Training on Analog In-memory Accelerators
Sep 2024: I'm grateful to receive the IEEE Signal Processing Society Scholarship
Sep 2024: Our paper on coupled constrained bilevel optimization was accepted by NeurIPS 2024
A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
Sep 2024: Our paper on global optimality for bilevel optimization is available. Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
Aug 2024: Our paper A Bilevel Optimization Method for Inverse Mean-Field Games is accepted by Inverse Problems.
June 2024: Our paper on bilevel optimization with coupled constraints is available. A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
May 2024: I will join IBM Research as a visiting scholar this summer, under the mentorship of Dr. Debarun Bhattacharjya and managed by Dr. Dharmashankar Subramanian.
Jan 2024: Our paper is available: A Bilevel Optimization Method for Inverse Mean-Field Games
Dec 2023: I'm grateful to receive the Belsky Award for Computational Sciences and Engineering in RPI
Sep 2023: Our paper was accepted by NeurIPS 2023
A Generalized Alternating Method for Bilevel Learning under the Polyak-Lojasiewicz Condition
Sep 2023: Our paper was accepted by IEEE Transactions on Signal Processing
Lazy Queries Can Reduce Variance in Zeroth-order Optimization
May 2023: I will attend the SIAM Conference on Optimization (OP23) to present our work on bilevel optimization with nonconvex lower-level problem. Check out the paper:
A Generalized Alternating Method for Bilevel Learning under the Polyak-Lojasiewicz Condition
Jan 2023: A short version of our paper on equality-constrained bilevel optimization and its application on federated bilevel learning was accepted by AISTATS 2023
Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization
May 2022: Our paper was accepted by ICML 2022
Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning
May 2022: I will join IBM Research as a research extern this summer, under the mentorship of Dr. Songtao Lu and managed by Dr. Lior Horesh
Jan 2022: Our paper was accepted by ICASSP 2022
Federated Multi-armed Bandit via Uncoordinated Exploration
Jan 2022: Our paper was accepted by AISTATS 2022 (Oral, top 2% of all submissions).
A Single-Timescale Method for Stochastic Bilevel Optimization