About Me
I am a first-year PhD student in the Department of Industrial Engineering & Management Sciences (IEMS) at Northwestern University.
I received my Bachelor’s degree from Shanghai University of Finance and Economics (September 2021 – June 2025), where I was advised by Prof. Yinyu Ye and Prof. Dongdong Ge.
📚 My Research
My research interests include Optimization, Artificial Intelligence (AI), and the interdisciplinary area between Operations Research and Machine Learning.
Currently, I am particularly focused on:
- Developing optimization-based algorithmic frameworks to enhance the training and inference efficiency of large language models (LLMs)
- Accelerating classical optimization methods by leveraging AI techniques that learn from historical data
- Designing and implementing efficient optimization algorithms for large-scale problems, with a particular focus on GPU-accelerated methods
Recent Publications
(2026).
GPU-Accelerated Conic Quadratic Programming with Local Linear Convergence under Strict Complementarity.
arXiv.
(2026).
A Curvature-Aware Rank-Adaptive Distributed Augmented-Lagrangian Solver for Large-Scale SDPs.
arXiv.
(2026).
PDHCG-II: An Enhanced Version of PDHCG for Large-Scale Convex QP.
arXiv.
(2026).
D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems.
arXiv.