About Me

I am currently pursuing my Bachelor’s degree at Shanghai University of Finance and Economics (2021.9 - 2025.6), specializing in the Interdisciplinary Science Experimental Class.

My coursework includes Optimization, Operations Management, Algorithm Design, and Machine Learning.

📚 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 framework 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
Hongpei Li, Ziyan He, Yufei Wang, Wenting Tu, Shanwen Pu, Qi Deng, Dongdong Ge (2025). BenLOC: A Benchmark for Learning to Configure MIP Optimizers. arXiv.
Cite DOI URL
Huikang Liu, Yicheng Huang, Hongpei Li, Dongdong Ge, Yinyu Ye (2025). PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation. arXiv.
Cite DOI URL
Yicheng Huang, Wanyu Zhang, Hongpei Li, Dongdong Ge, Huikang Liu, Yinyu Ye (2024). Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming. arXiv.
Cite URL
Hongpei Li, Han Zhang, Ziyan He, Yunkai Jia, Bo Jiang, Xiang Huang, Dongdong Ge (2024). Solving Integrated Process Planning and Scheduling Problem via Graph Neural Network Based Deep Reinforcement Learning. arXiv.
Cite DOI URL