About me

I am currently a third-year PhD student in SChool of Artificial Intelligence and Data Science at the University of Science and Technology of China (USTC). Previously, I received my Bachelor’s degree in Mathematics and Applied Mathematics in the School of the Gifted Young (SGY) at USTC in 2022. I am working towards my Ph.D. degree in the MIRA Lab at USTC, under the supervision of Prof. Jie Wang. My current research interests include Leanring to Optimize and AI4EDA. If you share similar interests or have any inquiries, please feel free to contact me by email.

Education

  • PhD. Candidate, SChool of Artificial Intelligence and Data Science, University of Science and Technology of China, 2024 -
  • M.S. Candidate, Electronic Engineering and Information Science, University of Science and Technology of China, 2022 - 2024
  • B.S., Mathematics and Applied Mathematics, School of the Gifted Young, University of Science and Technology of China, 2018 - 2022
  • High School, Xuzhou No. 1 Middle School, 2016 - 2018

Research

Publications

  1. Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu. “MILP-StuDio: MILP Instance Generation via Block Structure Decomposition.” NeurIPS 2024.
  2. Jian Luo, Jie Wang, Hong Wang, huanshuo dong, Zijie Geng, Hanzhu Chen, Yufei Kuang. “Neural Krylov Iteration for Accelerating Linear System Solving”. NeurIPS 2024 (Spotlight).
  3. Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Mingxuan Yuan, Jianye HAO, Yongdong Zhang, Feng Wu. “Reinforcement Learning within Tree Search for Fast Macro Placement.” ICML 2024. [paper]
  4. Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu. “Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling.” ICLR 2024 (Spotlight). [paper]
  5. Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu. “A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability.” NeurIPS 2023 (Spotlight). [paper] [project] [code]
  6. Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu. “De Novo Molecular Generation via Connection-aware Motif Mining.” ICLR 2023. [paper] [code]
  7. Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu. “Learning task-relevant representations for generalization via characteristic functions of reward sequence distributions.” SIGKDD 2022. [paper] [code]

Preprint

  1. Zhihai Wang*, Zijie Geng*, Zhaojie Tu*, Jie Wang, Yuxi Qian, Zhexuan Xu, Ziyan Liu, Siyuan Xu, Zhentao Tang, Shixiong Kai, Mingxuan Yuan, Jianye Hao, Bin Li, Yongdong Zhang, Feng Wu. “Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms.” [paper]
  2. Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao. “Machine Learning Insides OptVerse AI Solver: Design Principles and Applications.” [paper]
  3. Jie Wang, Zijie Geng, Xijun Li, Jianye Hao, Yongdong Zhang, Feng Wu. “G2MILP: Learning to Generate Mixed-Integer Linear Programming Instances for MILP Solvers.” [paper]
  4. Jie Wang, Rui Yang, Zijie Geng, Zhihao Shi, Mingxuan Ye, Qi Zhou, Shuiwang Ji, Bin Li, Yongdong Zhang, Feng Wu. “Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution.” [paper]

Services

  • Conference Reviewer: KDD 2023, NeurIPS 2023 (Top Reviewer), AAAI 2024, ICLR 2024, ICML 2024, NeurIPS 2024, AAAI 2025, ICLR 2025.

Awards

  • National Scholarship, 2024
  • MSRA Stars of Tomorrow, 2022
  • S.-T. Yau College Student Mathematics Contest (Analysis and Partial Differential Equations), Outstanding Prize, 2021
  • The Chinese Mathematics Competitions (CMC), First Price in Anhui Province, 2020
  • S.-T. Yau College Student Mathematics Contest (Applied and Computational Mathematics), Outstanding Prize, 2020

Experience