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Xijun Li

Principle research engineer of HUAWEI Noah’s Ark Lab


xijun.li@huawei.com, xijunli@miralab.ai

Interests

  • Learning to Optimization (L2O)
  • Machine Learning for Computer Systems (ML4CS)

Education

  • M.Sc., Computer Software Engineering, 2018

    Shanghai Jiao Tong University

  • B.S., Applied Mathematics, 2015

    South China University of Technology

About me

Xijun has received his Ph.D. degree from the University of Science and Technology of China (HUAWEI-USTC Joint Ph.D. Program). Before that, he received his master degree from Shanghai Jiao Tong University, PR China, in 2018. Currently, he is a principle researcher of HUAWEI Noah’s Ark Lab. He has published several papers on top peer-reviewed conferences and journals (SIGMOD, KDD, ICDE, DAC, CIKM, ICDCS, TCYB, etc.). He has also been committee member of MDM 2021 Industry Track and reviewer of multiple top journals and conferences (TKDE, AAAI, ICDE, CIKM, etc.). Moreover, his research interests focus on learning to optimize combinatorial optimization problem and machine learning for computer systems.

Awards

  • National Scholarship, Sep 2014, Chinese Ministry of Education
  • National Scholarship, Sep 2017, Chinese Ministry of Education
  • Skyworth Enterprise Scholarship, First Prize, Jun 2015, Skyworth Enterprise
  • Mathematical Contest in Modeling (MCM), Meritorious Award, Mar 2014, Consortium for Mathematics and Its Applications, COMAP
  • Innovation Pioneer Award, Second Prize, Dec 2020, 2012 Labs, Huawei Technologies

Experience

  • Senior Research Engineer A, HUAWEI Noah’s Ark Lab, Mar 2022 – Present
  • Senior Research Engineer B, HUAWEI Noah’s Ark Lab, Dec 2019 – Present
  • Research Engineer, HUAWEI Noah’s Ark Lab, Apr 2018 – Nov 2019
  • Research Intern, HUAWEI Noah’s Ark Lab, Aug 2017 – Mar 2018

Publications

Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu, Jianye Hao, Feng Wu. Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph. ICML 2024.

Zhihai Wang, Lei Chen, Jie Wang, Yinqi Bai, Xing Li, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu. A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design. ICML 2024.

Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu. Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. TPAMI.

Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu. Rethinking Branching on Exact Combinatorial OPtimization Solver: The First Deep Symbolic Discovery Framework. ICLR 2024.

Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu. A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability (Spotlight). NeurIPS 2023.

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Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu. Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. ICLR 2023.

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Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lv, Jia Zen. Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. ICDE 2021.

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Yingtian Tang, Han Lu, Xijun Li, Lei Chen, Mingxuan Yuan, Jia Zeng. Learning-Aided Heuristics Design for Storage System. SIGMOD 2021.

Zhenkun Wang, Hui-Ling Zhen, Jingda Deng, Qingfu Zhang, Xijun Li, Mingxuan Yuan, Jia Zeng. Multiobjective Optimization-Aided Decision-Making System for Large-Scale Manufacturing Planning. IEEE Trans Cybern.

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Xijun Li, Jianguo Yao, Mingxuan Yuan, Jia Zeng. A Two-Layer Algorithmic Framework for Service Provider Configuration and Planning with Optimal Spatial Matching. CIKM 2018.

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Xijun Li, Jianguo Yao, Xue Liu, Haibing Guan. A First Look at Information Entropy-Based Data Pricing. ICDCS 2017.

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Xijun Li, Mingxuan Yuan, Di Chen, Jianguo Yao, Jia Zeng. A Data-Driven Three-Layer Algorithm for Split Delivery Vehicle Routing Problem with 3D Container Loading Constraint. KDD 2018.

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