Principal Researcher @ Huawei Noah's Ark Lab E-mail: xijun.li@huawei.com (preferred) [Google Scholar] [Info@MIRA Lab] [Github] [Linkedin] |
[03-10-2024] The paper “Joint Directory, File and IO Trace Feature Extraction and Feature-based Trace Regeneration for Enterprise Storage Systems” is accepted by ICDE 2024. Congrats to Kecheng!
[02-29-2024] I successfully defended my doctoral thesis [pic]!
[01-16-2024] Two papers are accepted by ICLR 2024. The camera-ready version will be released soon!
[01-12-2024] We released a position paper “Machine Learning Insides OptVerse AI Solver: Design Principles and Applications”. Please stay tuned with OptVerse AI Solver!
[10-14-2023] I delivered a talk “天筹AI求解器及运筹优化落地实践” on AI4OR workshop at National Univesrity of Defense Technology.
[09-29-2023] I will serve as PC member for TheWebConf 2024.
[09-22-2023] The paper “A Deep Instance Generative Framework For MILP Solvers Under Limited Data Availability” has been accepted at NeurIPS 2023 as a spotlight! Congratulations!
[09-20-2023] I will serve as PC member for ICLR 2024.
[08-28-2022] Our intern Yufei has been arwarded Excellent Intern of Huawei Noah's Ark Lab (5 out of 400+ all interns)! Congratulations!
[07-16-2023] I will serve as PC member for AAAI 2024.
[07-07-2023] Our OptVerse AI Solver received WAIC SAIL Award 卓越人工智能引领者 and I gave a tutorial on behalf of our team! [pic1] [pic2]
[05-17-2023] The paper “HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline” is accepted by KDD 2023!
[05-13-2023] I delivered a talk “Order matters: Boosting Mathematical Programming Solver via Machine Learning Techniques” at the MOS2023 中国运筹学会.
[05-01-2023] We established a booth at ICLR 2023, presenting recent research progress in Noah's Ark Lab. Welcome on board! [pic1] [pic2] [pic3]
[03-06-2023] I delivered a talk “Order matters: Boosting Mathematical Programming Solver via Machine Learning Techniques” at the CUHKSZ 香港中文大学 (深圳) and SRIBD 深圳大数据研究院.
[02-24-2023] The paper “Layout Decomposition via Boolean Satisfiability” is accepted by DAC 2023!
[02-22-2023] My intern Yunfan has been arwarded Excellent Intern of Huawei Noah's Ark Lab (10 out of 800+ all interns).
[02-08-2023] Received the Presidential Individual Award from Huawei Supply Chain Management Department!
[01-22-2023] Two papers have been accepted by ICLR 2023 and congratulations to all co-authors!
[01-01-2023] Received the Presidential Individual Award from Huawei 2012 Labs!
[12-18-2022] The paper “Accelerating Linear Programming Solving by Exploiting the Performance Variability via Reinforcement Learning” is accepted by AAAI 2023 workshop on AI to Accelerate Science and Engineering!
[11-25-2022] The paper “Machine Learning Methods in Solving the Boolean Satisfiability Problem” is accepted by Machine Intelligence Research Journal!
[11-09-2022] The paper “A Survey for Solving Mixed Integer Programming via Machine Learning” is accepted by Neurocomputing Journal!
[10-06-2022] I served as Industry PC member for WWW 2023.
[09-28-2022] My intern Xiaotian has been arwarded Excellent Intern of Huawei Noah's Ark Lab (10 out of 800+ all interns)!
[09-19-2022] The paper “Satellite Observation and Data-Transmission Scheduling using Imitation Learning based on Mixed Integer Linear Programming” is accepted by IEEE Transactions on Aerospace and Electronic Systems. Congratulations to Qingyu and all co-authors!
[08-09-2022] I served as PC member for AAAI 2023.
[07-08-2022] I delivered a talk “Frontier of Learning to Optimization” at the CUHKSZ-HUAWEI Computing Mathematic Forum 港中深-华为计算数学论坛 and MIRA Lab Seminar of USTC 中国科学技术大学 MIRA Lab 学术讲座 [slides].
[05-07-2022] The paper “LQoCo: Learning to Optimize Cache Capacity Overloading in Storage Systems” is accepted by DAC 2022 and recognized by program committe as Publicity Paper with high market value!
[04-30-2022] The paper “Learning to Optimize DAG Scheduling in Heterogeneous Environment” is accepted by MDM 2022!
[02-15-2022] My intern Qingyu has been arwarded Excellent Intern of Huawei Noah's Ark Lab (10 out of 800+ all interns)!
[02-01-2022] I led a team (named qqy) to win the championship of student learderboard in Dual Track of NeurIPS 2021 ML4CO Competition. Check out the result [media] [solution]!
[01-05-2022] I passed the Ph.D. qualifying exam!
[03-01-2021] The paper “Learning-Aided Heuristics Design for Storage System” is accepted by SIGMOD 2021!
[02-16-2021] The paper “Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems” is accepted by ICDE 2021!
Xijun is a principal researcher of Huawei Noah’s Ark Lab. Before that, he has received master degree under the supervision of Prof. Jianguo Yao (the Dean of the School of Software) from Shanghai Jiao Tong University in 2018. He is working towards his Ph.D. degree in the University of Science and Technology of China (HUAWEI-USTC Joint Ph.D. Program) under the supervision of Prof. Jie Wang (the Vice Dean of the School of the Gifted Young). He has published many papers on top peer-reviewed conferences and journals (such as NeurIPS, ICLR, KDD, ICDE, SIGMOD, DAC, etc.) and applied/published 10+ patents with Huawei Noah's Ark Lab. He has also won the championship of student learderboard in Dual Track of NeurIPS’21 ML4CO Competition. His recent research interests focus on Mathematical Programming Solver, Learning to Optimization (L2O), and Large Language Model for Optimization/Reasoning. Last but not least, he is one of core developers of the Huawei Cloud OptVerse AI Solver.
Learning to Optimize
Large Language Model for Optimization/Reasoning
Mathematical Programming Solver
Neural Combinatorial Optimization
Machine Learning for Computer System
Reinforcement Learning
Operational Research
Meta-Heuristic Algorithms
Applications in Logistics, Supply Chain, Storage Systems, etc.
Kecheng Huang, Xijun Li, Mingxuan Yuan, Ji Zhang, Zili Shao: Joint Directory, File and IO Trace Feature Extraction and Feature-based Trace Regeneration for Enterprise Storage Systems. ICDE 2024 [coming soon]
Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, et al.: Machine Learning Insides OptVerse AI Solver: Design Principles and Applications [arxiv]
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 [pdf]
Chang Liu, Zhichen Dong, Haobo Ma, Weilin Luo, Xijun Li, Bowen Pang, Jia Zeng, Junchi Yan: L2P-MIP: Learning to Presolve for Mixed Integer Programming. ICLR 2024 [pdf]
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) [page] [pdf] [code]
Yang Li, Xinyan Chen, Wenxuan Guo, Xijun Li, Wanqian Luo, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Junchi Yan: HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline. KDD 2023 [pdf] [code]
Xijun Li, Qingyu Qu, Fangzhou Zhu, Jia Zeng, Mingxuan Yuan, Jie Wang: Accelerating Linear Programming Solving by Exploiting the Performance Variability via Reinforcement Learning. AAAI 2023 workshop on AI to Accelerate Science and Engineering [pdf] [poster] [slides] [video]
Xijun Li*, Zhihai Wang*, 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 [pdf] [slides] [code (MindSpore)] [code (PyTorch)] [media]
Han Lu, Zenan Li, Runzhong Wang, Qibing Ren, Xijun Li, Mingxuan Yuan, Jia Zeng, Xiaokang Yang, Junchi Yan: ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs. ICLR 2023 [pdf] [code]
Hongduo Liu, Peiyu Liao, Mengchuan Zou, Bowen Pang, Xijun Li, Mingxuan Yuan, Tsung-Yi Ho, Bei Yu: Layout Decomposition via Boolean Satisfiability. DAC 2023 [pdf] [slides]
Yiyuan Yang, Rongshang Li, Qiquan Shi, Xijun Li, Gang Hu, Xing Li, Mingxuan Yaun: SGDP: A Stream-Graph Neural Network Based Data Prefetcher. IJCNN 2023 [pdf] [code]
Wenxuan Guo, Hui-Ling Zhen, Xijun Li#, Mingxuan Yuan, Yaohui Jin, Junchi Yan: Machine Learning Methods in Solving the Boolean Satisfiability Problem. Machine Intelligence Research Journal [pdf]
Jiayi Zhang, Chang Liu, Xijun Li#, Hui-Ling Zhen, Junchi Yan, Mingxuan Yuan: A Survey for Solving Mixed Integer Programming via Machine Learning. Neurocomputing Journal [pdf]
Qingyu Qu, Kexin Liu, Xijun Li, Yunfan Zhou, Jinhu Lv: Satellite Observation and Data-Transmission Scheduling using Imitation Learning based on Mixed Integer Linear Programming. IEEE Transactions on Aerospace and Electronic Systems, TAES [pdf]
Ji Zhang, Xijun Li#, Xiyao Zhou, Mingxuan Yuan, Zhuo Cheng, Keji Huang, Yifan Li: L-QoCo: learning to optimize cache capacity overloading in storage systems. DAC 2022: 379-384 (CORE A, CCF A) [pdf]
Xijun Li*#, Yunfan Zhou*, Jinhong Luo, Mingxuan Yuan, Jia Zeng, Jianguo Yao: Learning to Optimize DAG Scheduling in Heterogeneous Environment. MDM 2022: 137-146 (CORE A, CCF C) [pdf] [video] [slides]
Qingyu Qu, Xijun Li#, Yunfan Zhou; Yordle: An Efficient Imitation Learning for Branch and Bound. NeurIPS 2021 ML4CO Competition [pdf]
Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lü, Jia Zeng: Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. ICDE 2021: 2511-2522 (CORE A, CCF A) [pdf] [slides]
Yingtian Tang, Han Lu, Xijun Li#, Lei Chen, Mingxuan Yuan, Jia Zeng: Learning-Aided Heuristics Design for Storage System. SIGMOD 2021: 2597-2601 (CORE A*, CCF A) [pdf] [video]
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 Transactions on Cybernetics 52(8): 8326-8339 (2022) (CORE A, CCF B) [pdf]
Hui-Ling Zhen, Zhenkun Wang, Xijun Li, Qingfu Zhang, Mingxuan Yuan, Jia Zeng; Accelerate the optimization of large-scale manufacturing planning using game theory. Complex & Intelligent Systems; 1-12 [pdf]
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: 528-536 (CORE A*, CCF A) [pdf] [video] [media]
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: 2273-2281 (CORE A, CCF B) [pdf]
Xijun Li, Jianguo Yao, Xue Liu, Haibing Guan: A First Look at Information Entropy-Based Data Pricing. ICDCS 2017: 2053-2060 (CORE A, CCF B) [pdf]
李希君, 上海, 上海交通大学: 基于信息熵的数据交易定价研究 [master thesis]
Machine Learning Insides OptVerse AI Solver: Design Principles and Applications [page]
Xijun Li, Qingyu Qu, Fangzhou Zhu, Jia Zeng, Mingxuan Yuan, Kun Mao, Jie Wang: Learning to Reformulate for Linear Programming. [arxiv]
Xijun Li*, Yunfan Zhou*, Ji Zhang: PASCAL - A Learning-aided Cooperative Bandwidth Control Policy for Hierarchical Storage Systems. [arxiv]
Jie Wang, Zijie Geng, Xijun Li, Jianye Hao, Yongdong Zhang, Feng Wu: G2MILP: Learning to Generate Mixed-Integer Linear Programming Instances for MILP Solvers [techrxiv]
Yufei Kuang, Xijun Li*, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu: Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning. [arxiv]
Yunfan Zhou*, Xijun Li*#, Qingyu Qu: Offline Reinforcement Learning with Adaptive Behavior Regularization. [arxiv]
Qingyu Qu, Xijun Li*, Yunfan Zhou, Jia Zeng, Mingxuan Yuan, Jie Wang, Jinhu Lv, Kexin Liu, Kun Mao: An Improved Reinforcement Learning Algorithm for Learning to Branch. [arxiv]
Zhihai Wang, Lei Chen, Jie Wang, Xing Li, Yinqi Bai, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu: A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design [arxiv]
Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu: Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. [arxiv]
Wenxuan Guo, Hui-Ling Zhen, Xijun Li, Mingxuan Yuan, Yaohui Jin, Junchi Yan: Machine Learning Methods in Solving the Boolean Satisfiability Problem. [arxiv]
Jiayi Zhang, Chang Liu, Xijun Li, Hui-Ling Zhen, Junchi Yan, Mingxuan Yuan: A Survey for Solving Mixed Integer Programming via Machine Learning. [arxiv]
Jianye Hao, Jiawen Lu, Xijun Li, Xialiang Tong, Xiang Xiang, Mingxuan Yuan, Hankz Hankui Zhuo: Introduction to The Dynamic Pickup and Delivery Problem Benchmark–ICAPS 2021 Competition. [arxiv]
Xinyan Chen, Wenxuan Guo, Yang Li, Wanqian Luo, Hui-Ling Zhen, Xijun Li, Mingxuan Yuan, Junchi Yan: Proceedings of SAT Competition 2022: Solver and Benchmark Descriptions [pdf] [link]
where ‘*’ indicates the equal contribution and ‘#’ stands for corresponding author.
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3rd Place, Parallel Track, SAT Competition 2023 [result] [solution]
1st Place, Student Learderboard in Dual Track, NeurIPS 2021 ML4CO Competition [result] [media] [solution]
Meritorious Award, Mathematical Contest in Modeling (MCM) 2014, Consortium for Mathematics and Its Applications [cerification]
“天筹AI求解器及运筹优化落地实践” on AI4OR workshop at National Univesrity of Defense Technology
“Order matters: Boosting Mathematical Programming Solver via Machine Learning Techniques” at the MOS2023 中国运筹学会 [slides (updated)]
“Order matters: Boosting Mathematical Programming Solver via Machine Learning Techniques” at the CUHKSZ 香港中文大学 (深圳) and SRIBD 深圳大数据研究院 [slides] [video]
“Frontier of Learning to Optimization” at the CUHKSZ-HUAWEI Computing Mathematic Forum 港中深-华为计算数学论坛 and MIRA Lab Seminar of USTC 中国科学技术大学 MIRA Lab 学术讲座 [slides]
Presidential Individual Award (总裁个人奖), Jan 2023, 2012 Labs, Huawei Technologies [cerification]
Presidential Individual Award (总裁个人奖), Jan 2023, Supply Chain Department, Huawei Technologies [cerification]
Battlefield Heroes Award (战地英雄奖), Nov 2022, 2012 Labs, Huawei Technologies [cerification]
Quality Star Award (质量之星奖), Dec 2021, 2012 Labs, Huawei Technologies [cerification]
Gold Medal Team Award (金牌团队奖), Dec 2020, 2012 Labs, Huawei Technologies [cerification1] [cerification2]
Innovation Pioneer Award (创新先锋奖), Dec 2020, 2012 Labs, Huawei Technologies [cerification]
Excellent New Employee (优秀新员工), Dec 2018, 2012 Labs, Huawei Technologies [cerification]
Outstanding Graduate, Jun 2018, Shanghai Jiao Tong University [cerification]
National Scholarship (国家奖学金 / top 5% out of all students), Sep 2017, Chinese Ministry of Education [cerification]
National Scholarship (国家奖学金 / top 5% out of all students), Sep 2014, Chinese Ministry of Education [cerification]
Skyworth Enterprise Scholarship (创维企业奖学金 / top 5%), First Prize, Jun 2015, Skyworth Enterprise [cerification]
Mathematical Contest in Modeling (MCM), Meritorious Award, Mar 2014, Consortium for Mathematics and Its Applications [cerification]
The AAAI 2024 Workshop on Artificial Intelligence for Operations Research
The ACM Web Conference 2024 (formerly known as International World Wide Web Conference, abbreviated as WWW)
The Twelfth International Conference on Learning Representations (ICLR) 2024
The AAAI Conference on Artificial Intelligence (AAAI) 2024
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS) 2023
The International Conference on Data Engineering (ICDE) 2023
The ACM Web Conference 2023 (formerly known as International World Wide Web Conference, abbreviated as WWW)
The AAAI Conference on Artificial Intelligence (AAAI) 2023
The International Conference on Data Engineering (ICDE) 2022
The IEEE International Conference on Mobile Data Management (MDM) 2021, Industry Track
The AAAI Conference on Artificial Intelligence (AAAI) 2021
The IEEE International Conference on Mobile Data Management (MDM) 2021
The AAAI Conference on Artificial Intelligence (AAAI) 2020
The ACM International Conference on Information and Knowledge Management (CIKM) 2020
The IEEE Transactions on Knowledge and Data Engineering
The IEEE Transactions on Emerging Topics in Computational Intelligence
Transportation Research Part E
Principal Researcher, Huawei Noah's Ark Lab, Mar 2024 – Present
Senior Research Engineer A, Huawei Noah's Ark Lab, Mar 2022 – Feb 2024
Senior Research Engineer B, Huawei Noah's Ark Lab, Dec 2019 – Feb 2022
Research Engineer, Huawei Noah's Ark Lab, Apr 2018 – Nov 2019
Research Intern, Huawei Noah's Ark Lab, Aug 2017 – Mar 2018
Ph.D., Electronic Engineering and Information Science, University of Science and Technology of China, 2019 Sep. - 2024 Mar.
M.Eng., Computer Software Engineering, Shanghai Jiao Tong University, 2015-2018
B.Sc., Applied Mathematics, South China University of Technology, 2011-2015
Dr. Weilin Luo (PhD graduated from Beihang University)
Yunfan Zhou (Msc student @ Chinese University of Hong Kong (Shenzhen), graduated from Peking University, Excellent Intern of Huawei Noah's Ark Lab of 2022H2) [cerification]
Qingyu Qu (PhD student @ Beihang University, Excellent Intern of Huawei Noah's Ark Lab of 2021H2) [cerification]
Xiaotian Hao (PhD student @ Tianjin University, Excellent Intern of Huawei Noah's Ark Lab of 2022H1) [cerification]
Yufei Kuang (PhD student @ University of Science and Technology of China, Excellent Intern of Huawei Noah's Ark Lab of 2023H1) [cerification]
Zhihai Wang (PhD student @ University of Science and Technology of China)
Yiyuan Yang (PhD student @ University of Oxford, graduated from Tsinghua University)
Kecheng Huang (PhD student @ Chinese University of Hong Kong, graduated from Shandong University)
Yingtian Tang (Msc student @ University of Pennsylvania, graduated from UESTC)
Zijie Geng (MPhil student @ University of Science and Technology of China)
It is pleased and appreciated to work with you guys!