Scholar
Zhiguang Cao
Google Scholar ID: 2R-cOkYAAAAJ
Singapore Management University
Learning to Optimize
Neural Combinatorial Optimization
Computational Intelligence
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Citations & Impact
All-time
Citations
6,569
H-index
40
i10-index
78
Publications
20
Co-authors
20
list available
Contact
Email
zhiguangcao@outlook.com
GitHub
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Publications
30 items
PyVRP$^+$: LLM-Driven Metacognitive Heuristic Evolution for Hybrid Genetic Search in Vehicle Routing Problems
2026
Cited
0
RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
2026
Cited
0
Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling
2026
Cited
0
RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
2026
Cited
0
Chain-of-Context Learning: Dynamic Constraint Understanding for Multi-Task VRPs
2026
Cited
0
Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
2026
Cited
0
READY: Reward Discovery for Meta-Black-Box Optimization
2026
Cited
0
DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimization
arXiv.org · 2026
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Resume (English only)
Academic Achievements
Named in Stanford University’s 'World’s Top 2% Scientists' list in 2024
Published numerous papers on L2Opt at top-tier conferences including NeurIPS, ICML, SIGKDD, IJCAI, AAAI, ICLR, ACM MM, and TheWebConf
Published multiple journal papers on L2Opt in TKDE, IEEE TII, T-ASE, CAOR, IJPR, JCLP, Neural Networks, TELO, and IJPE
Serving as Area Chair or Senior Program Committee member for major conferences: NeurIPS'25, ICML'25, SIGKDD'25/26, ICLR'26, AAAI'26, IJCAI'25
Associate Editor for IEEE Transactions on Industrial Informatics (TII)
Delivered a keynote talk at the ECML PKDD workshop in September 2025
Background
Assistant Professor at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU)
Leading the L2Opt Group focusing on Learning to Optimize (L2Opt)
Research interests include Deep Reinforcement Learning, Deep Learning, and Large Language Models (LLM)
Explores AI-driven solutions to combinatorial optimization problems such as Vehicle Routing, Job Shop Scheduling, and Bin Packing
Works at the intersection of Artificial Intelligence and Operations Research with applications in logistics, transportation, and robotics
Co-authors
20 total
Wen Song
Shandong University
Jie Zhang
Professor of Computer Science, Nanyang Technological University
Yaoxin Wu
Eindhoven University of Technology
Hongliang Guo
四川大学计算机学院
Yining Ma
Postdoctoral Associate, MIT
ZHENGHUA CHEN
Senior Lecturer (Associate Professor) at University of Glasgow, UK
Le Zhang(张乐)
Professor, University of Electronic Science and Technology of China
Yue-Jiao Gong (龚月姣)
South China University of Technology
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