Hi! I am a third-year Ph.D. student in the College of Computing and Data Science (CCDS) at Nanyang Technological University (NTU), supervised by Prof. Jie Zhang and Prof. Zhiguang Cao. I am currently conducting research at MIT’s Laboratory for Information and Decision Systems (LIDS), mentored by Prof. Cathy Wu. Previously, I received my M.Eng. degree from Sun Yat-Sen University (SYSU) in 2023, advised by Prof. Jiahai Wang, and received my B.Sc. degree from SYSU in 2020.

I’m on the job market! Please contact me if you know of any suitable positions!

Research

My research focuses on AI for Optimization, specifically developing autonomous solutions for complex optimization problems and decision-making challenges, including feasibility handling, generalization and interpretability. Recently, I am exploring the integration of LLMs and Agentic AI to build next-generation solvers for compelling application domains, such as routing, manufacturing, and robotics.

Research Keywords

• Machine Learning: Deep Reinforcement Learning, Deep Learning, LLM, Agentic AI, Foundation Model, Interpretability
• Optimization: Neural Combinatorial Optimization (NCO), Learning-guided Optimization (LGO), GPU-Accelerated Optimization
• Application: Routing, Scheduling, Manufacturing, Robotics

News

• [2026.09] Two papers were accepted by NeurIPS 2026: 1) Interpreting Neural Combinatorial Optimization via Evolving Programmatic Bottlenecks, and 2) Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty! Welcome to chat with me in Sydney!
• [2026.08] One paper was accepted by EMNLP 2026: FormuEvo: LLM-Guided Evolution for Discovering Solver-Efficient Mixed-Integer Programming Formulations!
• [2026.04] I gave a talk on “Constraint Handling in Neural Routing Solvers” to Eindhoven University of Technology.
• [2026.02] I’m excited to present my recent work, ‘Efficient Constraint Handling in AI for Logistics’, at the annual MIT CEE Research Day on Feb 23rd!
• [2026.01] Two papers were accepted by ICLR 2026: 1) Towards Efficient Constraint Handling in Neural Solvers for Routing Problems, and 2) Generalizable Heuristic Generation Through LLMs with Meta-Optimization! Welcome to chat with me in Rio!
• [2025.11] I will conduct research exchange at MIT’s Laboratory for Information and Decision Systems (LIDS), supervised by Prof. Cathy Wu.
• [2025.10] I am selected as NeurIPS 2025 Top Reviewer (10%)!
• [2025.09] I gave a talk on “Constraint Handling in Learning-to-optimize: Progress and Future” to LEAD 2025.
• [2025.05] I gave a talk on “Neural Combinatorial Optimization: Challenges and Applications” to MINIEYE.
• [2025.05] My collaborated benchmark library “RL4CO: An Extensive Reinforcement Learning for Combinatorial Optimization Benchmark” got accepted by KDD (Oral) 2025!
• [2025.04] Pass Ph.D. Qualifying Examination!
• [2024.10] I am selected as NeurIPS 2024 Top Reviewer (10%) for both main and DB track!
• [2024.09] My first-authored paper “Learning to Handle Complex Constraints for Vehicle Routing Problems” was accepted by NeurIPS 2024!
• [2024.01] Start my Ph.D. journey at CCDS, NTU!
• [2023.06] Graduate as Outstanding Graduate from SYSU!
• [2022.09] My first-authored paper “Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation” was accepted by NeurIPS 2022!
• [2020.09] Start my M.Eng. journey at SYSU, majoring in Software Engineering!
• [2020.06] Graduate as Outstanding Graduate from SYSU!