About Me
Hi, I am currently a researcher at College of Computing and Data Science, Nanyang Technological University (NTU), working in collaboration with Prof. Jie Zhang. I obtained my Ph.D. degree in Industrial Systems Engineering at National University of Singapore (NUS), in March 2024, where I am honored to be advised by Prof. Yeow Meng Chee. I received my B.E. degree from School of Computer Science and Engineering, South China University of Technology (SCUT), in June 2019, supervised by Prof. Yuejiao Gong. I have also collaborated closely with Prof. Zhiguang Cao from Singapore Management University (SMU).
I am working at the intersection of Machine Learning (ML) and Optimization, striving to develop automated ML solutions to address complex optimization challenges. My research has been featured in top-tier conferences and journals, including NeurIPS, ICLR, IJCAI, TNNLS, TCYB, SMCA, TITS, etc. I have served as an Area Chair for the IEEE CAI conference and a Reviewer/PC Member for top-tier conferences such as ICML, NeurIPS, ICLR, etc, along with prestigious journals such as TNNLS, TCYB, TITS, TASE, TRPE, etc.
Welcome to see my publications, academic services, experience, and honors & awards, and welcome to reach out for collaboration! You may approach me at:
- E-mail: yiningma [at] u [dot] nus [dot] edu
- Phone: +65 8291 7017
💡 Research Interests
My research has primarily focused on the emerging field of “Learning to Optimize (L2Opt)”, where the latest ML techniques (e.g., reinforcement learning, deep learning, large language models, etc) are exploited to develop state-of-the-art ML-powered frameworks/approaches for addressing challenging optimization problems (e.g., combinatorial optimization, black-box optimization, multi-objective optimization, etc). My research in L2Opt spans various ML perspectives, such as representation learning, foundational model development, efficient training/inference framework design, out-of-distribution generalization, multi-agent coordination, decision-making in dynamic environments, etc.
Research Keywords
- Machine Learning: Reinforcement Learning, Deep Learning, Large Language Model (LLM), Federated/Distributed Learning, Multi-Agent Systems
- Optimization: Combinatorial Optimization, Black-Box Optimization
- Application: Routing, Planning, Logistics, Transportation, Autonomous Vehicles
⚡ News
- [03/2024] One paper on MARL got accepted by TNNLS, where we introduced DOMAC for opponent modelling in multi-agent systems using only local information.
- [03/2024] Joined the open-source organization - AI4CO.
- [03/2024] One paper on L2Opt got accepted by SMCA, where we introduced RL-DAS for dynamic algorithm selection based on deep reinforcement learning.
- [02/2024] Gave a talk at MIT, hosted by Prof. Cathy Wu.
- [02/2024] Successfully defended my PhD thesis at NUS!