James Arambam
Research Fellow,
School of Computer Science and Engineering,
Nanyang Technological University, Singapore
Email : arambam.singh@ntu.edu.sg
About Me
I am currently a Research Fellow at School of Computer Science and Engineering, Nanyang Technological University(NTU) Singapore, working with Prof. Arvind Easwaran on AI Singapore project.
I completed my PhD in Computer Science in August 2021 from School of Computing and Information Systems, Singapore Management University. I was advised by Prof. Akshat Kumar and Prof. Hoong Chuin Lau
Research Interests
Artificial Intelligence/Machine Learning - Reinforcement learning(RL), Multiagent-RL.
Professional Services
- Program Committee Member (Reviewer):
- Journal of Artificial Intelligence Research (JAIR)
- IJCAI 2024-2022, AAAI 2024-2020, ICAPS 2024-2022, ICRA 2022, IAAI 2022
- Local Organizing Committee, AAMAS - 2016
Awards & Honours
- Dean’s List - 2021, 2020, 2019 for research excellence at School of Computing & Information Systems, Singapore Management University (SMU).
- SMU Presidential Doctoral Fellowship - 2020, 2019 for outstanding academic research achievements.
- Selected to attend Global Young Scientists Summit 2020.
- Student Travel Scholarship to attend International Conference on Autonomous Agents and Multiagent Systems (AAMAS - 2019), at Montreal, Canada.
- Student Travel Scholarship to attend International Summer School on Planning and Scheduling, held in conjunction with International Conference on Automated Planning and Scheduling (ICAPS-2018), at Delft, The Netherlands.
- Fujitsu-SMU Ph.D Student Scholarship - 2017.
- Gold Medal from National Institute of Technology Durgapur, India for M.Tech. 2014.
News
- Our paper, PAS: Probably Approximate Safety Verification of Reinforcement Learning Policy Using Scenario Optimization. is accepted in International Conference on Autonomous Agents and MultiAgent Systems (AAMAS-2024).
- Our paper, Constrained Multiagent Reinforcement Learning for Large Agent Population. is accepted in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2022).
- Our paper, Trajectory Optimization for Safe Navigation in Maritime Traffic Using Historical Data is accepted in International Conference on Principles and Practice of Constraint Programming (CP-2022, Machine Learning Track).
- Our paper, Ship-Gan: Generative Modeling Based Maritime Traffic Simulator (Demo paper) is accepted in International Conference on Autonomous Agents and MultiAgent Systems (AAMAS-2021). (Best Demo Award)