|Academic Profile |
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Assoc Prof Bo An
Associate Professor, School of Computer Science and Engineering
Assistant Chair (Innovation)
|Bo An is an Associate Professor and the President’s Council Chair in Computer Science and Engineering, Nanyang Technological University, Singapore. He received the Ph.D degree in Computer Science from the University of Massachusetts, Amherst. |
His current research interests include artificial intelligence, multiagent systems, computational game theory, reinforcement learning, and optimization. His research results have been successfully applied to many domains including infrastructure security and e-commerce. He has published over 90 referred papers at AAMAS, IJCAI, AAAI, ICAPS, KDD, WWW, JAAMAS, AIJ and ACM/IEEE Transactions. Dr. An was the recipient of the 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award, an Operational Excellence Award from the Commander, First Coast Guard District of the United States, the 2012 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice, and 2018 Nanyang Research Award (Young Investigator). His publications won the Best Innovative Application Paper Award at AAMAS’12 and the Innovative Application Award at IAAI’16. He was invited to give Early Career Spotlight talk at IJCAI’17. He led the team HogRider which won the 2017 Microsoft Collaborative AI Challenge. He was named to IEEE Intelligent Systems' "AI's 10 to Watch" list for 2018. He was invited to be an Advisory Committee member of IJCAI’18. He is a member of the editorial board of JAIR and the Associate Editor of JAAMAS, IEEE Intelligent Systems, and ACM TIST. He was elected to the board of directors of IFAAMAS and senior member of AAAI.
You can find more information at http://www.ntu.edu.sg/home/boan/
|Artificial intelligence, multi-agent systems, game theory, reinforcement learning, automated negotiation, resource allocation, and optimization|
- 2019 President’s Council Chair in Computer Science and Engineering (An Bo)
- ADL+: A Digital Toolkit for Cognitive Assessment and Intervention
- Adversarial Machine Learning in Big Data Era
- Anti-spam Impression Allocation and Ranking Policy Robustness Evaluation
- Cyber security solutions for smart traffic control systems
- Dynamic Electronic Toll Collection for Traffic Congestion Alleviation
- Improving Cybersecurity through Optimal Policy Design and Human Behaviour Modelling
- Improving Trustworthiness of Real-world AI systems through Adversarial Attack and Effective Defense
- Large Scale Influence Maximization with Uncertain States and Networks
- Modelling, Analysis and Computation for Combating Multiple Cooperative Adversaries
- New Directions in Adversarial Machine Learning: From Theory to Applications
- Next Generation Computationa; Game Theory For Security
- Optimal Pricing for Competitive Cloud Markets with Incomplete Information
- Optimal Security Resource Allocation for Protecting Large Public Events
- Some Key Research Problems in Multi-agent Systems
- Understand AI’s Ecosystem
- JC.Jiang, B. An, YC. Jiang, P. Shi, Z. Bu, J. Cao. (2019). Batch Allocation for Tasks with Overlapping Skill Requirements in Crowdsourcing. IEEE Transactions on Parallel and Distributed Systems, Accepted.
- JC. Jiang, B. An, YC. Jiang, DH. Lin. (2019). Context-aware Reliable Crowdsourcing in Social Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, Accepted.
- JC. Jiang, B. An, YC. Jiang, DH. Lin, Z. Bu, J. Cao, Z. Hao. (2018). Understanding Crowdsourcing Systems from a Multiagent Perspective and Approach. ACM Transactions on Autonomous and Adaptive Systems, 13(2), Article 8.
- Han Yu, Chunyan Miao, Bo An, Zhiqi Shen & Cyril Leung.(2018). Making Efficient Reputation-aware Decisions in Multi-agent Systems. In Jianye Hao & Ho-Fung Leung(Ed), Interactions in Multiagent SystemsSingapore: World Scientific.
- JC. Jiang; P. Shi; B An; JY. Yu; CJ. Wang. (2017). Measuring the social influences of scientist groups based on multiple types of collaboration relations. Information Processing and Management, 53(1), 1-20.