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个人简介
His research focuses on the theory and practice of artificial intelligence; largely motivated by problems that require a blend of techniques to develop systems and algorithms that support decision making for autonomous agents and/or humans. Most of his projects and leverage theory, data, and experiment to create novel algorithms, mechanisms, and systems that enable and support individual and group decision making.
Before joining Tulane he was a Research Staff Member in the IBM TJ Watson Research Laboratory in the IBM Research AI – Reasoning Lab where he worked on a number of topics including Complex Question Answering / Natural Language Inference, Decision Making, and issues in AI, Ethics, and Society.
Before joining Tulane he was a Research Staff Member in the IBM TJ Watson Research Laboratory in the IBM Research AI – Reasoning Lab where he worked on a number of topics including Complex Question Answering / Natural Language Inference, Decision Making, and issues in AI, Ethics, and Society.
研究兴趣
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SIGCSE (2) (2023)
WWW 2023pp.2808-2818, (2023)
MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE, LOD 2022, PT II (2023): 502-509
AI Mattersno. 3 (2023): 4-9
Jessie J. Smith, Anas Buhayh, Anushka Kathait, Pradeep Ragothaman,Nicholas Mattei,Robin Burke,Amy Voida
FAccTpp.1652-1663, (2023)
AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systemspp.2685-2687, (2023)
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CoRR (2023)
AAMAS '23 Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (2023): 573-581
CoRRpp.2058-2068, (2023)
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