Bo Dai

Bo Dai is an Assistant Professor at the School of Computational Science and Engineering, Georgia Institute of Technology, and a Staff Research Scientist at Google DeepMind. His research focuses on Agent AI, Generative Models, and Representation Learning, aiming to create decision-making agents through world modeling. He holds a Ph.D. from Georgia Tech (2013–2018) and previously worked at Google Brain. Dai has authored numerous influential papers in top conferences like NeurIPS, ICML, and ICLR, and received the AISTATS Best Paper Award (2016).

Education:

• Ph.D., School of Computational Science and Engineering, Georgia Tech (2013–2018)

Research Interests:

• Reinforcement Learning and Representation Learning for decision-making agents
• Generative Models and their integration with Agent AI
• Provable and scalable algorithms for real-world applications

His work bridges theory and practice, emphasizing spectral representations and provable guarantees in complex systems.

Key Article Trends: His recent work emphasizes scalable spectral methods for multi-agent systems, diffusion policies, and representation-based techniques in reinforcement learning. He also explores LLM alignment and sim-to-real transfer learning.

Awards:

• AISTATS Best Paper Award (2016)
• NeurIPS Workshop Best Paper (2017)
• Ross Fellowship (2011–2012)

Advising & Grants: Supervises 6 current Ph.D. and M.S. students. Active in organizing workshops on reinforcement learning and serves as an Area Chair for top conferences.

Labs & Software: Leads development of Representation-based Reinforcement Learning and Repr-Control toolboxes for nonlinear control and stochastic systems.