Aditya Pisupati is a Research Scientist at Google AI (formerly Google Brain). His research primarily focuses on reinforcement learning, decision-making under uncertainty, multi-agent systems, and the application of these concepts to robotics and large language models. He is interested in developing algorithms that enable intelligent agents to learn complex behaviors, generalize to new situations, and interact safely and effectively in real-world environments. Aditya completed his PhD in Computer Science from Stanford University, where his work centered on reinforcement learning for robotics, and his B.Tech in Computer Science from IIIT Hyderabad. His contributions often involve theoretical advancements as well as practical applications in complex domains.
Aditya Pisupati's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Completed doctoral studies at Stanford University, advised by Prof. Jeannette Bohg and Prof. Shuran Song, focusing on reinforcement learning for robust robotic manipulation and generalizable decision-making.
Conducting cutting-edge research in artificial intelligence, with a focus on reinforcement learning, multi-agent systems, and their applications in areas like robotics and large language models. Contributes to projects aiming to build more capable and general AI systems.
Authored and co-authored numerous research papers presented at prestigious international conferences such as NeurIPS (Neural Information Processing Systems), ICML (International Conference on Machine Learning), CoRL (Conference on Robot Learning), and ICLR (International Conference on Learning Representations).
Developed novel algorithms and frameworks for improving sample efficiency, generalization, and safety in reinforcement learning, with significant applications in robotic control and manipulation tasks.
University of Hyderabad - Year 2003
Jawaharlal Nehru Technological University - Year 1998
Jhonson Grammar School - Year 1989
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