Siddharth Srivastava

Siddharth Srivastava is an Associate Professor at the School of Computing and Augmented Intelligence, Arizona State University, where he directs the Autonomous Agents and Intelligent Robotics (AAIR) Lab. His research focuses on principled AI systems for generalizable planning, sequential decision-making under uncertainty, and user-driven AI assessment. He previously served as Staff Scientist at United Technologies Research Center and postdoctoral researcher at UC Berkeley.

• Education
  • Ph.D. in Computer Science, University of Massachusetts-Amherst
  • M.S. in Mathematics, Indian Institute of Technology (IIT) Kanpur

His work spans AI planning, robotics, and neuro-symbolic methods, emphasizing safe, reliable AI systems that can learn abstractions, transfer knowledge, and self-assess capabilities. Recent publications focus on user-aligned explanations, integrated task-motion planning, and stochastic reinforcement learning.

Scientific recognition includes:

• NSF CAREER award
• Top 5% Faculty Award (Fulton Schools of Engineering)
• Best Paper at ICAPS
• Outstanding Dissertation (UMass Amherst)
• Best Final Year Thesis (IIT Kanpur)
• Chambliss Medal (AAS)

He has supervised multiple Ph.D. students including Pulkit Verma, Naman Shah, and Rushang Karia, and developed the JEDAI system for teachable robot planning. His research has been featured in BBC, Motherboard, and IEEE Spectrum.