Aniruddh Puranic
Cambridge,
MA 02142, USA
I am a researcher in Neuro-Symbolic AI and safe autonomous systems, with interests in building learning-enabled systems that are reliable, interpretable, and formally verifiable. My research focuses on:
- Reinforcement and imitation learning for autonomous systems
- Formal methods-based foundation models for verifiable autonomy
- Human-centered, explainable, and safe AI
- Multi-agent and lifelong learning with safety guarantees
I recently completed a postdoctoral appointment in the Institute for Systems Research (ISR) at University of Maryland - College Park, where I was mentored by John S. Baras and Calin Belta.
I received my Ph.D. in Computer Science from University of Southern California (USC) in 2024 under the supervision of Jyotirmoy V. Deshmukh and Stefanos Nikolaidis. Prior to that, I earned an M.S. in Computer Science from USC in 2018 and a B.E. in Computer Science and Engineering from B.M.S College of Engineering (VTU), India in 2016.
During my Ph.D., I was a Research Intern at SRI International’s Center for Vision Technologies (Summer 2022), where I worked on lifelong learning. Before graduate school, I was a researcher in the Intelligent Connected Systems Division at Toyota North America R&D - InfoTech Labs, where I worked on data-driven formal specifications for connected-vehicle systems and edge computing applications.