Field of Research     AI + Robotics
Focus Areas       Sequential decision making, learning abstractions for reliable planning and learning, generalized planning, explainable AI, AI safety and AI assessment, knowledge representation, probabilistic programming, probabilistic inference and machine learning

My research group focuses on developing new formal frameworks and algorithmic paradigms that enable reliable, taskable AI systems: autonomous agents that can learn to plan and act efficiently and reliably under uncertainty to achieve user-desired objectives.

Our ongoing research includes neuro-symbolic approaches for learning abstraction hierarchies and generalizable knowledge for reliable sequential decision-making in a wide range of AI systems including online agents as well as physical robots, as well as explainable AI and AI safety. Check out my group's webpage to learn more about our research!

Student opportunities: If you are interested in joining my group, send me a message with your CV and a note about your related interests and past work. The main requirements for starting a project with me are to have a strong motivation for doing AI research and a good technical foundation. If you have done well in technically rigorous classes in AI, or mathematics, or CS theory, you are off to a great start!

Press Coverage: The BBC | Motherboard | AAAS Eureka Alert! Science News | NBC News | IEEE Spectrum

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