Sriram Sankaranarayanan
Papers
9
Total Citations
223
H-Index
5
About
Sriram Sankaranarayanan is a leading researcher at the intersection of formal methods, robotics, and probabilistic programming. His work focuses on ensuring the safety and correctness of autonomous systems, particularly those operating under uncertainty. He has made foundational contributions to the static analysis of probabilistic programs (122 citations), developing techniques to verify properties of code used in risk analysis and cyber-physical systems. In robotics, Sankaranarayanan has advanced automata-theoretic approaches for task and mission planning, addressing the critical challenge of revising specification automata to guarantee provably correct robot behavior (30, 28 citations). His recent work includes counterexample-guided training of neural networks for trajectory tracking control (12 citations) and the development of temporal behavior trees for robust specification and trace segmentation (3 citations). He has also pioneered automated, adaptive multimodal feedback systems for psychomotor skills training in quadrotor teleoperation (4 citations), demonstrating a commitment to scalable human-robot interaction. With a research portfolio spanning invariant generation for parametrized systems and probabilistic specification learning, Sankaranarayanan’s work is essential reading for anyone interested in building reliable, verifiable autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Static analysis for probabilistic programs122 citations · 2013
- 2On the minimal revision problem of specification automata30 citations · 2015
- 3On the revision problem of specification automata28 citations · 2012
- 4Invariant Generation for Parametrized Systems Using Self-reflection18 citations · 2012
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- 8Temporal Behavior Trees: Robustness and Segmentation3 citations · 2024
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