Krishnendu Chatterjee

Institute of Science and Technology Austria

Papers

Total Citations

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About

Krishnendu Chatterjee is a leading figure in the formal verification and synthesis of probabilistic systems, with a particular focus on partially observable Markov decision processes (POMDPs) and their applications in robotics. His work bridges the gap between theoretical computer science and practical autonomous decision-making. In a highly cited 2015 paper (57 citations), Chatterjee provided a groundbreaking qualitative analysis of POMDPs with temporal logic specifications, demonstrating how complex real-world uncertainties in robotics can be modeled and verified against linear-time temporal logic (LTL) properties. This contribution has been instrumental in enabling robots to make reliable decisions under partial observability. More recently, his 2018 work on parameter-independent strategies for parametric Markov decision processes (pMDPs) via POMDPs (2 citations) extends the frontier of robust controller synthesis, offering novel approaches to handle unknown or varying environmental parameters. Chatterjee's research has profoundly impacted the design of trustworthy autonomous systems, earning him recognition as a pioneer in probabilistic verification. His work continues to shape how engineers and computer scientists approach safety-critical robotics and AI decision-making under uncertainty.