Sayan Saha
Papers
3
Total Citations
58
H-Index
3
About
Sayan Saha is a leading researcher in formal methods for robotics, specializing in the synthesis of safe and optimal controllers for autonomous and semiautonomous systems. His work bridges temporal logic and control theory to ensure that robots not only perform tasks efficiently but also adhere to complex, human-interpretable specifications. Saha’s most impactful contribution is his method for advisory temporal logic inference, where he learns and refines Signal Temporal Logic (STL) formulas from successful and failed task trajectories, enabling robots to improve through experience. This work, published in 2018, has garnered 30 citations and is pivotal for human-robot collaboration. His 2017 paper on task and motion planning for manipulator arms, with 24 citations, introduced Metric Temporal Logic (MTL) to synthesize control inputs that guarantee task execution while optimizing performance—a key advance for industrial automation. Earlier, in 2016, Saha developed a Mixed-Integer Linear Programming (MILP) approach for real-time controller synthesis with MTL specifications, achieving reactive, correct-by-construction behaviors. With over 58 total citations, Saha’s research is foundational for developing trustworthy, specification-driven robotic systems, making him a vital figure in the intersection of formal verification and robotics.
Research Focus
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Top Papers
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