Insoon Yang
Papers
11
Total Citations
548
H-Index
8
About
Insoon Yang is a prominent researcher at the intersection of robotics, autonomous systems, and optimization-based control, with a particular focus on risk-aware motion planning and distributionally robust decision-making. His work has garnered significant attention, accumulating hundreds of citations across a productive body of research that spans machine learning applications in industrial settings to cutting-edge safety frameworks for mobile robots. Yang's most influential contributions center on developing mathematically rigorous methods for enabling robots to navigate uncertain, dynamic environments safely. His pioneering use of Conditional Value-at-Risk (CVaR) as a safety metric, introduced in his 2019 paper on risk-aware motion planning (108 citations), has shaped how researchers approach probabilistic safety guarantees. He further advanced this line of work through distributionally robust optimization techniques—leveraging Wasserstein distance metrics and semidefinite programming—to ensure collision avoidance even when the underlying probability distributions of environmental uncertainty are unknown or learned imperfectly. Beyond classical optimization, Yang has made notable strides in bridging model predictive control with reinforcement learning, including safe RL via Lyapunov-based approaches and meta-RL integration for adaptive robot behavior. His research is especially valuable for students working in autonomous driving, surgical robotics, or any safety-critical application where uncertainty quantification is essential.
Research Focus
Key Achievements
Top Papers
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- 2Risk-Aware Motion Planning and Control Using CVaR-Constrained Optimization108 citations · 2019
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