Lena Trang

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About

Lena Trang is an emerging researcher at the forefront of autonomous systems safety, specializing in real-time motion planning, reachability analysis, and risk-aware decision-making for autonomous vehicles. Her work addresses one of the most pressing challenges in robotics: enabling autonomous systems to operate safely and efficiently under real-world uncertainty. Trang's most recognized contribution is the REFINE framework, which combines robust feedback linearization with zonotope-based reachability analysis to enable real-time, safety-guaranteed trajectory design for autonomous vehicles. By eliminating the need for computationally expensive online numerical integration, REFINE represents a significant advancement in making provably safe motion planning practically viable. Her 2024 iteration of this work has already garnered 8 citations, reflecting rapid uptake in the research community. Complementing this, her RADIUS framework tackles the conservatism inherent in deterministic safety methods by incorporating chance-constrained optimization, allowing robots to reason probabilistically about obstacle locations without sacrificing responsiveness. Together, these contributions accumulating 14 citations across three papers signal a focused and impactful research trajectory. Trang's work is particularly valuable for students and researchers seeking rigorous yet computationally tractable approaches to autonomous vehicle safety.