Keynote Speaker-Towards Robust and Efficient Autonomous Driving Systems from the Lens of Software Engineering

Autonomous driving systems operate in complex, unpredictable environments where accuracy alone is insufficient. Safe deployment requires robustness, efficiency, fault tolerance, and systematic testing. This talk discusses how software engineering perspectives help bridge the gap between ML model performance and real-world dependable autonomy. Dr. Yang introduces recent work on robustness frameworks for ADS perception, stress-testing perceptual modules, and detecting high-latency behaviors. These findings highlight the importance of engineering-driven analysis in building safer and more reliable autonomous systems.