"Human-Centered Autonomous Vehicles"
Abstract: I will present a human-centered paradigm for building autonomous vehicle systems, contrasting it with how the problem is currently formulated and approached in academia and industry. The talk will include discussion and video demonstration of new work on driver state sensing, voice-based transfer of control, annotation of large-scale naturalistic driving data, and the challenges of building and testing a human-centered autonomous vehicle at MIT.
Bio: Lex Fridman is a research scientist at MIT, working on deep learning approaches to perception, control, and planning in the context of semi-autonomous vehicles and more generally human-centered artificial intelligence systems. His work focuses on learning-based methods that leverage large-scale, real-world data. Lex received his BS, MS, and PhD from Drexel University where he worked on applications of machine learning, computer vision, and decision fusion techniques in a number of fields including robotics, active authentication, and activity recognition. Before joining MIT, Lex was at Google leading deep learning efforts for large-scale behavior-based authentication. Lex is a recipient of a CHI-17 best paper award and a CHI-18 best paper honorable mention award.