معرفی
Tony Dear is a Senior Lecturer in the Computer Science Department at Columbia University, affiliated with the School of Engineering and Applied Science (SEAS). He serves as faculty director for the CS@CU Bridge to MS Program and the online Artificial Intelligence executive education program. His teaching focuses on courses like Discrete Mathematics (COMS 3203) and Artificial Intelligence (COMS 4701), emphasizing computational problem-solving and theoretical foundations. Dear holds a B.S. from UC Berkeley (2012), and M.S. and Ph.D. from Carnegie Mellon University's Robotics Institute (2015/2018).
His research integrates geometric mechanics and reinforcement learning to advance robot locomotion, particularly in underactuated systems and swimming robots. Recent work explores symmetry exploitation to accelerate learning and reduce computational demands. He advises students on independent projects ranging from reinforcement learning applications to robotics education development. Notable contributions include launching a Coursera course on Decision Making and Reinforcement Learning (2023).
Dear has advised Columbia Space Initiative’s NASA Robotics Challenge team (2020) and ADI Labs (2019). His teaching philosophy prioritizes student-driven projects and pedagogical innovation, supported by Columbia’s Center for Teaching and Learning. He emphasizes the importance of STEM education scalability and accessibility through online platforms and executive training programs.
