Tony Dear

He recently introduced a new graduate-level course on Data-Driven Decision Modeling, and he is the instructor of Decision Making and Reinforcement Learning on Coursera.

Dear is currently a faculty director of Columbia Engineering's Online Artificial Intelligence Executive Education certificate program. He is also the current faculty director of the CS@CU MS Bridge program for students and professionals from non-CS backgrounds seeking to make a transition into a CS-oriented career. 

Dear regularly advises undergraduate and graduate students on individual research projects. His research interests lie in the intersection of robotics and reinforcement learning. He is particularly interested in systems for which traditional planning methods have difficulty scaling due to problem complexity, but whose structure may be exploited to increase sampling efficiency. His goal is to make such methods work on real, physical robots, especially in the realm of locomotion.

Dear received his BS in Electrical Engineering and Computer Science from UC Berkeley in 2012. He subsequently received his MS in 2015 and PhD in 2018, both in Robotics from Carnegie Mellon University.

Research Areas

• Artificial Intelligence (AI) and Machine Learning (ML)
• Vision and Robotics
• Applied and Theoretical Machine Learning
• Robotics and Autonomous Systems