Tony Dear
Senior Lecturer in Computer Science
Tony Dear is a member of the Computer Science teaching faculty. He designs and teaches courses in the areas of math for CS, artificial intelligence, and robotics. He co-designed a new graduate-level course on Data-Driven Decision Modeling, and he is also the instructor of Decision Making and Reinforcement Learning on Coursera.
Dear is a faculty director of Columbia Engineering's Online Artificial Intelligence Executive Education certificate program. He is also the 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, reinforcement learning, and deep 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.
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
Additional Information
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Professional Experience
- Senior Lecturer in Computer Science, Columbia University, 2025-
- Lecturer in the Discipline of Computer Science, Columbia University, 2018-
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Education
- PhD, Robotics, Carnegie Mellon University
- MS, Robotics, Carnegie Mellon University
- BS, Electrical Engineering and Computer Science, University of California, Berkeley