I am an assistant professor at Carnegie Mellon University (CMU) in the Robotics Institute. I lead a research group, RPAD: Robots Perceiving And Doing.
You can check out my lab website:

[RPAD Website][Publications][Lab Members]

Formal Bio

David Held is an assistant professor at Carnegie Mellon University in the Robotics Institute and is the director of the RPAD lab: Robots Perceiving And Doing. His research focuses on perceptual robot learning, i.e. developing new methods at the intersection of robot perception and planning for robots to learn to interact with novel, perceptually challenging, and deformable objects. David has applied these ideas to robot manipulation and autonomous driving. Prior to coming to CMU, David was a post-doctoral researcher at U.C. Berkeley, and he completed his Ph.D. in Computer Science at Stanford University. David also has a B.S. and M.S. in Mechanical Engineering at MIT. David is a recipient of the Google Faculty Research Award in 2017 and the NSF CAREER Award in 2021.

You can also download my slightly outdated CV.

Research Interests

My research lies at the intersection of robotics, machine learning, and computer vision.

I am interested in developing new methods for robotic perception and control that can allow robots to operate in the complex environments of our daily lives. I have applied the idea of perceptual robot learning to improve a robot's capabilities in two domains: object manipulation and autonomous driving. In the realm of object manipulation, I am developing methods for robots to learning to manipulate novel objects, perceptually challenging objects (e.g. transparent and specular), and deformable objects (e.g. cloth). Regarding autonomous driving, I am developing methods for self-supervised learning and semi-supervised learning (e.g. learning from unlabeled data). Solving these challenges requires rethinking robot perception and control algorithms to handle these types of tasks.

To find out more, check out my lab website: [RPAD Website][Publications][Lab Members]

Joining my Group

If you are interested in coming to CMU to join my group as a Ph.D. student, there is no need to email me. Just apply to CMU's Ph.D. program! You should apply to either the Robotics Institute Ph.D. program or the Machine Learning Ph.D. program and mention my name in your research statement. After you get accepted, you should contact me to discuss the possibility of working in my group.

Teaching

Spring 2018:16-831: Statistical Techniques in Robotics
Spring 2019: 16-881: Seminar: Deep Reinforcement Learning for Robotics
Fall 2019: 16-831: Statistical Techniques in Robotics
Spring 2020: 16-881: Seminar: Deep Reinforcement Learning for Robotics
Fall 2020: 16-831: Statistical Techniques in Robotics
Spring 2021: 16-881: Seminar: Deep Reinforcement Learning for Robotics







Elliot Dunlap Smith Hall (EDSH), Room 213