Portrait of J. Andrew (Drew) Bagnell
Consulting Professor
Home Department: RI
Phone: (412) 681-8669
Administrative Assistant: Brian Hutchison
Mailing Address

I am interested in “closing the loop” on complex systems; that is, I am interested in designing algorithms that allow systems to observe their own operation and improve performance. My belief is that the border land between planning, control and computational learning is particularly rich with research challenges and potential to make real, immediate impact on applications. I’m particularly interested in systems for which we can obtain at best a partial model. To this end, I’m excited about extending research tools that come from information theory, statistics, control theory, statistical physics and optimization.

At the moment, I am particularly focused on two areas in machine learning. First I am working on applications of learning and decision making applied to mobile robotics. Second, I am interested in developing rich, structured probabilistic models that are appropriate for both making and learning decisions.

Displaying 168 Publications

2022
Gokul Swamy, Nived Rajaraman, Matt Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, and Kannan Ramchandran
Conference Paper, Proceedings of (NeurIPS) Neural Information Processing Systems, November, 2022
Conference Paper, Proceedings of (NeurIPS) Neural Information Processing Systems, November, 2022
Conference Paper, Proceedings of (ICML) International Conference on Machine Learning, August, 2022
Tech. Report, CMU-RI-TR-22-53, Robotics Institute, Carnegie Mellon University, August, 2022
2021
Conference Paper, Proceedings of (ICML) International Conference on Machine Learning, May, 2021
Conference Paper, Proceedings of 35th AAAI Conference on Artificial Intelligence (AAAI '21), pp. 6147 - 6155, February, 2021
2020
Conference Paper, Proceedings of 59th IEEE Conference on Decision and Control (CDC '20), pp. 4157 - 4163, December, 2020
Conference Paper, Proceedings of Robotics: Science and Systems (RSS '20), July, 2020
2019
Conference Paper, Proceedings of (ICML) International Conference on Machine Learning, pp. 6036 - 6045, June, 2019
Conference Paper, Proceedings of 22nd International Conference on Artificial Intelligence and Statistics (AISTATS '19), March, 2019