| 2023 | ICLR | Robust Active Distillation. | Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee |
| 2020 | ICLR | Provable Filter Pruning for Efficient Neural Networks. | Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus |
| 2020 | TAMC | On Coresets for Support Vector Machines. | Murad Tukan, Cenk Baykal, Dan Feldman, Daniela Rus |
| 2019 | ICLR | Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds. | Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus |
| 2019 | TAMC | Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse PageRank. | Harry Lang, Cenk Baykal, Najib Abu Samra, Tony Tannous, Dan Feldman, Daniela Rus |
| 2018 | ICRA | Kinematic Design Optimization of a Parallel Surgical Robot to Maximize Anatomical Visibility via Motion Planning. | Alan Kuntz, Chris Bowen, Cenk Baykal, Arthur W. Mahoney, Patrick L. Anderson, Fabien Maldonado, Robert J. Webster III, Ron Alterovitz |
| 2017 | ICRA | Persistent surveillance of events with unknown, time-varying statistics. | Cenk Baykal, Guy Rosman, Sebastian Claici, Daniela Rus |
| 2016 | WAFR | Persistent Surveillance of Events with Unknown Rate Statistics. | Cenk Baykal, Guy Rosman, Kyle Kotowick, Mark Donahue, Daniela Rus |
| 2015 | IROS | Optimizing design parameters for sets of concentric tube robots using sampling-based motion planning. | Cenk Baykal, Luis G. Torres, Ron Alterovitz |
| 2014 | ICRA | Interactive-rate motion planning for concentric tube robots. | Luis G. Torres, Cenk Baykal, Ron Alterovitz |