Anuran Makur
Assistant Professor of Computer Science
Assistant Professor of Electrical and Computer Engineering
Joined department: Fall 2021
Education
Anuran Makur is an Assistant Professor in the Department of Computer Science and the Elmore Family School of Electrical and Computer Engineering at Purdue University, West Lafayette, IN, USA. He received his B.S. degree with highest honors (summa cum laude) from the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley (UC Berkeley), CA, USA, in 2013, and his S.M. and Sc.D. degrees from the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, in 2015 and 2019, respectively. Then, he was a postdoctoral researcher at the Laboratory for Information and Decision Systems and the Institute for Data, Systems, and Society at MIT from 2019 to 2021. His research interests include theoretical statistics and machine learning, information theory, and other areas in applied probability. He was a recipient of the Arthur M. Hopkin Award from UC Berkeley in 2013, the Irwin Mark Jacobs and Joan Klein Jacobs Presidential Fellowship from MIT in 2013, the Ernst A. Guillemin Master's Thesis Award from MIT in 2015, the Jin Au Kong Doctoral Thesis Award from MIT in 2020, and the Thomas M. Cover Dissertation Award from the IEEE Information Theory Society in 2021.
Selected Publications
A. Jadbabaie, A. Makur, and D. Shah, "Estimation of skill distribution from a tournament," in Proceedings of the Advances in Neural Information Processing Systems 34 (NeurIPS), Vancouver, BC, Canada, December 6-12 2020, pp. 8418-8429.
A. Makur, E. Mossel, and Y. Polyanskiy, "Broadcasting on random directed acyclic graphs," IEEE Transactions on Information Theory, vol. 66, no. 2, pp. 780-812, February 2020.
A. Makur, E. Mossel, and Y. Polyanskiy, "Broadcasting on two-dimensional regular grids," IEEE Transactions on Information Theory, vol. 68, no. 10, pp. 6297-6334, October 2022.
A. Makur, "Coding theorems for noisy permutation channels," IEEE Transactions on Information Theory, vol. 66, no. 11, pp. 6723-6748, November 2020.
A. Jadbabaie, A. Makur, E. Mossel, and R. Salhab, "Inference in opinion dynamics under social pressure," IEEE Transactions on Automatic Control, July 2022.