Anuran Makur - Department of Computer Science - Purdue University Skip to main content
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Anuran Makur

Assistant Professor of Computer Science

Assistant Professor of Electrical and Computer Engineering


Joined department: Fall 2021

Education

Sc.D., Massachusetts Institute of Technology, Electrical Engineering and Computer Science (2019)
S.M., Massachusetts Institute of Technology, Electrical Engineering and Computer Science (2015)
B.S., University of California, Berkeley, Electrical Engineering and Computer Sciences (2013)

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 the theory of machine learning, information theory, and applied probability. He was a recipient of the Arthur M. Hopkin Award from UC Berkeley in 2013, the 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, the Thomas M. Cover Dissertation Award from the IEEE Information Theory Society in 2021, and the CAREER Award from the National Science Foundation in 2023.

Selected Publications

W. Lu and A. Makur, "Permutation capacity region of adder multiple-access channels," IEEE Transactions on Information Theory, vol. 70, no. 7, pp. 4693-4720, July 2024.

A. Jadbabaie, A. Makur, and D. Shah, "Estimation of skill distributions," IEEE Transactions on Information Theory, vol. 70, no. 9, pp. 6447-6480, September 2024.

A. Makur and J. Singh, "Minimax hypothesis testing for the Bradley-Terry-Luce model," submitted preprint, pp. 1-54, 2024.

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 and J. Singh, "Doeblin coefficients and related measures," IEEE Transactions on Information Theory, vol. 70, no. 7, pp. 4667-4692, July 2024.

Last Updated: Jul 7, 2021 12:27 PM

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