Supratik Mukhopadhyay

Associate Professor

3272H Patrick F. Taylor Hall

Louisiana State University
Baton Rouge, LA 70803

Phone: 225 578 1496
mmukho1@lsu.edu

 

Educational Background

Ph.D. in Computer Science, Max-Plank Institute for Computer Science
and University of Saarland, Germany, 2001

M.S. in Computer Science, Indian Statistical Institute, Calcutta, 1996

 

Research Interests

Software Engineering, Artificial Intelligence, Computer Vision, Applications

 

Teaching Responsibilities

CSC 3380: Object Oriented Design

CSC 4101: Programming Languages

CSC 4330: Software System Development

CSC 7150: Program Analysis & Model Checking

 

Selected Publications

Saikat Basu, Supratik Mukhopadhyay, Manohar Karki, Robert DiBiano, Sangram Ganguly, Ramakrishna R. Nemani, Shreekant Gayaka: Deep neural networks for texture classification - A theoretical analysis. Neural Networks 97: 173-182 (2018).

Gokarna Sharma, Costas Busch, Supratik Mukhopadhyay: How to Make Fat Autonomous Robots See all Others Fast? ICRA 2018: 1-9.

Saikat Basu, Sangram Ganguly, Supratik Mukhopadhyay, Robert DiBiano, Manohar Karki, Ramakrishna R. Nemani: DeepSat: a learning framework for satellite imagery. SIGSPATIAL/GIS 2015: 37:1-37:10.

Boyda, E., Basu, S., Ganguly, S., Michaelis, A., Mukhopadhyay, S., & Nemani, R. R. (2017). Deploying a quantum annealing processor to detect tree cover in aerial imagery of California. PloS one, 12(2), e0172505.

Subhajit Sidhanta, Wojciech M. Golab, Supratik Mukhopadhyay, Saikat Basu: Adaptable SLA-Aware Consistency Tuning for Quorum-Replicated Datastores. IEEE Trans. Big Data 3(3): 248-261 (2017).

 

Awards and Honors

In October 2020, Dr. Mukhopadhyay won the best paper award at the 20th International Conference on Runtime Verification, 2020 for “Empirical Abstraction" authored with Vivian M Ho, Chris Alvin, Supratik Mukhopadhyay, Brian Peterson and Jimmy D Lawson in Proceedings of the 20th International Conference on Runtime Verification (RV), 2020. Lecture Notes in Computer Science.

Dr. Mukhopadhyay led the DeepDrug team (for automated drug discovery) to the semifinals of IBM Watson Artificial Intelligence XPrize while competing with 147 teams worldwide.