S.G.Krishna, A. Narasimhan, S. Radhakrishnan, On Factorizing Million Scale Non-Negative Matrices using Compressed Structures, in-progress

S.G.Krishna, A. Narasimhan, S. Radhakrishnan, R. Veras, Billion Scale Tensors: Compression Methods and Parallel Computations, The 27th Int’l Conf on Parallel and Distributed Processing Techniques and Applications, in-press

S.G.Krishna, A. Narasimhan, S. Radhakrishnan, R. Veras, On Large-Scale Matrix-Matrix Multiplication on Compressed Structures, IEEE Conference on Big Data 2021, pg 2976-2985

M. Nelson, S. Radhakrishnan, A. Chatterjee, C. Shekaran, S.G. Krishna, Queryable Compression on Time-EvolvingWeb and Social Networks with Streaming, ACM Transactions on Web, Volume 16, Issue 2, May 2022

S.G. Krishna, S. Radhakrishnan, M. Nelson, A. Chatterjee, C. Shekaran, On Compressing Time-Evolving Networks, The Seventh International Conference on Big Data, Small Data, Linked Data and Open Data, pg 43-48

Presented my work Billion Scale Tensors: Compression Methods and Parallel Computations at The 27th Int’l Conf on Parallel and Distributed Processing Techniques and Applications in Las Vegas, USA

Presented my work On Large-Scale Matrix-Matrix Multiplication on Compressed Structures at IEEE Conference on Big Data 2021 (Virtual)

Presented my work On Compressing Time-Evolving Networks, at The Seventh International Conference on Big Data, Small Data, Linked Data, and Open Data (Virtual)

Presented Introduction to Python Programming at DataBite Workshop at the University of Oklahoma. Fall 2020

Presented Introduction to Python Programming at the country-wide AI/ML symposium held at the University of Oklahoma. Spring 2020