Jyotikrishna Dass

About

Jyotikrishna Dass is an assistant professor in the School of Electrical, Computing, and Software Engineering at The University of Arizona. His research integrates machine learning, parallel computing, and hardware design to create efficient algorithms and systems for distributed edge intelligence. His work has been featured in the IEEE International Conference on Machine Learning (ICML), IEEE International Conference on Distributed Computing Systems (ICDCS), IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE International Symposium on High-Performance Computer Architecture (HPCA), IEEE Micro and IEEE Transactions on Computers (TC). He has served as instructor-of-record for several courses during his g

Education

• PhD, Computer Science and Engineering, Texas A&M University, College Station, 2021
• B.Tech, Electronics and Communications Engineering; Minor in Computer Science and Engineering, Indian Institute of Technology, Guwahati, 2014