Upendranatha Sharma Chakravarthy

Dr. Upendranatha Sharma Chakravarthy is a Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA), where he has served since January 2000. He leads the Information Technology Laboratory (IT Lab), established in 2000, and oversees the NSF-funded Distributed and Parallel Computing Cluster. His roles include academic leadership, research mentorship, and contributions to the College of Engineering.

Education: He holds a B.E. in Electrical Engineering from the Indian Institute of Science (1973), M.Tech from IIT Bombay (1975), and Ph.D. from the University of Maryland (1985). Prior to UTA, he was at the University of Florida (1989–1999) and held industry roles at Xerox and Computer Corporation of America.

Research Interests focus on Big Data Analytics using AI/ML, graph mining, multilayer networks, stream data processing, and distributed systems. His work emphasizes scalability, real-time data handling, and applications in social networks, healthcare, and cybersecurity. Recent projects include MLN-geeWhiz (multilayer network analysis), CoWiz (Covid-19 visualization), and NetSplicer (scalable network algorithms).

Awards include ACM Distinguished Scientist (2011), IEEE Senior Member (2011), and multiple university awards for research excellence. He organizes conferences (e.g., DEBS 2013) and teaches advanced topics in databases, data mining, and parallel computing.

Grants: Active NSF funding includes NetSplicer (2020–2025) and CyberTraining (2023–2024). He has supervised 15 PhD and 85 MS students. The IT Lab collaborates with industry/government on projects like ROMAN (airborne networks) and justice-in-data initiatives.

Labs/Teams: IT Lab specializes in big data science, developing tools like ModViz (data visualization) and VideoScoop (video analysis). It also promotes underrepresented STEM participation through BPC initiatives.