AUSTIN, TX – Katana Graph, the AI-powered Graph Intelligence Platform providing faster, deeper, and more accurate insights on massive and complex data, announced that cofounder and CEO Keshav Pingali has been awarded the 2023 Charles Babbage Award by the Institute of Electrical and Electronics Engineers (IEEE).
Keshav co-founded Katana Graph in 2020 to drive graph computing innovation forward and to revolutionize the way that data-intensive industries – from financial services, pharmaceutical and life sciences, and security – derive immediate and valuable insights from connected data, using graph query, analytics, and AI.
Keshav is also the William “Tex” Moncrief Chair of Grid and Distributing Computing in the Department of Computer Science at the University of Texas at Austin. Before moving to Austin, he was the India Chair of Computing in the Department of Computer Science at Cornell University. Keshav has a Ph.D. from MIT and a B.Tech. degree from the Indian Institute of Technology, Kanpur, where he was awarded the President’s Gold Medal. Keshav’s research has been supported for many years by a series of DARPA grants, and that work culminated in the founding of Katana Graph.
“I am deeply honored to receive this award from the IEEE,” said Keshav Pingali, CEO and cofounder at Katana Graph. “My years in academia – and now at Katana Graph – have been dedicated to finding ways to understand data and extract deep insights from massive datasets. I am indebted to my family, colleagues, and students for supporting my passion for advancing parallel computing and graph technology.”
Named after the English polymath regarded as the father of the computer, the annual Charles Babbage Award is given in recognition to those who have made significant contributions in the field of parallel computing and is one of the highest honors in Computer Science. Along with a certificate and honorarium, the winner is invited to present a distinguished lecture at the annual IEEE CS International Parallel and Distributed Processing Symposium (IPDPS).
