Inaugural Chief AI Officer, University of Utah. Director of the Scientific Computing and Imaging Institute and Presidential Professor in the University of Utah’s Kahlert School of Computing. US.

“Harnessing Responsible AI for Science: Taming Open Data“

Tuesday 17 February 2026

Abstract

Artificial intelligence (AI) and open data have become essential engines for scientific discovery and innovation. However, realizing this transformative potential requires a transdisciplinary approach that ensures research and development can effectively and responsibly leverage the diversity of data sources. Despite the exponential growth of available digital data sources and the ubiquity of non-trivial computational power for processing this data, realizing data-driven, AI-enabled science workflows remains challenging. In this talk, I will discuss the importance of democratizing AI R&D, including access to open data and advanced cyberinfrastructure. I will introduce the University of Utah’s One-U Responsible AI Initiative, which aims to catalyze an innovation ecosystem at the University of Utah and across the state. I will also present the vision, architecture, and deployment of the National Data Platform project, as part of a broader national cyberinfrastructure, aimed at catalyzing an open and extensible data ecosystem for science.

Bio

Manish Parashar is the inaugural Chief AI Officer at the University of Utah. He is also Executive Director of the Scientific Computing and Imaging (SCI) Institute, and Presidential Professor in the Kalhert School of Computing. He leads the University’s One-U Responsible AI Initiative. Manish’s expertise is in high-performance parallel and distributed computing and cyberinfrastructure, and his research has enabled new insights across multiple science domains.

Manish has received several awards for his research and leadership, including the 2023 IEEE Computer Society Sidney Fernbach Award, the 2024 CRA Distinguished Service Award, and the 2025 ACM Distinguished Service Award.

Manish is a Fellow of AAAS, ACM, and IEEE.

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