TLDR: Rensselaer Polytechnic Institute (RPI) Assistant Professor Shaowu Pan has been recognized with two prestigious awards: a Google Research Scholar Award for his work on an AI assistant for Computational Fluid Dynamics (CFD) and an ARPA-E award, funded by General Electric Vernova (GEV), for advancements in hydrogen sensing and diagnostics. These accolades highlight his innovative contributions at the intersection of artificial intelligence and sustainable energy solutions.
Troy, NY – Dr. Shaowu Pan, an assistant professor of mechanical, aerospace, and nuclear engineering at Rensselaer Polytechnic Institute (RPI), has been awarded two significant honors for his groundbreaking research in artificial intelligence and clean energy. These awards underscore his commitment to addressing complex engineering challenges through innovative computational and data-driven methodologies.
Dr. Pan received a Google Research Scholar Award to support the development of an artificial intelligence (AI) assistant designed to enhance Computational Fluid Dynamics (CFD). This AI tool aims to make CFD faster, more accessible, and more productive for engineers globally. The project also holds potential for broader applications, including improving weather forecasting by predicting wind interactions with structures. To measure the progress of this ambitious endeavor, Dr. Pan’s team has already developed the first comprehensive benchmark for evaluating large language models (LLMs) on CFD tasks. Dr. Pan noted, ‘Much of my research is about finding ways to make very difficult tasks more manageable. The AI assistant is one example of how we can design smarter tools to help engineers focus on discovery and innovation.’
In addition to the Google award, Dr. Pan secured funding from General Electric Vernova (GEV) through an award from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E). This funding will be directed towards advancing hydrogen sensing and diagnostics, crucial for ensuring the safe and economical operation of hydrogen energy infrastructure. This initiative extends his vision of applying innovative solutions to the energy sector.
Dr. Pan’s research at RPI, where he leads the Computational Scientific Machine Learning (CSML) Lab, spans computational fluid dynamics, data-driven modeling of complex systems, scientific machine learning, and generative AI. His work integrates theoretical principles, computational techniques, and AI to transform engineering approaches to some of the world’s most pressing issues. He is also affiliated with the Rensselaer-IBM Artificial Intelligence Research Collaboration.
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Prior to his tenure at RPI, Dr. Pan was a postdoctoral scholar at the AI Institute of Dynamic Systems at the University of Washington, Seattle. He earned his Ph.D. in Aerospace Engineering and Scientific Computing in 2021 from the University of Michigan, Ann Arbor. His academic background also includes an M.S.E. in Mechanical Engineering from the University of Michigan (2015) and a B.S. in Applied Mathematics and B.E. in Aerospace Engineering from Beihang University (2013). His previous recognitions include the MICDE Fellowship (2018), Doctoral Fellowship (2016), Rackham Summer Award (2015), Richard and Eleanor Towner Prize for Outstanding Ph.D. Research (2019 Department Nominee), and the Chinese Outstanding Student Abroad Award (2018).
