AI and Scientific Computing: Algorithmic Alloys for Forecasting and Optimization of Complex Systems

Petros Koumoutsakos, Harvard Cambridge Fluids Network - fluids-related seminars 12 November 2025 2:00pm LR6 Computational science and Artificial Intelligence have been drivers and benefactors of advances in algorithms and hardware, each in different ways, and originally with different targets. The intellectual space between these two fields is home to exciting opportunities for scientific discovery and engineering innovation. I will discuss algorithmic alloys based on the fusion of data driven and equation driven methodologies for the prediction and control of complex flows. I will also present ideas of developing algorithmic alloys for fusing experiments and simulations for understanding and controlling complex systems. BIO: Petros Koumoutsakos is Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering at Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). He is currently on sabbatical as a visiting research scientist at Google Deep Mind, London, UK. Petros studied Naval Architecture (Diploma-NTU of Athens, M.Eng.-U. of Michigan), Aeronautics and Applied Mathematics (PhD-Caltech). He has conducted post-doctoral studies at the Center for Parallel Computing at Caltech and at the Center for Turbulent Research at Stanford University and NASA Ames. He has served as the Chair of Computational Science at ETHZ Zurich (1997-2020). Petros is elected Fellow of the American Society of Mechanical Engineers (ASME), the American Physical Society (APS), the Society of Industrial and Applied Mathematics (SIAM) and the Collegium Helveticum. He is recipient of the the ACM Gordon Bell prize in Supercomputing and the Advanced Investigator Award by the European Research Council and . He is elected International Member to the US National Academy of Engineering (NAE). His research interests are on the fundamentals and applications of computing and artificial intelligence to understand, predict and optimize fluid flows in engineering, nanotechnology, and medicine.