Launch Your Career in the Dynamic Field of Robotics

STAND OUT FROM THE COMPETITION WITH A MASTER'S FROM NORTHWESTERN

In the next decade, robotic capabilities will advance quickly. Position yourself at the forefront of this rapidly growing field with a Master of Science in Robotics from Northwestern University.

Join us for an information session and learn how our one-year, interdepartmental program will allow you to build a strong portfolio of work and prepare for a diverse set of career options.

Related Info

Register Now

The Ted Belytschko Seminar

Algorithmic Alloys for Forecasting and Control of Complex Systems

Petros Koumoutsakos
Harvard University, Cambridge, MA
Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering

BIO
Petros Koumoutsakos is Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and currently on sabbatical as a Visiting Research Scientist at Google Deep Mind. He 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). He is recipient of the ACM Gordon Bell prize in Supercomputing and elected International Member to the US National Academy of Engineering (NAE). Research in his group explores the fundamentals and applications of computing and AI to understand, predict and optimize complex systems in engineering and medicine.

ABSTRACT
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 describe our decades long explorations on this space and discuss algorithmic alloys based on the fusion of data driven and equation driven methodologies for the prediction and control of complex flows. I will discuss in particular how particle based methods, as pioneered by Ted Belytschko, are today at the foundation of core Machine Learning tools such as graph neural networks. I will also present ideas of developing algorithmic alloys for fusing experiments and simulations for understanding and controlling complex systems.

ABOUT TED BELYTSCHKO
Treasured member of the Northwestern faculty from 1977 until his death in 2014, Ted Belytschko was a central figure in the McCormick community and an internationally renowned researcher who made major contributions to the field of computational structural mechanics. One of the most cited researchers in engineering science, Belytschko developed explicit finite element methods that are widely used in crashworthiness analysis and virtual prototyping in the auto industry. He received numerous honors, including membership in the U.S. National Academy of Engineering, U.S. National Academy of Science, and the American Academy of Arts and Sciences. He was a founding director of the U.S. Association for Computational Mechanics, and in 2012, the association named a medal in his honor. The ASME Applied Mechanics Award was renamed the ASME Ted Belytschko Applied Mechanics Division Award in November 2007. Belytschko also served as editor-in-chief of the International Journal for Numerical Methods in Engineering, and he was co-author of the books “Nonlinear Finite Elements for Continua and Structures” and “A First Course in Finite Elements.”

Thursday, October 23, 2025
3:00 The Hive 2-350 Ford
With Reception to follow in the Willens W