Events Calendar

AME Seminar

Speaker: Evangelos Theodorou , Georgia Institute of Technology

Abstract: In this talk, I will present use cases for stochastic optimal control that span the areas of terrestrial high-speed navigation, control of VTOL vehicles for urban aerial mobility, large-scale multi-agent control, training of score-based models in generative AI, opinion dynamics depolarization and single cell RNA sequencing. The presentation will cover fundamental concepts in stochastic control theory that includes path integrals, Forward-Backward SDEs and Schrodinger Bridges, and highlight the importance of scalable optimization for large scale and real time decision-making. In the last part of the talk, we will look into different distributed optimization architectures for large-scale optimal control and conclude with future directions and vision at the intersection of autonomy, generative AI and large-scale optimization.

Biography: Evangelos A. Theodorou is an Associate professor with the Guggenheim School of aerospace engineering at Georgia Institute of Technology and Amazon CORE-AI Scholar. He is also the director of the Autonomous Control and Decision Systems Laboratory, and he is affiliated with the Institute of Robotics and Intelligent Machines and the Center for Machine Learning Research at Georgia Tech. Evangelos Theodorou holds a BS in Electrical Engineering, from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California(USC) in Spring 2010. In May of 2011 he graduated with his PhD, in Computer Science from USC. After his PhD, he was a Postdoctoral Research Fellow with the department of computer science and engineering, University of Washington, Seattle. Evangelos Theodorou is the recipient of the King-Sun Fu best paper award of the IEEE Transactions on Robotics in 2012 and a recipient several best paper awards and nominations in top conferences in machine learning and robotics communities. His theoretical research spans the areas of stochastic optimal control theory, machine learning and optimization. Applications involve learning, planning and control in autonomous, robotic and aerospace vehicles, multi-agent and large-scale systems, and dynamical systems in social sciences and biology.

Host: AME Department

More Info: https://ame.usc.edu/seminars/

Webcast: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8

Location: Seaver Science Library (SSL) - 202

WebCast Link: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8

Audiences: Everyone Is Invited

Contact: Tessa Yao

Event Link: https://ame.usc.edu/seminars/