Clément Pit-ClaudelTeaching & PhD PhD Students Yawen Guan, Kacper Feliks Korban, Can Cebeci, Alexandre Pinazza, Shardul Chiplunkar Courses Interactive Theorem Proving Project CS-642 A project-focused introduction to interactive theorem proving. Interactive theorem proving CS-428 A hands-on introduction to interactive theorem proving, computer-checked mathematics, compiler verification, proofs as programs, dependent types, and proof automation.Come learn how to write computer-checked proofs an
Pawel DuchExpertise
My present research focuses on the intersection between probability theory, PDE theory and Euclidean quantum field theory. I am especially interested in problems involving singular stochastic partial differential equations and renormalization. I have also a background in mathematical aspects of perturbative and axiomatic quantum field theory as well as general relativity.
I am a postdoctoral researcher in the group of Martin Hairer. Previously, I was a postdoc at Adam Mickiewicz University in Pozn
Keivan Faghih NiresiExpertise
Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua Univer
Nicolas BoumalTeaching & PhD PhD Students Andreea-Alexandra Musat Past EPFL PhD Students Christopher Criscitiello, Quentin Rebjock Courses Continuous optimization MATH-329 This course introduces students to continuous, nonlinear optimization. We study the theory of optimization with continuous variables (with full proofs), and we analyze and implement important algorithms to solve constrained and unconstrained problems. Linear Algebra MATH-111(e) The purpose of the course is to introduce
Yuning JiangExpertise
Learning- and optimization- based policies for operating complex intelligent systems such as nonlinear autonomous systems (e.g., au- tonomous vehicles, robotics, and smart buildings) and large-scale multi-agent systems (e.g., power and energy systems, IoT and traffic networks).
Expertise
Learning- and optimization- based policies for operating complex intelligent systems such as nonlinear autonomous systems (e.g., au- tonomous vehicles, robotics, and smart buildings) and large-scale multi-agent sy
Maryam KamgarpourMaryam Kamgarpour holds a Doctor of Philosophy in Engineering from the University of California, Berkeley and a Bachelor of Applied Science from University of Waterloo, Canada. Her research is on safe decision-making and control under uncertainty, game theory and mechanism design, mixed integer and stochastic optimization and control. Her theoretical research is motivated by control challenges arising in intelligent transportation networks, robotics, power grid systems and healthcare. She is the recipient of NASA High Potential Individual Award, NASA Excellence in Publication Award, and the European Union (ERC) Starting Grant.
Wenjie XuI am currently a PhD student in Electrical Engineering in EPFL, working with Prof. Colin Jones. I received my MPhil from the Department of Information Engineering, The Chinese University of Hong Kong. I am fortunate to work with Prof. Minghua Chen during my MPhil research. Prior to that, I received my BEng in Electronic Engineering and (dual) BSc in Math, both from Tsinghua University in 2018.
Tony Alan WoodTony A. Wood received a B.Sc. degree in Information Technology and Electrical Engineering in 2010 and an M.Sc. degree in Robotics, Systems and Control in 2013, both from ETH Zurich, Switzerland. In 2018 he completed a Ph.D. at the Automatic Control Laboratory of ETH Zurich. From 2018 to 2021, he was a Research Fellow in the Department of Electrical and Electronic Engineering at the University of Melbourne, Australia. He is currently a Scientist in the Systems Control and Multiagent Optimization Research Group (Sycamore) at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. His research interests lie in the fields of optimisation and automatic control with a particular focus on multi-agent systems. The specific topics he investigates include system identification, task allocation, path planning, model predictive control, delay compensation, and formal specification satisfaction for uncertain systems encountered in applications such as energy systems, smart buildings, biology, and robotics.