Mathias Josef PayerMathias Payer is a security researcher and professor at the EPFL school of computer and communication sciences (IC), leading the HexHive group. His research focuses on protecting applications in the presence of vulnerabilities, with a focus on memory corruption and type violations. He is interested in software security, system security, binary exploitation, effective mitigations, fault isolation/privilege separation, strong sanitization, and software testing (fuzzing) using a combination of binary analysis and compiler-based techniques. More details are available in his CV.
Ali H. SayedAli H. Sayed is Dean of Engineering at EPFL, Switzerland, where he also leads the Adaptive Systems Laboratory. He has also served as Distinguished Professor and Chairman of Electrical Engineering at UCLA. He is recognized as a Highly Cited Researcher and is a member of the US National Academy of Engineering. He is also a member of the World Academy of Sciences and served as President of the IEEE Signal Processing Society during 2018 and 2019.
Dr. Sayed is an author/co-author of over 570 scholarly publications and six books. His research involves several areas
including adaptation and learning theories, data and network sciences, statistical inference, and multiagent systems.
His work has been recognized with several major awards including the 2022 IEEE Fourier Award, the 2020 Norbert Wiener Society Award and the 2015 Education Award from the IEEE Signal Processing Society, the 2014 Papoulis Award from the European Association for Signal Processing, the 2013 Meritorious Service Award and the 2012 Technical Achievement Award from the IEEE Signal Processing Society, the 2005 Terman Award from the American Society for Engineering Education, the 2005 Distinguished Lecturer from the IEEE Signal Processing Society, the 2003 Kuwait Prize, and the 1996 IEEE Donald G. Fink Prize. His publications have been awarded several Best Paper Awards from the IEEE (2002, 2005, 2012, 2014) and EURASIP (2015). He is a Fellow of IEEE, EURASIP, and the American Association for the Advancement of Science (AAAS); the publisher of the journal Science.
Michele VidulisExpertise
Geometric Computing, Geometry Processing, Optimization, Physics-based Simulation
Education Master of Science in Computational Science and Engineering | 2018 – 2021 Polytechnic University of Milan and EPFL Bachelor of Science in Mathematical Engineering | 2015 – 2018 Polytechnic University of Milan
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
Alexandre Sébastien Julien WillommetEducation 3D high density memory based on emering resistive technologies : circuit and architecture design | Microelectronics 2014 – 2017 CEA-Leti
Teaching & PhD Courses Fundamentals of VLSI design EE-429 The course introduces the fundamentals of digital integrated circuits and the technology aspects from a designers perspective. It focuses mostly on transistor level, but discusses also the extension to large digital semicustom designs. Lab in advanced VLSI design
Haitham Al HassaniehTeaching & PhD PhD Students Eduard Vlad, Raphael Cannatà, Arman Maghsoudnia, Jiachen Lu, Samah Hussein Youssef, Hailan Zhang Shanbhag, Aoyu Gong Courses Intelligent systems: communications & AI COM-304 The course teaches the development of systems that solve real-world challenges in communications, signal processing, foundation models, and AI. Students will work in teams, construct their ideas, and either program available hardware prototypes or build their hardware or software system.
Lazar MilikicExpertise
LLMs (Large Language Models), NLP (Natural Language Processing), Automated Reasoning
Mission
My work focuses on developing robust methods for autoformalization and automated theorem proving using large language models. I aim to enhance the reasoning reliability of modern AI systems by reducing hallucinations, improving predictability, and integrating formal verification techniques and tools into LLM-based pipelines.
Before joining EDIC, I completed a Bachelor’s in Mathematics and Computer Science
