Martin SchrimpfExpertise
NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, startups [CV]
Mission
Modeling the brain: Martin's research focuses on a computational understanding of the neural mechanisms underlying natural intelligence in vision and language. To achieve this goal, he bridges Deep Learning, Neuroscience, and Cognitive Science, building artificial neural network models that match the brain’s neural representations in their internal processing and are aligned to
Cezar ZotaTeaching & PhD PhD Students Soujanya Madasu Past EPFL PhD Students as codirector Alberto Ferraris Courses Nanoscale MOSFETs and beyond CMOS devices MICRO-611 This course provides the trends in nanoelectronics for scaling, better performances and lower energy per function. It covers fundamental phenomena of nanoscale devices, beyond CMOS steep slope switches, emerging architectures, cryo electronics, non-volatile memories and energy efficient smart sensin
Lénaïc ChizatTeaching & PhD PhD Students Javier Esteban Maass Martinez Past EPFL PhD Students Guillaume Yitian Wang Courses Computational optimal transport MATH-528 Computational aspects of measure transportation, from classical optimal transport to modern denoising diffusion models. Topics in machine learning MATH-520 Mathematical analysis of modern supervised machine learning techniques, with an emphasis on the mathematics of artificial neural networks.
Giancarlo Ferrari TrecateExpertise
Automatic control, Dependable control, Neural-network Control, Machine learning, Microgrids, Hybrid systems
Mission
See the webpage of the DECODE (Dependable Control and Decision) group.
Teaching & PhD PhD Students Laura Meroi, Julien Pallage, Nicolas Léo Pierre Kirsch, Simone Baratto, Daniele Martinelli, Riccardo Cescon, Jakob Nylöf, Sabri El Amrani Past EPFL PhD Students Pulkit Nahata, Mustafa Sahin Turan, Baiwei Guo, Jean-Sébastien Brouillon, Clara Galimberti, Andrea Martin, Muhammad Zakwan,
Olga FinkTeaching & PhD PhD Students Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei Past EPFL PhD Students Ismail Nejjar, Mengjie Zhao Courses Data Science for infrastructure condition monitoring CIVIL-332 The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real
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
Marina Zapater SanchoTeaching & PhD PhD Students Karan Pathak, Qunyou Liu Past EPFL PhD Students as codirector Joshua Alexander Harrison Klein
Mathias SoekenTeaching & PhD Past EPFL PhD Students as codirector Winston Jason Haaswijk, Eleonora Testa, Giulia Meuli, Bruno Schmitt Antunes Courses Fault-tolerant quantum computing CS-630 The course explains how to execute scalable algorithms on fault-tolerant quantum computers. It describes error correction used to build reliable logical operations from noisy physical operations, and how quantum programs are mapped into logical operations sets taking into account layout constraints.
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
