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
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
Alexander DittrichCurrent Work
My research interests are somewhere between neural networks with Hebbian plasticity, meta-reinforcement learning, and the control of rather unconventional soft robotic platforms like tensegrity robots.
Geovani RizkExpertise
Distributed Machine Learning, Robustness, Safety, Optimization, Multi-Agent, Bandits in Graphs
I am a postdoctoral researcher at école Polytechnique Fédérale de Lausanne since 2022, where I work with Rachid Guerraoui on robustness of distributed machine learning algorithms. From 2018 to 2022, I completed my Ph.D. in computer science at Université Paris Dauphine-PSL on multi-agent bandits in graphs under the supervision of Yann Chevaleyre, Rida Laraki, Igor Colin, and Albert Thomas.Pre-prints Over
Zepeng ZhangZepeng is a PhD student at École Polytechnique Fédérale de Lausanne (EPFL). He works in the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink. Previously, He received his master’s degree at ShanghaiTech University and B.Eng. degree from Wuhan University (WHU). During his studies, he have visited Télécom Paris, Institut Polytechnique de Paris (IP Paris), Peking University (PKU), and City University of HongKong (CityU) as a research intern. His current research
Simon Elias BibriExpertise
• Sustainable cities• Smarter eco-cities• Sustainable smart cities• Artificial Intelligence of Things (AIoT) • Generative Artificial Intelligence of Things (GAIoT)• Foundation Models (FMs) • Quantum Generative Artificial Intelligence (QGAI)• Urban Digital Twins (UDTs)• Urban Brain (UB) • Smart Circular Metabolism• Urban planning and design• Environmental sustainability and climate resilience• Sustainable smart energy• Sustainable smart transportation• Sustainable smart waste and water management•
Michael HerbstExpertise
For more information about our research, see https://matmat.org/research/.
Teaching & PhD PhD Students Niklas Frederik Schmitz, Anna Paulish, Bruno Ploumhans, Benedikt Menges Courses Error control in scientific modelling MATH-500 Errors are ubiquitous in computational science as neither models nor numerical techniques are perfect. With respect to eigenvalue problems motivated from materials science and atomistic modelling we discuss, implement and apply numerical techniques for e Vinay SharmaExpertise
Computational Mechanics, Graph Machine Learning.
Radoslav MarchevskiTeaching & PhD PhD Students Jou An Chen, Tobias Alexandre Monnard, Xiafei Chang, Gauri Napoletano, Kerim Guseinov, Noémie Duc Courses Particle physics I PHYS-415 Presentation of particle properties, their symmetries and interactions.Introduction to quantum electrodynamics and to the Feynman rules. Particle physics: the flavour frontiers PHYS-471 This course will present experimental aspects of flavour physics primarily in the quark sector but also in the lepton sector and
Xinxin LiaoXinxin Liao received the B.S. and Ph.D. degrees in instrument science and technology from the University of Science and Technology of China, Hefei, China, in 2015 and 2020, respectively. After that, he was a postdoctoral fellow with the Institute of Vibration Shock & Noise, Shanghai Jiao Tong University, Shanghai, China. He is currently a postdoc/scientist in LAI, STI, EPFL working on ultrasonic motor optimization. His research interests include smart piezoelectric actuators and sensors, robotics, piezoelec
Caglar GulcehreTeaching & PhD PhD Students Tim Ruben Davidson, Skander Moalla, Anja Surina, Xiuying Wei, Liangze Jiang, Mikhail Terekhov, Amin Mansouri, Justin Samuel Deschenaux, Yitao Xu Courses Training Large Language Models EE-628 This PhD-level course dives deep into the training of Large Language Models (LLMs), focusing on the complementary roles of datasets, pre-training and post training methodologies in shaping model performance and scalability.
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
Wenlong LiaoExpertise
deep learning, power system, renewable energy, data analysis
Davide TisiGraduated in Physics from University of Modena and Reggio Emilia, Italy. He earned his PhD in SISSA under the supervision of Prof. Stefano Baroni, working on the computation of transport properties of liquids from ab initio approach and neural-network potentials. He joined COSMO as a postdoc in 2022 and he is currently working on simulations of Li-based solid state electrolytes for battery materials.
