Antoine BosselutAntoine Bosselut is an assistant professor at EPFL. He leads the EPFL NLP group, which conducts research on natural language processing (NLP) systems that can model, represent, and reason about human and world knowledge.
Prior to joining EPFL, he was a postdoctoral researcher at Stanford University working in the
SNAP
and
NLP
groups and a young investigator on the
Mosaic
project at the
Allen Institute for AI
. He completed his PhD at the University of Washington.
Zsuzsanna Viktoria SzemerediTeaching & PhD Courses Critical thinking I HUM-425 This course will develop logical reasoning and argumentation skills to enable you to influence decision making. You will achieve this by learning how to represent and communicate your reasoning as arguments, and by continuously practicing logical reasoning and problem solving in teams. Critical thinking II HUM-484 Critical Thinking II (HUM 484) builds on concepts acquired in Critical Thinking I (HUM 425). Please read HUM
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
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
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
Siba Smarak PanigrahiExpertise
Geometric Deep Learning, Generative Models
I am a Ph.D. at école Polytechnique Fédérale de Lausanne (EPFL) working with Prof. Maria Brbic in the Brbic Lab. My research interests span geometric deep learning, generative models, and computer vision.Previously, I was a visiting researcher at ServiceNow Research in the Multimodal Foundation Models team, building foundation model for structured document understanding. I was also a Research Intern at PROSE at Microsoft, working on designing algorithms a
Juan Pablo Zuluaga GomezJuan Pablo Zuluaga is currently working at IDIAP as a joint Ph.D. student (second year) with the École polytechnique fédérale de Lausanne, Switzerland. He is currently working on the EU Horizon 2020 ATCO2 project, dedicated to the development of an Automatic Air Traffic Speech Recognition system, allowing to collect, organize and pre-process air traffic control (voice communication) data from air space. His main interests are automatic speech recognition and speech understanding. Also interested in artificial general intelligence and natural language processing.
Tanja Christina Käser JacoberTanja Käser is an assistant professor at the EPFL School of Computer and Communication Sciences (IC) and head of the D-VET laboratory. Her research lies at the intersection of machine learning, data mining, and education. She is particularly interested in creating accurate models of human behavior and learning.Prior to joining EPFL, Tanja Käser was a senior data scientist with the Swiss Data Science Center at ETH Zurich. Before that, she was a postdoctoral researcher with the AAALab at the Graduate School of Education of Stanford University.
Tanja Käser received her PhD degree from the Computer Science Department of ETH Zurich. In her dissertation, completed at the Computer Graphics Laboratory, she focused on user modeling and data mining in education, which was honored with the Fritz Kutter Award 2015.
