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.
Vinay SharmaExpertise
Computational Mechanics, Graph Machine Learning.
Lin DuLin Du obtained her BSc in Electronic Information Engineering and her MSc in Information and Communication Engineering respectively from Beijing Institute of Technology, China.From December 2022, she joined Integrated Circuits Laboratory (ICLAB) at EPFL. She is studying for her PhD in Electrical Engineering focusing on machine learning algorithms for drug concentration estimation from data acquired by the sensors. The PhD project is co-supervised by Prof. Sandro Carrara (EPFL) and Prof. Yann Thoma (HEIG-VD)
Sayan BiswasExpertise
Decentralized Machine Learning and Federated Learning focusing on Privacy, Fairness, and Personalization; Secure and Trustworthy Distributed Systems; Differential Privacy; Location Privacy.
Sayan Biswas (CV) is a Postdoctoral Researcher in the Scalable Computing Systems (SaCS) lab at EPFL, Switzerland, led by Prof. Anne-Marie Kermarrec. He completed his PhD in Computer Science at INRIA and école Polytechnique in France, under the supervision of Prof. Catuscia Palamidessi. Prior to that, Sayan stud
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
Andrea CavalliTeaching & PhD PhD Students Alessia Ghidini Courses Drug Discovery CH-630 The course gives an overview of drug discovery. Computational methods in drug design and discovery, including methods for free energy and residence time, drug-target interactions, pharmacodynamics, pharmacokinetics, and drug delivery,biophysical methods, interaction including ITC, SPR, MST, and NMR.
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
Cyrus Thibault LognonnéCyrus Lognonné-Khalatbari is an artist, designer and PhD candidate of the joint program between the Geneva Arts and Design University (HEAD & Genève, HES-SO) and the Swiss Federal Institute of Technology (EPFL). Inside his PhD, Cyrus bridges ethnographic fieldwork, Science and Technology Studies (STS) with arts and design methodologies in order to address, at the level of the Graphical Processing Unit (GPU), the ecological implications of computing power and the digital. Cyrus' research has been published b
