Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
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
Adriano MeleEnseignement et PhD Cours Control and Operation of Tokamaks PHYS-748
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
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
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•
Michail VlachosEnseignement et PhD Cours Data science and machine learning MGT-502 Introduction pratique à la science des données et à l'apprentissage automatique. Nous abordons les systèmes de recommandation, l'IA générative, les chatbots, les graphes, ainsi que la régression, la classification, l'analyse de texte et les réseaux neuronaux. Programmation en Python.
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.
Han SunExpertise
Deep Learning, Computer Vision, Domain Adaptation, Generative Modeling
Open Projects:
Test-Time Domain Adaptation for Anomaly Detection: SiROP link for detailed information
Han obtained her master's degree in Geomatic from the Federal Institute of Technology in Zürich (ETHZ). Before joining IMOS Lab - EPFL, she focused on computer vision with a particular interest in domain adaptation & style adaptation. During her Ph.D. study, she will explore more in the field of domain adaptation with its appli
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
Mohammad Ali ShaeriExpertise
Neural Engineering, Neural Signal Processing, Neural Decoding, Neural Prosthesis, Brain Machine Interface
Jiancheng YangI am a 4th-year PhD student in the Department of Electronic Engineering, Shanghai Jiao Tong University, advised by Prof. Bingbing Ni. I received BEng and MEng degree in the Department of Automation from the same university. Enrolled in a double master degree program, I spent 2 years in France with an Engineer degree. I was a visiting research fellow in Visual Computing Group at Harvard University. I am now visiting EPFL CVLAB, working with Prof. Pascal Fua.I focus on medical image analysis, 3D computer vision and trustworthy machine learning, with a clinical emphasis on lung cancer and thoracic diseases. I have (co-)first-authored more than 10 papers on top-tier journals / conferences, e.g., Cancer Research, CVPR, MICCAI and NeurIPS. I was a reviewer for more than 10 prestigious venues, a top-ranking participant for several AI competitions, and the lead organizer for MICCAI 2020 RibFrac Challenge.Updated on April, 2021.
Wenlong LiaoExpertise
deep learning, power system, renewable energy, data analysis
Mirko MarrasMirko Marras was born on April 19, 1992 in Iglesias (Italy). He is a Postdoctoral Researcher at the Digital Vocational Education and Training • Machine Learning for Education Laboratory of EPFL - Swiss Federal Institute of Technology in Lausanne (Switzerland). He received a PhD in Computer Science in 2020 and a MSc Degree in Computer Science (summa cum laude, 18 months) in 2016, from University of Cagliari (Italy). He received the Computer Science Engineering certification from the University of Pisa (Italy) in 2016.
In 2015, he was involved as Researcher within UnitelCagliari (Italy) for the ELIOS project (MIUR, 1ME). In 2017, he spent five months as Visiting Scholar at EURECAT (Spain), collaborating with the Data Science and Big Data Analytics Unit on the DECODE project (EU, 16P, 5ME). In 2018, he spent three months as Visiting Scholar within the University Institute for Intelligent Systems and Digital Applications in Engineering (SIANI) at the Universidad de Las Palmas de Gran Canaria (Spain). In 2019, he spent two months at the Department of Computer Science and Engineering of the New York University: Tandon School of Engineering (U.S.A). He has been involved as Researcher in the ILEARNTV project (MIUR, 6P, 10ME) since 2018. From 2019, he is referral of the University of Cagliari (Italy) for two work packages under the EDUC project (EU, 6P, 5ME). He has been teaching assistant for the “Computer Networks” course since 2017 and thesis assistant since 2018 at the University of Cagliari (Italy).
In 2014, he was recognized as the best third-year student of the BSc Program in Computer Science of the University of Cagliari (Italy). In 2016, he was recognized as the best MSc student of the Faculty of Science and one of the top 12 MSc students of the same University. In 2018, he got to the podium of the Call for Visionary Ideas - Education Section event organized by Nesta Italia. He has received the Best Poster Award at the European Semantic Web Conference 2017 (ESWC2017), the Demo Honorable Mention at The Web Conference 2018 (WWW2018) and the Best Paper Award at Didamatica Conference 2018. He has been awarded two Erasmus PlaceDoc scholaships to spend 5 months at EURECAT (Spain) and 3 months at Universidad de Las Palmas de Gran Canaria (Spain), respectively. Moreover, he has been awarded a GlobusDoc scholarship to spend 2 months at New York University: Tandon School of Engineering (U.S.A).
His current research focuses on Data Mining and Machine Learning with a focus on Education. He has co-authored papers in top-tier international journals, such as Pattern Recognition Letters (Elsevier), Computers in Human Behavior (Elsevier), Information Processing & Management (Elsevier), and IEEE Cloud Computing. His research activity also brought him to give talks (e.g., ECIR 2019 and INTERSPEECH 2019), demos (e.g., TheWebConf 2018 and AVI 2020), and tutorials (e.g., UMAP 2020 and ICDM 2020) at several international conferences. He is part of the program committee of main international conferences, such as ACL, AIED, ECML-PKDD, EDM, EMNLP, ITICSE, INTERSPEECH, ICALT, and UMAP. He has been also acting as a reviewer for top-tier journals, such as Pattern Recognition Letters and IEEE Transactions on Image Processing. He has been also co-chairing the BIAS@ECIR2020 and BIAS@ECIR2021 workshops. He has served as a guest editor for a special issue of Information Processing & Management (Elsevier) and Future Generation Compter Systems (Elsevier). He has been involved in several national and European projects (e.g., iLearnTV, DECODE, EDUC). He is a member of several national and international associations, including CVPL, AIxIA, IEEE, and ACM.
Sebastian Jonas NeumayerExpertise
Applied Analysis, Data Science, Inverse Problems, Mathematical Imaging, Variational Methods
Expertise
Applied Analysis, Data Science, Inverse Problems, Mathematical Imaging, Variational Methods
