Nako NakatsukaMission
At the Laboratory of Chemical Nanotechnology (CHEMINA), our mission is to develop translational chemical biosensing technologies that advance human health. Working at the intersection of chemistry, engineering, and neuroscience, we seek to probe the dynamic chemical landscape of biological systems across in vitro systems, in vivo models, and human clinical samples. We develop novel biorecognition elements and innovate biosensing platforms to enable monitoring of small molecules in complex biofluids,
Mykhailo BatiukExpertise
Single cell and spatial genomics (wet/dry lab), glia, psychiatry, neuroscience
I obtained my PhD (2012-2018) in KU Leuven/VIB, Belgium where I investigated astrocyte heterogeneity using single cell transcriptomics. During this period I developed tools to acutely and specifically isolate astrocytes from adult brain and identified five astrocyte subtypes in the cortex and hippocampus of mouse brain expanding previous understanding of astrocyte variability.Following my PhD, I did my first post-doc in
Vittorio ErbaTeaching & PhD Courses Statistical physics of computation PHYS-512 The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning.
Konstantinos KarapiperisKostas Karapiperis is an Assistant Professor at EPFL directing the Data-Driven Mechanics Laboratory (LMD). His research lies at the intersection of mechanics, multiscale modeling, and data science, with applications ranging from geomaterials to structural materials. Prior to EPFL, he worked as a Postdoctoral Researcher and Lecturer at the Department of Mechanical and Process Engineering of ETH Zürich, supported by a Marie Sklodowska-Curie Fellowship. He holds a PhD in Applied Mechanics and a Minor in Applie
Amine BenouhibaAmine Benouhiba graduated from the Preparatory School of Science and Technology, Algeria, in 2012. He received his engineering degree in material engineering from Ecole Nationale Polytechnique (ENP), Algeria, in 2015. He also received his master’s degree in innovative materials from Ecole centrale de Lyon (ECL) in 2016. He completed his Ph.D. degree in 2020 at the Bourgogne-Franche-Comté University. Currently, he is a postdoctoral researcher at Ecole polytechnique fédérale de Lausanne (EPFL). His research interests include the design and development of soft robotics, origami-inspired structures and microrobotics.
Iegor VlasenkoIegor (Yegor) Vlasenko (he/him) is a researcher in urban studies and planning with a Master of Science degree in Urban Studies from Malmo University (2017). Since April 2023, he is a Doctoral Assistant and PhD student in Architecture and City Sciences at the Laboratory of Urbanism, EPFL, working on the dissertation entitled «Decentralisation as an Agent of Resilience? Comprehending Urbanisation and Wartime Planning in Ukraine». He is also serving as a Communications Assistant of the Doctoral Program in Arch
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