Prof. Eleni Chatzi is a Full Professor and Chair of Structural Mechanics at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. She holds a PhD from Columbia University (2010) and has held roles from Assistant to Full Professor at ETH since 2010. Her research focuses on intelligent structural monitoring and data-driven asset management, emphasizing nonlinear dynamics and sensor integration. Affiliations : Institute of Structural Engineering, European Academy of Wind Energy (EAWE President), Swiss Community for Computational Methods (SWICCOMAS Chair) Research interests include Structural Health Monitoring (SHM), system identification, and advanced simulation tools. She pioneered work on data-driven diagnostics and self-aware infrastructure, supported by grants like the ERC Starting Grant (2015). Awards include the 2020 Walter L. Huber Prize and 2024 SHM Person of the Year Award. Her work spans wind energy infrastructure, metamaterials for vibration control, and AI-driven structural analytics. Over 600 publications and 200k+ citations highlight her impact. She teaches computational science and structural dynamics in ETH's programs and collaborates globally on sustainable infrastructure projects.
Dr. Igor V. Pivkin is a Full Professor at the Institute of Computing within the Faculty of Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His academic journey includes degrees from Novosibirsk State University (B.Sc./M.Sc. Mathematics), Brown University (M.Sc. Computer Science and Ph.D. Applied Mathematics), and postdoctoral research at MIT's Department of Materials Science and Engineering. His research focuses on multiscale/multiphysics modeling , numerical methods , and large-scale simulations of biological and physical systems. Key areas include biophysics, cellular/molecular biomechanics, stochastic modeling, and coarse-grained molecular simulations. He leverages high-performance computing (HPC) and particle-based methods to address complex biological phenomena. His work spans diverse applications, from understanding cellular mechanosensitivity and biofilm engineering to modeling cancer cell behavior and red blood cell dynamics in the spleen. His contributions bridge computational science, biotechnology, and biomedical research. He has published extensively in top-tier journals, with recent work advancing automated biofilm analysis, deep learning for microbial classification, and systems biology approaches to metal bioleaching. His lab collaborates on interdisciplinary projects, emphasizing computational innovation for real-world biological challenges.
Konstantinos Karapiperis is a Tenure Track Assistant Professor at EPFL's Laboratory of Multiscale Modeling of Materials (LMD), within the School of Architecture, Civil and Environmental Engineering (ENAC). His research integrates mechanics , multiscale modeling , and data science to study geomaterials and structural materials. PhD in Applied Mechanics (minor in Applied Mathematics), Caltech Postdoctoral Researcher & Lecturer, ETH Zürich (Marie Skłodowska-Curie Fellowship) Research focuses on granular materials , architected materials , and nonlocal modeling using techniques like Level-Set Discrete Element Method (LS-DEM) and machine learning . Recent work explores fracture control via graph neural networks and thermodynamics-informed models. Selected scientific award: Marie Skłodowska-Curie Fellowship Teaches courses in Soil Mechanics and Multiscale Modeling . PhD students include Thomas Henzel and Hrishikesh Gopakumar Menon. His Data-Driven Mechanics Laboratory (LMD) develops predictive tools for granular and structured material behavior.
Edward Andò is a Principal Scientist and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) , with affiliations to the IMAGING group and the College of Engineering (ENAC) . His work bridges software development, experimental geomechanics, and educational initiatives in image analysis. Principal Scientist, IMAGING-GE (EPFL) Lecturer, Sciences et Génie Civil (SGC-ENS) Lecturer, Enseignement à la Défense (EDEE-ENS) Research Interests Andò specializes in 3D image analysis , with a focus on X-ray tomography , digital volume correlation (DVC) , and micromechanical modeling of granular materials. His work addresses geomechanical failure mechanisms, soil dynamics, and open-source software tools like SPAM for practical material analysis. Publication Trends His recent articles (2025–2023) emphasize X-ray tomography for studying granular deformation , rock failure , medical imaging , and soft particle compaction . Topics span geomechanics, computational modeling, and software development for experimental validation. Labs and Teams Andò contributes to the IMAGING group at EPFL, where he co-develops the SPAM (Software for Practical Analysis of Materials) . His teaching includes courses like Fundamentals of Image Analysis and Quantitative Imaging for Engineers , which integrate hands-on training with theoretical frameworks.
Jan Carmeliet is a Full Professor at the Department of Mechanical and Process Engineering at ETH Zürich , holding the Chair of Building Physics since 2008. He previously held academic positions at Katholieke Universiteit Leuven and Eindhoven University of Technology . His research focuses on multiscale modeling of porous and granular materials , urban heat-air-moisture flows , and energy-efficient urban systems . His work integrates advanced computational techniques (e.g., lattice Boltzmann methods , CFD , FEM ) with experimental approaches ( X-ray tomography , wind tunnel PIV ). He leads major projects such as the RePoDH and Urban Multiscale Energy Modelling initiatives, aiming to decarbonize urban energy systems and understand local heat islands. Current projects emphasize renewable-powered district heating networks and urban climate modeling . Key collaborations include institutions like Empa , University of Illinois , and Los Alamos National Laboratory . He has secured significant grants from the Swiss National Science Foundation (SNSF) and ETH Domain , focusing on urban energy resilience and material science. His leadership roles include directing the Energy Science Center ETH Zürich and coordinating the SCCER-efficiency program.
Dr. Yinghe Qi is a Professor in the Department of Experimental Fluid Dynamics at ETH Zürich, Switzerland. His research focuses on multiphase flows, turbulence, and free-surface dynamics, with applications in aerospace, marine engineering, and computational fluid dynamics. He has contributed extensively to understanding bubble dynamics, flow instabilities, and turbulence modulation through experimental and phenomenological studies. Research Interests: Dr. Qi’s work addresses complex phenomena in multiphase flow instabilities free-surface turbulence deformable bubble dynamics supersonic jet interactions vortex-induced fragmentation machine learning in fluid dynamics Recent Publications: His recent studies (2023–2025) explore multiscale bubble deformation, free-surface turbulence structure, and supersonic jet-plume interactions. Key themes include turbulent fragmentation, vortex-bubble coupling, and novel computational methodologies. Laboratory Affiliations: He collaborates with the Coletti Group, Jenny Group, and Supponen Group at ETH Zürich, advancing experimental and computational techniques in fluid dynamics.
Jinghui Luo is a Research Professor and Principal Investigator at the Paul Scherrer Institute's Laboratory for Multiscale Bioimaging in Switzerland. Her research focuses on neurodegenerative diseases, particularly amyloid protein aggregation mechanisms. Luo's team investigates amyloid oligomers using nanopore engineering, cryo-electron microscopy, and single-molecule techniques to understand their role in Alzheimer's and Parkinson's diseases. Key research areas include α-synuclein phase separation, tau protein dynamics, and metal ion interactions with amyloid proteins. Her recent work demonstrates strong emphasis on protein oligomer characterization, liquid-liquid phase separation phenomena, and developing innovative trapping methods for single-molecule analysis. Publications consistently integrate structural biology with biophysical approaches. Luo has received prestigious awards including the NIH Director's Early Independence Award and Siebel Scholarship. She currently mentors six graduate students and postdoctoral researchers in her laboratory.
Matteo Dal Peraro is an Associate Professor at École polytechnique fédérale de Lausanne (EPFL) in the School of Life Sciences, where he leads the Laboratory for Biomolecular Modeling (LBM) within the Interfaculty Institute of Bioengineering (IBI). He also holds significant administrative roles as Head of IBI-SV Administration and Co-Director of IBI-STI Administration, demonstrating his leadership across both the School of Life Sciences and School of Engineering. His research bridges computational approaches with experimental validation to understand complex biological systems at multiple scales. His educational background includes a B.S. and M.S. in Physics from the University of Padua (2000), followed by a Ph.D. in Biophysics from the International School for Advanced Studies (SISSA) in Trieste (2004). He then completed postdoctoral training at the University of Pennsylvania under Professor M. L. Klein before joining EPFL as a Tenure Track Assistant Professor in late 2007. Dal Peraro's research focuses on computational biophysics and multiscale modeling of biological systems, with particular emphasis on membrane-protein interactions, nanopore sensing technologies, and structural biology. His work spans fundamental molecular mechanisms to applied educational technologies, demonstrating a commitment to both scientific discovery and knowledge dissemination. He has made significant contributions to understanding protein-membrane interactions, antibiotic resistance mechanisms, mitochondrial disorders, and viral pathogenesis through advanced computational approaches. His publication record shows a strong trend toward integrating augmented and virtual reality technologies with molecular modeling, exemplified by his development of the moleculARweb platform for chemistry and structural biology education. His research spans computational methods development, structural characterization of biomolecules, membrane biophysics, and applications to medically relevant problems including antibiotic resistance and neurodegenerative disorders. This interdisciplinary approach connects fundamental biophysical principles with practical applications in medicine and education. Dal Peraro has mentored numerous doctoral students through EPFL's PhD programs, particularly in Computational and Quantitative Biology. His leadership extends to serving on PhD program committees and directing research groups focused on computational molecular biology. He has established collaborations across multiple disciplines, facilitating integrative approaches to complex biological problems. He leads the Laboratory for Biomolecular Modeling (LBM), which develops and applies computational methods to study biological systems at multiple scales. The lab bridges molecular simulations with experimental validation, creating a synergistic approach to understanding complex biological phenomena. Dal Peraro's team has made significant contributions to membrane biophysics, protein folding, and the development of educational technologies that make structural biology accessible through augmented reality platforms.
Marco Stampanoni is a Full Professor for X-ray Imaging at the Department of Information Technology and Electrical Engineering, ETH Zürich, and leads the division for X-ray Imaging and Microscopy at the Institute of Biomedical Engineering. He also heads the X-ray Tomography Group at the Swiss Light Source (SLS), Paul Scherrer Institut, Switzerland. Education : Physics (ETH Zurich, 1998-2002) Key Research Areas : Phase Contrast X-ray Imaging, Realtime Tomographic Microimaging, Nano-tomography, Novel Radiological Methods, Non-Destructive Testing His work bridges cutting-edge synchrotron technologies with clinical applications, focusing on novel X-ray instruments for multiscale non-invasive analysis. He has secured an ERC Grant and received multiple awards for his pioneering research. ETH Silver Medal (2003) Dalle Molle Foundation Award (2012) Finalist, European Inventor Award (2022) Giuseppe Sciacca International Award (2022) He teaches X-ray microscopy at ETH Zurich and has held leadership roles, including Director of the ETH Master of Advanced Studies in Medical Physics (2010-2013) and President of the Paul Scherrer Institut Research Commission (since 2018).
Georg Spinner is a Lecturer and Head of the Research Group for Medical Image Analysis & Data Modelling at the Institute of Computational Life Sciences, Zurich University of Applied Sciences (ZHAW). His work integrates computational methods with biomedical research, focusing on stroke management, intracranial aneurysm risk modeling, and quantitative medical imaging. Primary affiliation: Zurich University of Applied Sciences Research focus: Bayesian networks, medical imaging, computational epidemiology Projects: GEMINI (digital twins for stroke), Stroke DynamiX (causal networks in stroke care), IVIM muscle activation studies Using Bayesian networks and advanced imaging techniques like IVIM DWI, his research aims to develop data-driven decision support systems for neurovascular diseases. He has contributed to modeling stroke health data and intracranial aneurysm risk stratification through international multicenter collaborations. His work spans computational biology, neuroinformatics, and digital health, with publications in journals like Medical Image Analysis and conferences including the International Conference on Computational and Mathematical Biomedical Engineering. Key methodologies include causal inference, dynamic disease modeling, and quantitative image analysis.
Antoine Sanner is a Researcher affiliated with the Institute of Construction Materials (Institute of Building Materials) at ETH Zurich, part of the College of Architecture, Civil and Environmental Engineering. His work focuses on computational mechanics of building materials, surface topography analysis, and adhesion science. He co-developed the dtool and dserver systems to enhance FAIR data practices in research. Research interests include the structural behavior of cement-based materials, mechanisms of material adhesion under varying surface conditions, and multiscale analysis of surface roughness effects. He has also contributed to engineering tools for characterizing surface topography across scales, emphasizing the creation and use of 'digital surface twins' for material studies. His publications consistently explore topics at the intersection of materials science and mechanical engineering, with recent work advancing understanding of surface adhesion dynamics and cement curing processes. No scientific awards are explicitly mentioned in the provided texts. As part of the Professorship for Computational Mechanics of Building Materials, Antoine contributes to research infrastructure and computational methods development. He has no listed advisees or grants, and his role appears to be full-time with no indication of part-time status. He collaborates on projects involving advanced materials characterization, particularly in polycrystalline diamond coatings and bearing component analysis, leveraging both experimental and computational methodologies.
Dr. John Provis is the Group Leader for Cement Systems at the Paul Scherrer Institute (PSI) in the Laboratory for Waste Management (LES). He holds a PhD in Chemical Engineering from the University of Melbourne, Australia, and was previously the Professor of Cement Materials Science and Engineering at the University of Sheffield, UK (2012–2023). His research focuses on cement chemistry, sustainable construction materials, and nuclear waste management, with a strong emphasis on standardization and beamline analysis. Provis has authored over 300 journal articles and secured major grants, including an ERC Starting Grant. He is a Fellow of multiple prestigious societies and has received awards such as the RILEM Robert L'Hermite Medal and a Doctor Honoris Causa from Universiteit Hasselt. He has supervised over 100 PhD/postdoc researchers and serves as an editorial board member for journals like Cement and Concrete Research and Materials and Structures . His research interests span cement durability, geopolymer development, and the environmental impact of construction materials. Provis also advises governments and agencies globally on funding and policy, contributing to projects like the Hanford Nuclear Reservation review. His work bridges academic research with industrial applications, emphasizing innovation in low-carbon materials and waste management solutions.
Emiliya Poghosyan is a Senior Scientist at the Paul Scherrer Institute (PSI) in Switzerland, affiliated with the Laboratory for Multiscale Bioimaging and the Electron Microscopy Facility. Since 2018, she provides user support, training, and manages advanced electron microscopy equipment while developing biological imaging methodologies. Her educational background includes: Bachelor of Science in Physics (with honours) from Yerevan State University Master's Degree in Nano-biophysics from Technical University of Dresden PhD in Cryo-electron microscopy from ETH Zurich Postdoctoral work on single particle cryo-EM of membrane proteins at University of Basel Her research focuses on cryo-electron microscopy techniques, structural biology, and membrane protein imaging. Recent publications highlight advancements in ptychography tools, X-ray tomography, and deep learning applications for electron microscopy. She actively contributes to method development and facility management. Scientific achievements include DAAD Long-Term Fellowships (2010-2012), PSI Research Grants (2021), and SDSC Collaborative Data Science Projects. She is a member of the Swiss Society for Optics and Microscopy (SSOM) and has delivered lectures at the University of Zurich (PHY 427). Teaching roles span multiple international cryo-EM schools and hands-on training programs since 2018, emphasizing practical microscopy education.
Franceschiello Benedetta is an Associate Professor at HES-SO Valais-Wallis School of Engineering, specializing in Technical and IT disciplines. She holds a PhD in Mathematical Neuroscience from Université Pierre et Marie Curie (Paris). Her work bridges applied mathematics, computational neuroscience, and neuroimaging, with a focus on visual perception modeling, MRI techniques, and neural dynamics. Teaching: Linear Algebra courses across multiple engineering bachelor programs Expertise: Combines mathematical modeling with neuroscientific applications to study optical illusions, brain connectivity, and ophthalmic diagnostics Key Affiliations: ISMRM, Organization for Human Brain Mapping (OHBM), Association for Research in Vision and Ophthalmology (ARVO) Research Interests: Computational modeling of visual cortex mechanisms underlying geometric optical illusions Development of MRI-based methods for eye structure segmentation and axial length estimation Analysis of brain network reliability through standardized MRI protocols Optimization techniques for medical imaging reconstruction (e.g., weighted LASSO problems) Recent Work Trends: Focus on integrating psychophysical experiments with computational models to elucidate perceptual mechanisms, emphasizing synergistic interactions between physical stimulus parameters. Active in advancing MRI applications for both clinical diagnostics and fundamental neuroscience research.
Igor V. Pivkin is a full professor at the Institute of Computing within the Faculty of Informatics at the University of Lugano (USI). He holds a B.Sc. and M.Sc. in Mathematics from Novosibirsk State University, followed by an M.Sc. in Computer Science and a Ph.D. in Applied Mathematics from Brown University. Before joining USI, he was a Postdoctoral Associate at MIT's Department of Materials Science and Engineering. His research focuses on multiscale/multiphysics modeling , numerical methods, and large-scale simulations of biological and physical systems. Key areas include biophysics, cellular/molecular biomechanics, stochastic modeling, and coarse-grained molecular simulations. He leverages high-performance computing and particle-based methods to address complex biological phenomena. His work spans diverse applications, including cancer cell dynamics, bioleaching bacterial biofilms, and erythrocyte mechanics in human spleen circulation. He has pioneered computational tools such as the Bayesian recursive global optimizer (BaRGO) and the in-silico lab-on-a-chip framework, enabling petascale simulations of microfluidic systems at cellular resolution. Pivkin collaborates extensively with institutions like the SIB Swiss Institute of Bioinformatics and has contributed to advancing methodologies for multi-model scientific simulations. His research integrates experimental data with computational models to bridge gaps between microscopic and macroscopic biological processes.
