Prof. Marcy Zenobi-Wong is a Full Professor at ETH Zurich's Department of Health Sciences and Technology, specializing in biofabrication and tissue engineering. Her research focuses on cartilage regeneration using advanced biomaterials, including nanofilm coatings and 3D printing techniques. She holds patents in tissue engineering and has pioneered methods like filamented light (FLight) biofabrication for creating anisotropic tissues. Her academic journey includes a B.Sc. from MIT (1985), M.Sc. and Ph.D. from Stanford (1987, 1990), followed by postdoctoral work at the University of Michigan. She leads the Biofabrication Group at ETH, developing therapies for joint repair and regenerative medicine. Courses taught include Biomedical Engineering and Materials and Mechanics in Medicine . Research highlights include engineered hydrogels for cartilage protection, CRISPR-driven gene editing in chondrocytes, and biohybrid neural interfaces. Her work bridges material science, cell biology, and clinical applications, with a focus on translational medicine. Collaborative projects involve creating elastic cartilage grafts for microtia reconstruction and volumetric printing of complex tissue constructs.
Prof. Olga Sorkine Hornung is a Full Professor of Computer Science at ETH Zürich, leading the Interactive Geometry Lab. She holds a BSc and PhD from Tel Aviv University (2000 and 2006) and conducted postdoctoral research at Technical University Berlin. Her research focuses on computer graphics, geometric modeling, and geometry processing, with applications in shape editing, digital fabrication, and animation. She has received numerous accolades, including the ACM Fellowship (2020), ERC Consolidator Grant (2020), and the Golden Owl Teaching Award (2021). Her work bridges theoretical foundations and practical algorithms, addressing challenges in parameterization, surface compression, and interactive design tools. Her research interests span: Computer Graphics & Visualization Geometric Modeling & Processing 3D Content Creation & Digital Fabrication Garment Design & Simulation Human Motion Analysis & Animation Awards and grants include: 2024: Best Paper Honorable Mention (EUROGRAPHICS) 2023: Member of Swiss Academy of Engineering Sciences (SATW) 2020: ERC Consolidator Grant 2017: Rössler Prize (ETH Zurich) Her lab focuses on developing novel methods for interactive geometry processing, with recent advancements in garment modeling (e.g., AIpparel, Rags2Riches) and motion retargeting systems like WalkTheDog. She actively collaborates on interdisciplinary projects, including biomedical applications and sustainable fashion technology.
Prof. Knut Drescher is an Associate Professor at the Biozentrum, University of Basel , leading a research group focused on bacterial biofilms , swarming , and microbial multicellularity . Previously, he served as a Professor of Biophysics and Max Planck Research Group Leader at Philipps-Universität Marburg (2015-2021) and conducted postdoctoral research at Princeton University. Research Interests: Physical and biological mechanisms of biofilm formation Cell-cell interactions in microbial communities Antibiotic resistance in biofilms Hydrodynamics of bacterial swarms Evolution of cooperation in multispecies biofilms Development of bioimaging software (BiofilmQ, BacStalk) Scientific Awards: 2023: SNSF Consolidator Grant 2019: Heinz Maier-Leibnitz Prize (DFG), VAAM Research Prize, IUPAP Young Scientist Prize 2016: ERC Starting Grant Advising & Grants: Advises PhD and Master's students in microbiology, biophysics, and bioinformatics Secured major grants from ERC , HFSP , and DFG
Prof. Dr. Johan Robertsson is a Full Professor of Applied Geophysics and Head of the Exploration and Environmental Geophysics (EEG) Group at ETH Zürich's Department of Earth and Planetary Sciences. He holds a MSc from Uppsala University (1991) and a PhD in Geophysics from Rice University (1994). Before joining ETH in 2012, he spent 15 years at Schlumberger in R&D roles, leading projects that revolutionized marine seismic data acquisition. His research focuses on wave propagation physics, seismic data inversion, and applications in exploration and environmental geophysics. He pioneered the use of Distributed Acoustic Sensing (DAS) for landslide monitoring and contributed to Mars seismology via the InSight mission. Education: MSc in Engineering Physics, Uppsala University (1991) PhD in Geophysics, Rice University (1994) Research Interests: Seismic wavefield modeling and inversion Planetary seismology (Mars, Moon) Acoustic metamaterials and wave control Environmental geohazard monitoring Marine seismic acquisition techniques His work on the Martian soil properties using InSight data and lunar exploration instrumentation (ALGEP) reflects his cross-disciplinary approach. He holds 90+ patents and has secured prestigious grants like the ERC Advanced Grant. Awards: EAGE Guido Bonarelli Award (2020) ERC Advanced Grant MATRIX (2017) EAGE Conrad Schlumberger Award (2018) Grants & Advising: Led the MATRIX ERC project advancing seismic imaging algorithms Advised over 20 PhD/MS students (names not listed) Secured Schlumberger's largest R&D project in marine seismic sampling His EEG Group operates cutting-edge labs for immersive wave experimentation and planetary geophysical instrumentation. Current initiatives include lunar subsurface exploration and acoustic invisibility experiments.
Dr. Parth Chansoria is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich, where he leads biofabrication research within the Tissue Engineering and Biofabrication (TEB) group. His work focuses on structured light technology for regenerative medicine applications, including in vivo bioprinting and microgravity-based tissue engineering. He holds Ambizione and Spark grants from the Swiss National Science Foundation and has pioneered innovations in light-guided biofabrication, collagen-based resins, and anisotropic tissue design. Research domains include: Filamented light biofabrication for aligned tissues Minimally invasive light-based in vivo bioprinting Musculoskeletal tissue engineering in microgravity Isotonic collagen-based photocrosslinkable resins He has secured over 6 patents and received prestigious awards including the ISBF Early Career Investigator Award (2022), Marie Curie Actions Fellowship (2021), and SME 30 Under 30 recognition (2021). His interdisciplinary research bridges bioengineering, materials science, and clinical applications. Key collaborations include projects at UNC Chapel Hill (USA) and NC State (USA), where he developed biomimetic patches for dynamic organ pathologies and ultrasound-assisted cell patterning. His lab explores novel bioinks, hybrid fabrication techniques, and translational applications in regenerative medicine.
Sabine Süsstrunk is a Full Professor and Director of the Images and Visual Representation Laboratory (IVRL) at EPFL's School of Computer and Communication Sciences. She holds a BS in Scientific Photography from ETH Zürich, MS from Rochester Institute of Technology, and PhD from University of East Anglia. Her career includes positions at Hewlett-Packard Labs and Corbis Corporation. Her research explores computational imaging, computational photography, color processing, computer vision, and image quality. Key interests include near-infrared applications, multispectral imaging, and computational aesthetics. Her work bridges hardware and software solutions for imaging challenges. Publications demonstrate consistent focus on advancing generative models (diffusion models, neural cellular automata), 3D reconstruction (NeRF variants), and media integrity (DeepFake detection). Recent trends show increased emphasis on 3D vision, robustness in generative AI, and video analysis. Awards & Honors: IS&T/SPIE Electronic Imaging Scientist of the Year (2013) Raymond C. Bowman Teaching Award (2018) EPFL AGEPoly IC Polysphere Award (2020) 8 Best Paper/Demo Awards Fellowships: IEEE, IS&T, ELLIS, AIIA She leads the IVRL lab and advises PhD candidates while serving as President of the Swiss Science Council. Research is supported through competitive grants and industry collaborations.
Gabriele Facciolo is a Professor at the Centre Borelli, ENS Paris-Saclay, France. He is a Senior Member of the Institut Universitaire de France (IUF) and holds an Innovation Chair (2025). His research focuses on image and video processing, remote sensing, and super-resolution techniques. Current affiliations: Centre Borelli (ENS Paris-Saclay), Institut Universitaire de France His research explores advanced algorithms for satellite stereo pipelines, real-time deblurring, denoising, and explainable AI systems for legal evidence enhancement. He coordinates projects like ANR SURECAVI (Super-resolution for visible camera systems) and ANR IMPROVED (video enhancement for judicial use), with recent work on Gaussian Splatting for Earth Observation and multi-date satellite super-resolution. Notable scientific achievements include the IGARSS 2025 Top 10 Student Paper Award and leadership in projects funded by ANR (€890k) and Prime Minister's entities (SGDSN/ANSSI). His work bridges computational imaging, defense applications, and digital forensics. Project leadership: SURECAVI, IMPROVED, BOFOR Key technologies: GPU acceleration, real-time processing, optical flow estimation, RPC refinement Gabriele actively contributes to open-source tools like S2P (Satellite Stereo Pipeline), MGM (MultiGlobal Matching), and OMNIflip. He teaches in the Master MVA program and collaborates across institutions (ENPC, UPF).
Dr. Attila Balázs is a Senior Researcher and Lecturer at ETH Zurich's Institute of Geophysics, affiliated with the Department of Earth and Planetary Sciences. His research integrates numerical modeling with geological data to investigate tectonic-surface process interactions, focusing on orogen-basin systems and continental deformation. Key contributions include studies on back-arc basins, transform faults, and the Tibetan Plateau's uplift mechanisms. He holds the 2020 Flinn-Hart Award and an ETH Zurich Postdoctoral Fellowship. His work emphasizes geodynamic processes such as mantle delamination, slab dynamics, and crustal deformation patterns. Balázs collaborates with the Geophysical Fluid Dynamics Group and maintains an active research portfolio spanning field observations, seismic analysis, and 3D numerical simulations. Research Foci: Tectonic modeling, basin evolution, mantle dynamics, and crustal rheology Key Regions: Pannonian Basin, Tibetan Plateau, Adriatic Sea, Himalayas His articles highlight interdisciplinary approaches to understanding continental and oceanic tectonics, with recent emphasis on transform fault mechanics, triple junction dynamics, and the interplay between tectonics and climate.
Martin Rajman is a Senior Scientist at École Polytechnique Fédérale de Lausanne (EPFL) with multiple affiliations across the institution. He holds positions in the School of Computer and Communication Sciences (SIN - Teaching, SCI IC MR Group, SSC - Teaching) as well as in the Vice Presidency for Strategic Development (VPS Artificial Intelligence) and the Vice Presidency for Academic Affairs (SNAI Administration). He serves as the Executive Director of Nano-tera.ch, a large Swiss Research Program funding collaborative multi-disciplinary projects in Health and the Environment. Rajman's research spans the intersection of artificial intelligence, natural language processing, and information retrieval. His work demonstrates a consistent focus on developing practical applications of computational linguistics and machine learning techniques. Early in his career, he contributed significantly to syntactic parsing, stochastic language models, and vector space representations for text. More recently, his research has expanded into deep learning applications for 3D reconstruction, empathetic conversational agents, and distributed analytics systems. His publications reveal a trajectory from foundational NLP research toward increasingly applied and interdisciplinary work connecting AI with healthcare, environmental monitoring, and human-computer interaction. Analysis of his recent publications (2015-2024) shows a clear evolution toward more applied AI research with strong interdisciplinary connections. While maintaining his core expertise in natural language processing and information retrieval, his work has expanded into computer vision, healthcare applications, and sustainable computing. The publications demonstrate increasing collaboration across disciplines, with applications in medical imaging, mental health support systems, environmental monitoring, and human-centered AI. His leadership role in the Nano-tera.ch program reflects this interdisciplinary approach, connecting computing research with real-world challenges in health and environmental contexts. Rajman has mentored several PhD students including Ailomaa Marita, Eckard Emmanuel, Melichar Miroslav, and Veselý Martin. His research has been supported through the Nano-tera.ch program, which has funded more than 100 research projects with over 95 million CHF in public funding. He has also managed more than 20 European projects during his tenure as Director of the EPFL Global Computing Center. As Executive Director of Nano-tera.ch, Rajman leads a significant research initiative connecting EPFL with national and international partners. His work bridges academic research with industry applications, notably through collaborations with eBay on product ranking technology and with Elsevier on article recommendation systems. His leadership extends to managing large-scale research programs while maintaining an active research agenda and mentoring the next generation of computer scientists.
Bernhard Thomaszewski is a Lecturer at the Department of Computer Science at ETH Zürich. His research focuses on computational mechanics, robotics, and computer graphics, with an emphasis on simulation-based design and material modeling. He explores topics such as deformable contact, flexible materials, and robotic mechanisms. His work bridges theoretical foundations and practical applications, including medical imaging, garment simulation, and biomechanical systems. Notable research interests include the development of novel algorithms for real-time simulation, optimization-driven design of mechanical systems, and integration of machine learning with physical models. He has contributed to advancements in finite element modeling, differentiable simulation, and topology optimization for robotic and biomedical applications. His recent projects highlight interdisciplinary collaboration, addressing challenges in areas like orthodontic treatment prediction, automated pipeline design, and neural network-driven material characterization. While no specific grants or awards are explicitly listed, his prolific publication record underscores his impactful contributions to computational engineering and computer science.
Professor Pascal Fua is a distinguished faculty member at EPFL (Swiss Federal Institute of Technology) in the School of Computer and Communication Science. He joined EPFL in 1996 and currently serves as Head of the Computer Vision Laboratory (CVLAB). His extensive research spans multiple cutting-edge areas in computer vision and geometric deep learning, with applications ranging from 3D reconstruction to medical imaging and aerodynamic optimization. Dr. Fua's research interests encompass Computer Vision, 3D Reconstruction, Shape Modeling, Geometric Deep Learning, Medical Image Analysis, Augmented Reality, Motion Recovery, Surface Mesh Processing, and Aerodynamic Shape Optimization. His work demonstrates a remarkable ability to bridge theoretical computer vision with practical applications across diverse domains. His research has evolved from traditional geometric computer vision techniques to incorporating deep learning approaches for 3D modeling, with recent focus on differentiable rendering, implicit surface representations, and applications in medical imaging and engineering design. His publication record shows a consistent trajectory of high-impact research, with recent work focusing on differentiable iso-surface extraction, geometric deep learning for aerodynamic shape optimization, and novel approaches to 3D reconstruction. His work spans both theoretical advances in computer vision algorithms and practical applications in medical imaging, autonomous driving, and computational fluid dynamics. IEEE Fellow Multiple ERC Grants recipient Associate Editor of IEEE Transactions for Pattern Analysis and Machine Intelligence Throughout his career, Professor Fua has mentored numerous PhD students who have gone on to make significant contributions in computer vision and related fields. His laboratory has established collaborations across multiple disciplines, including medical imaging, aerospace engineering, and neuroscience, demonstrating the broad applicability of his research. His current work continues to push the boundaries of geometric deep learning and 3D vision, with particular emphasis on making these techniques more practical and applicable to real-world engineering and medical problems.
Mark Tibbitt is an Associate Professor in the Department of Mechanical and Process Engineering at ETH Zürich, where he also serves as Deputy Head of the Department. His research focuses on macromolecular engineering , integrating chemical engineering, synthetic chemistry, and biology to design responsive soft materials for biomedical applications. Key areas include drug delivery, regenerative medicine, and biomaterials with tunable mechanical properties. Education: B.A. in Integrated Science and Mathematics, Northwestern University Ph.D. in Chemical Engineering, University of Colorado Boulder NIH Postdoctoral Fellow, MIT (2013–2017) Research Interests: His lab develops user-programmable materials to study biological processes and solve clinical challenges. Current projects explore stimuli-responsive hydrogels, ex situ organ perfusion, and biomaterials for tissue engineering. The Macromolecular Engineering Laboratory emphasizes interdisciplinary collaboration across engineering, chemistry, and medicine. Labs/Teams: He leads the Macromolecular Engineering Laboratory at ETH Zürich, dedicated to advancing dynamic biomaterials and their clinical translation.
Xiangyu Chen is a Lecturer at the Department of Civil, Environmental and Geomatic Engineering, ETH Zürich. He is affiliated with the Luftqualität u. Partikeltechnolog (Air Quality and Particle Technology) research group. His contact information includes the email xiangchen@ethz.ch and is located at HIF D 27.1, Laura-Hezner-Weg 7, 8093 Zürich, Switzerland. His research focuses on nanotechnology and materials science applied to environmental engineering, biomedical diagnostics, and energy systems. Key areas include: Development of advanced sensors for air quality and biomedical applications Catalytic material design for energy efficiency Biomedical nanomaterials for targeted drug delivery and imaging Xiangyu Chen’s recent publications (2021–2024) highlight innovations in nanoparticle-based technologies, including 3D metal-organic frameworks for energy systems, deformable organosilica nanoparticles for MRI contrast agents, and real-time in vivo imaging techniques for glioma targeting. His work bridges theoretical material science with practical sensor and medical applications. No scientific awards or grants are explicitly mentioned. He mentors students within his teaching role but no specific advisees are listed. His affiliation with the Air Quality and Particle Technology group aligns with environmental nanotechnology research.
Berke Erbas is a researcher at the École polytechnique fédérale de Lausanne (EPFL) within the Department of Microengineering under the School of Engineering . His work focuses on advancing nanofabrication techniques through thermal scanning probe lithography (t-SPL) and complementary methods like reactive ion etching (RIE) and nanoimprint lithography (NIL). Education : Doctoral candidate at EPFL, specializing in semiconductor strain engineering and quantum device fabrication. Research interests center on grayscale nanopatterning, 2D material engineering, and quantum hardware development. His innovations in strain-controlled MoS 2 transistors have demonstrated significant electron mobility improvements ( 185 cm²/V.s ), while hybrid t-SPL/DSA approaches address sub-20 nm fabrication challenges. Publication trends reveal expertise in combining top-down lithography with bottom-up material assembly, enabling contamination-free interfaces and scalable CMOS-compatible processes. Applications span transparent electronics, photonic devices, and quantum computing. Labs & Collaborations : A core member of the LMIS1 laboratory , with collaborations across EPFL's Center of Micro/Nanotechnology (CMI), ETH Zürich, and international institutions. His work integrates interdisciplinary methodologies from materials science, quantum physics, and advanced manufacturing.
Adrienne Grêt-Regamey serves as Full Professor at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering, where she heads the Institute for Spatial and Landscape Development. Her academic career spans over 15 years at one of Europe's leading technical universities, with significant leadership roles including Head of the Engagement Platform for Future Cities Lab Global since 2021. Her research focuses on the complex interactions between human activities and landscape evolution across temporal and spatial scales. Specializing in landscape planning and environmental science, she investigates land-use decision models through forecasting and backcasting approaches. A key innovation in her work involves developing state-of-the-art 3D visualizations and auralizations within her laboratory to understand public perception of landscape changes and create decision support tools for participatory planning processes. Her methodology emphasizes iterative design-science collaboration to develop place-specific solutions that balance human well-being with environmental sustainability. Analysis of her recent publications reveals a strong trend toward interdisciplinary research integrating spatial analysis, ecosystem services assessment, and participatory decision-making. Her work increasingly addresses urgent global challenges including renewable energy transitions, climate adaptation strategies, and urban-rural dynamics, often employing advanced computational methods like machine learning and immersive virtual reality environments. Dandelion Entrepreneurship Award (2023) Most Influential Female Award in Land System Science (2022) ERC Starting Grant for GLOBESCAPE project (2017) Swiss National Science Foundation Transdisciplinary Award (2013) ETH Silver Medals for both Master and PhD theses Grêt-Regamey actively contributes to scientific governance as Member of the Swiss Science Council (since 2024) and Advisory Committee of the Wyss Academy for Nature. She serves as Associate Editor for Landscape and Urban Planning and Editor for disP - The Planning Review. Her research program has secured significant funding including an ERC Starting Grant and multiple Swiss National Science Foundation projects, with current work focusing on integrating design and land system science to foster place-making in peri-urban landscapes. Her laboratory at ETH Zurich specializes in developing immersive 3D environments for landscape assessment and planning, with recent work extending into therapeutic applications of virtual reality. She leads the Future Cities Lab Global engagement platform, facilitating knowledge exchange between researchers, practitioners, and policymakers on sustainable urban development challenges worldwide.
