Pascal Frossard is a Full Professor at the Department of Electrical Engineering in the School of Engineering (STI) at EPFL, with a courtesy appointment in the School of Computer and Communication Sciences. He founded and directs the LTS4 laboratory since 2003, co-leads the EPFL AI Center and Swiss Data Science Center, and serves as Associate Dean for Research at STI. Research Focus: Machine Learning, Graph Signal Processing, AI Applications in Healthcare, Computer Vision Academic Leadership: IEEE Fellow, ELLIS Fellow, Conference Chair roles Key Projects: Digital Pathology for Oncology, Cardiac Digital Twins, Robust Machine Learning Research Interests: His work bridges signal processing, machine learning, and applied mathematics, emphasizing biomedical applications. Recent research includes adversarial robustness in classifiers, network representation learning, and 360-degree video analysis. Scientific Awards: IEEE Fellow ELLIS Fellow Leadership in IEEE technical committees Advising & Grants: Supervised 20+ PhD students and postdocs. Secured major grants from PHRT, Hasler Foundation, FNS-Sinergia, Armasuisse, Google, and Cisco.
Olga Sorkine-Hornung is a Professor of Computer Science at ETH Zurich and head of the Institute of Visual Computing. She leads the Interactive Geometry Lab, focusing on theoretical and practical advancements in digital content creation, geometry processing, and shape modeling. Current position: ETH Zurich, Department of Computer Science Previous roles: Courant Institute (NYU), Technical University of Berlin Education: BSc and PhD from Tel Aviv University, postdoc at TU Berlin Her research spans shape representation, digital fabrication, computer animation, and fundamental geometry processing. Key contributions include Laplacian surface editing, as-rigid-as-possible deformation, and generalized winding numbers. She works on applications in VR, AR, and autonomous systems. Awards include Test of Time Awards (2024), ACM Fellow (2020), ERC Consolidator Grant (2020), and EUROGRAPHICS Young Researcher Award (2008). She has supervised numerous students and co-developed software libraries like libigl and Instant Meshes . Co-chair roles for SIGGRAPH, Eurographics, and Pacific Graphics Editorial board member for ACM Transactions on Graphics and other journals Keynote speaker at VMV, CVPR, and SIAM conferences Her work bridges mathematical rigor with practical implementation, advancing computer graphics and geometry processing through intuitive algorithms that maintain surface detail while enabling efficient computation.
Lior Wolf is a Professor at the School of Computer Science, Tel Aviv University. Previously, he was a postdoctoral researcher at MIT's Center for Biological and Computational Learning (CBCL) under Prof. Tomaso Poggio and earned his PhD from Hebrew University of Jerusalem with Prof. Amnon Shashua. His educational background includes: PhD in Computer Science, Hebrew University of Jerusalem Postdoctoral Research, MIT CBCL Prof. Wolf's research centers on artificial intelligence with seminal contributions to deep learning, computer vision, and natural language processing. His work bridges theoretical foundations (e.g., attention mechanisms, transformer analysis) with practical applications in medical imaging, speech processing, and sign language technology. He pioneered methods for neural network interpretability, efficient sequence modeling, and multimodal fusion. Analysis of his 2023-2025 publications reveals dominant trends in large language model optimization (neuron pruning, attention analysis), efficient video generation, and cross-modal learning. His work increasingly integrates medical applications (fMRI/EEG analysis) while maintaining theoretical rigor in model architecture design. His scientific achievements include: Best paper award at EMNLP 2024 for 'Backward Lens: Projecting Language Model Gradients into the Vocabulary Space' Best paper award at SCIA 2023 for 'Gradient Adjusting Networks for Domain Inversion' Best paper award at FG 2021 for 'Generating Master Faces for Dictionary Attacks' Prof. Wolf mentors graduate students in the School of Computer Science and leads research at the ICRC building laboratory. His team collaborates with 'the friends of TAU' on projects spanning biometric security, medical imaging, and generative AI. Current work focuses on efficient transformers, neural network interpretability, and multimodal medical diagnostics.
Gustavo Alonso is Full Professor at the Department of Computer Science (D-INFK) of ETH Zurich and Head of the Institute for Computing Platforms . He has been at ETH since 1995, first as a post-doc, then as Assistant Professor from April 1998, and promoted to Full Professor in October 2001. Within the Systems Group he leads the Information and Communication Systems Research Group . Education: 1989 – Telecommunications Engineering (undergraduate), Madrid Technical University (UPM-ETSIT), Spain 1992 – M.S. Computer Science, University of California, Santa Barbara (UCSB) 1994 – Ph.D. Computer Science, University of California, Santa Barbara (UCSB) Research Interests: His work spans databases, distributed systems, cloud-computing architecture, FPGAs, hardware acceleration for data science, parallel and reconfigurable computing . The group investigates how modern heterogeneous hardware—from GPUs to SmartNICs—can be integrated into data-processing systems to achieve orders-of-magnitude performance gains, energy savings, and new functionality such as in-network computation and serverless acceleration. Scientific Awards & Honors: Fellow of the ACM (Association for Computing Machinery) Fellow of the IEEE (Institute of Electrical and Electronics Engineers) Distinguished Alumnus, Department of Computer Science, UC Santa Barbara Four Test-of-Time / Most Influential Paper Awards across databases, programming languages, cloud computing, and software engineering Labs & Projects: He directs the Information and Communication Systems Research Group within the Systems Group ( systems.ethz.ch ). The lab develops open-source platforms such as Coyote v2 for FPGA abstractions, Shuhai for HBM benchmarking, and MicroRec for micro-second recommendation serving, while collaborating with industry on SmartNICs, serverless analytics, and cloud-scale data analytics.
David Lindlbauer is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University, where he leads the Augmented Perception Lab and co-directs the CMU Extended Reality Technology Center. His research bridges human perception, extended reality (AR/VR), and computational interaction techniques, focusing on developing systems that dynamically adapt interface elements based on environmental context, user cognition, and task requirements. He completed his PhD at TU Berlin under Prof. Marc Alexa and held a postdoctoral position at ETH Zurich's Advanced Interactive Technologies lab. His work has been published extensively at top venues including ACM CHI, UIST, and IEEE VR, with research themes spanning gaze tracking, spatial audio optimization, haptic feedback, and multimodal notification systems. Media outlets like MIT Technology Review and Fast Company Design have featured his innovations. Dr. Lindlbauer has received prestigious grants from Meta, NSF, and ETH Zurich, and serves on program committees for CHI, UIST, and ISMAR. He has been recognized with Best Paper awards at ISS 2023 and CHI 2016, and his lab develops tools like MineXR for personalized XR interfaces and RealityReplay for temporal change visualization in mixed reality environments.
Babak Falsafi is a Full Professor at the School of Computer and Communication Sciences (IC) at EPFL, leading the Parallel Systems Architecture Laboratory (PARSA). He is a renowned expert in computer architecture, datacenter systems, and cloud-native server design. His research focuses on post-Moore era computing, emphasizing heterogeneous architectures, energy efficiency, and scalable IT infrastructure. Falsafi is the founder of EcoCloud, an EC-sponsored industrial-academic consortium investigating sustainable information technology. He holds ACM and IEEE fellowships, a Sloan Research Fellowship, and has contributed to major projects like Optimus Prime (data transformation acceleration), AstriFlash (flash-based online service systems), and Midgard (virtual memory re-design). His work spans hardware-software co-design, memory systems, and security. Falsafi advises numerous PhD students and collaborates with industry partners such as Google and Cavium. Key achievements include pioneering scalable multiprocessor architectures, snoop filters in IBM BlueGene, and spatial memory streaming in ARM cores. His lab develops open-source tools like QFlex for server simulation. He frequently presents at top conferences (HPCA, ISCA, MICRO) and chairs workshops on post-Moore infrastructure. Teaching roles include leading courses in computer architecture and parallel systems across multiple EPFL departments (SIN, EDIC, SSC, SMA). His work addresses datacenter challenges like the 'data tax' and mitigating latency through specialized accelerators.
Alexander Mathis is an Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Brain Mind Institute (School of Life Sciences). His research bridges computational neuroscience and machine learning to decode sensorimotor behaviors and develop AI tools for behavioral analysis. Pure Mathematics MSc, Ludwig Maximilians University Munich PhD in Computational Neuroscience, Ludwig Maximilians University Munich His work focuses on understanding how the brain generates behavior through computational models and algorithms. Key contributions include the DeepLabCut toolbox, hBehaveMAE , and other frameworks for pose estimation, action segmentation, and brain-inspired AI. His group also explores proprioception, motor control, and neural coding theories. Recent publications include unsupervised hierarchical behavior modeling via masked autoencoders (ECCV 2024), synthetic basketball benchmarks (Shot7M2), and extensions of BABEL into hBABEL. These works highlight his interest in temporal hierarchies in behavior and scalable AI solutions for neuroscience. Scientific Honors Robert Bing Prize (2024) Eric Kandel Young Neuroscientists Prize (2023) Frontiers of Science Award (2023) Marie Skłodowska-Curie Postdoctoral Fellowship Studienstiftung des deutschen Volkes scholarship He advises PhD candidates in neuroscience and life sciences, leads courses on brain-like computation and software engineering for life sciences , and collaborates across AI4Science initiatives. His group actively participates in competitions, such as NeurIPS' MyoChallenge, where brain-inspired reinforcement learning algorithms have won awards.
Dr. Giulia Donati is a Researcher at Eawag – Swiss Federal Institute of Aquatic Science and Technology, affiliated with the Department of Environmental Social Sciences. She holds a PhD from ETH Zürich and has extensive experience in conservation biology, inter/transdisciplinary research, and project management. Her work focuses on social-ecological systems, ecological connectivity, and biodiversity conservation in aquatic and terrestrial ecosystems. Education: PhD (2016–2020, ETH Zürich), MSc (2013–2015, University of Lausanne), BSc (2010–2013, University of Lausanne). Notable roles include postdoctoral research on BlueGreenNet (2021–2024) and Connect-HDL (2020), and leadership in the Save Our Seas Foundation project (2019–2020). Research emphasizes social-ecological networks, blue-green infrastructure, and amphibian connectivity in human-dominated landscapes. Projects like BlueGreenNet and Connect-HDL integrate ecological modeling with stakeholder collaboration to enhance biodiversity. Her work bridges ecology, policy, and urban planning to address global conservation challenges. Publications span topics from clownfish genetics to urban biodiversity frameworks, reflecting interdisciplinary approaches. Active in science communication and policy-relevant research, she collaborates across sectors to foster sustainable solutions. Current affiliations include Eawag’s PEGO research group and the Department of Environmental Social Sciences.
Vincent Kaufmann is an Associate Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) , leading the Urban Sociology Laboratory (LaSUR) . Since 2010, he serves as Scientific Director of the Mobile Lives Forum in Paris. His career spans teaching at institutions like Lancaster University , Ecole des Ponts ParisTech , and Tongji University , with research focusing on mobility sociology , urban dynamics , and public policy evaluation . Master's in Sociology from University of Geneva PhD at EPFL on transport modal practices His work explores mobility-capital interactions , motility , and rhythmanalysis in contemporary societies. Key themes include urban lifestyle transformations , cross-border regions , and mobility-sustainability nexus , with recent emphasis on new proximities and slow cities . Teaching roles span EPFL departments like Teaching (EDAR) , Architecture and Urban Sciences (SGC) , and Human and Social Sciences (CDH) . He has directed numerous PhD and master's theses on urban mobility topics.
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
Claudia R. Binder is Full Professor at EPFL's School of Architecture, Civil and Environmental Engineering, leading the Laboratory for Human-Environment Relations in Urban Systems (HERUS) since 2016. Previously, she held professorships at the University of Munich (2011-2016), University of Graz (2009-2011), and University of Zurich (2006-2009). She served as Dean of EPFL's ENAC School from 2020-2023 and holds advisory roles with Swiss federal institutions including the Mercator Foundation since 2024. Her academic foundation includes a Biochemistry degree and PhD in Environmental Sciences from ETH Zurich, followed by postdoctoral research at the University of Maryland. This interdisciplinary background underpins her research approach spanning natural and social sciences. Professor Binder's work centers on urban sustainability transitions, examining urban metabolism dynamics through systems science frameworks. She investigates energy-food-transport interdependencies in cities using transdisciplinary methods that integrate material flow analysis, spatial modeling, and socio-technical assessments. Her research particularly emphasizes regulatory mechanisms and transformation drivers in human-environment systems, with case studies across Swiss and global urban contexts. Recent publications reveal evolving focus from foundational urban metabolism studies toward actionable transition strategies. Her 2024-2025 work increasingly addresses social tipping dynamics, circular decarbonization, and spatially explicit waste management, demonstrating methodological innovation through geo-referenced material flow analysis and participatory backcasting frameworks. Key thematic clusters include energy innovation diffusion, plastic waste governance, and demand-side flexibility in residential systems. She actively mentors 7 current PhD candidates while supervising 11 graduates since 2018, with research spanning urban metabolism modeling, sustainability assessment, and transition governance. Her leadership extends to Swiss National Science Foundation committees and National Research Program 71 on energy consumption management. At EPFL, she directs the HERUS laboratory which develops the Sustainability Solution Space methodology for urban assessment. The lab operates at the intersection of data science, environmental engineering, and social theory, maintaining strong field connections in Switzerland, Indonesia, and Germany for empirical validation of transition models.
Alexis Berne is an Associate Professor at the Environmental Remote Sensing Laboratory (LTE) within the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL). He co-directs the SSIE-GE program and serves as a member of the CDS (Commission for Doctoral Studies) . His research spans radar meteorology, precipitation microphysics, polar precipitation, and geostatistics, with a focus on mountainous and polar regions. Current Positions Associate Professor, LTE, EPFL (2013–present) Co-Director, SSIE-GE, EPFL PhD Program Committee Member, EDCE-GE, EPFL Research Interests include the remote sensing of precipitation, particularly snowfall and ice production mechanisms, using radar and geostatistical methods. His work addresses atmospheric processes in extreme environments like Antarctica and the Swiss Alps, leveraging machine learning and numerical modeling for climate analysis. Teaching encompasses courses on remote sensing, atmospheric processes, and climate change, emphasizing interdisciplinary approaches and spatiotemporal variability. He advises current PhD students such as Heather Anne Corden and Gionata Ghiggi, alongside mentoring past students like Jacopo Grazioli and Timothy Hugh Raupach.
Devis Tuia serves as Associate Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), holding appointments in the Institute of Environmental Engineering (IIE) within the School of Architecture, Civil and Environmental Engineering (ENAC). He leads the Environmental Computational Science and Earth Observation Laboratory (ECEO) since 2020 and contributes to EPFL's Doctoral Program in Civil and Environmental Engineering. His academic journey began in Lausanne with studies at UNIL and EPFL, culminating in a PhD in remote sensing from UNIL. Postdoctoral research followed at institutions in Valencia, Boulder, and EPFL, focusing on machine learning model adaptation. He progressed from Research Assistant Professor at University of Zurich to Associate and Full Professor at Wageningen University before joining EPFL. Tuia's research bridges Earth observation with artificial intelligence, specializing in interpretable deep learning for environmental applications. His lab develops algorithms for making remote sensing accessible, with particular emphasis on digital wildlife conservation through automated censuses using drone and satellite imagery. Current projects tackle the 'black box' problem in environmental modeling while advancing spatial intelligence for sustainable urban development. His 2023-2025 publication portfolio reveals three dominant trends: (1) species distribution modeling using incomplete observations, (2) multimodal fusion of satellite/drone data with textual descriptions, and (3) interpretable AI frameworks for environmental decision-making. This work consistently addresses real-world challenges like wildfire forecasting and biodiversity monitoring. As an educator, Tuia supervises 12 current PhD students and has graduated 4 former EPFL doctoral candidates. His teaching portfolio includes Frontiers of Deep Learning for Engineers , Sensing and Spatial Modeling for Earth Observation , and Image Processing for Earth Observation courses. The ECEO laboratory maintains active collaborations with ESA-NASA initiatives and conservation organizations globally.
Sidi Wu is a Researcher affiliated with ETH Zürich's Institute of Cartography and Geoinformatics. Their primary role is as Staff of the Professorship for Cartography, contributing to academic research and technical operations within the department. They are based at HIL G 23.2, Stefano-Franscini-Platz 5 in Zürich, Switzerland, and can be reached at sidiwu@ethz.ch. Research interests center on advancing AI-driven cartographic methods, historical map analysis, and environmental spatial dynamics. Specific focuses include generative AI applications in map-making, semantic segmentation of historical documents, and leveraging digitized maps for ecosystem studies. They also explore steganography in image translation and cross-domain adaptation techniques for geospatial data. Recent work emphasizes innovations in automated map storytelling systems, spatio-temporal context modeling using transformers, and weakly supervised learning approaches for map segmentation. Their studies frequently bridge cartography with environmental science disciplines like hydrology and urban morphology. No scientific awards or grants are explicitly listed in the provided information. While no advisees are documented here, their research collaborations likely involve student contributions. They are part of the core team at the Institute of Cartography and Geoinformatics, contributing to cutting-edge projects in geomatics and computational cartography.
Dima Damen is a Professor of Computer Vision at the School of Computer Science, University of Bristol, where she leads the Machine Learning and Computer Vision Group. She also serves as a Senior Research Scientist at Google DeepMind. As an EPSRC Early Career Fellow (2020-2025) and a Fellow of ELLIS for Europe, her research focuses on advancing computer vision, particularly in egocentric (first-person) vision, video understanding, and action recognition. Her educational background and professional journey have positioned her as a leader in the field of computer vision, with a particular emphasis on understanding human activities from wearable cameras. She has received numerous awards including Best Paper at ACCV 2024 and Outstanding Paper at ICASSP 2021. Professor Damen's research interests span multiple areas of computer vision and machine learning. She specializes in egocentric vision, where she has made significant contributions to understanding human activities from first-person perspectives. Her work explores video understanding, action recognition, hand-object interactions, and the development of vision-language models that can interpret and generate instructions from visual data. She has pioneered approaches to unique video captioning, long video understanding through active memory representations, and spatial reasoning from egocentric videos. Her research often bridges the gap between theoretical computer vision and practical applications in human-centered AI. Her recent publications demonstrate a strong focus on egocentric vision, with papers like "AMEGO: Active Memory from long EGOcentric videos" (ECCV 2024) and "HOI-Ref: Hand-Object Interaction Referral in Egocentric Vision" (2024) advancing the state of the art in understanding long-form first-person videos. She has also contributed to vision-language models with works like "ShowHowTo: Generating Scene-Conditioned Step-by-Step Visual Instructions" (CVPR 2025) and "It's Just Another Day: Unique Video Captioning by Discriminitave Prompting" (ACCV 2024, Best Paper). Her research shows a consistent trajectory toward building systems that can understand human activities in natural environments with human-like capabilities. Professor Damen has received significant recognition for her work, including: EPSRC Early Career Fellow (2020-2025) ELLIS Fellow for Europe (Nov 2024) Best Paper at ACCV 2024 Outstanding Paper at ICASSP 2021 (awarded to only 3 out of 1700 papers) Outstanding Reviewer for CVPR 2020 and 2021 Program Chair for ICCV 2021 She has successfully advised numerous PhD students and postdoctoral researchers, many of whom have gone on to prestigious positions in academia and industry. Her group has secured significant research funding including the EPSRC Programme Grant Visual AI and the EPSRC UMPIRE grant. She actively collaborates with industry partners including Google DeepMind, Adobe, and Meta, ensuring her research has practical impact. Professor Damen leads the Machine Learning and Computer Vision Group at the University of Bristol, which focuses on egocentric vision, video understanding, and the development of vision-language models. The group has created influential datasets like EPIC-KITCHENS, which has become a standard benchmark in egocentric vision research. Her team regularly participates in and organizes workshops at major computer vision conferences including CVPR, ICCV, and ECCV.
