Prof. Srdjan Capkun is a Full Professor in the Department of Computer Science at ETH Zurich and Director of the Zurich Information Security and Privacy Center (ZISC). He holds a Dipl.Ing. from the University of Split (1998) and a Ph.D. from EPFL (2004). His research focuses on system and network security, including wireless security (e.g., secure positioning), trusted computing, blockchain technologies, and privacy-preserving systems. He co-founded 3db Access (acquired by Infineon) and Sound-Proof, addressing secure distance measurement and authentication. Notable achievements include an ERC Consolidator Grant (2016), ACM Fellowship, and IEEE Fellowship. Education: Dipl.Ing., Electrical Engineering / Computer Science, University of Split, 1998 Ph.D., Communication Systems, EPFL, 2004 Research Interests: Wireless security (e.g., UWB, GNSS, cellular) Trusted execution environments (TEEs) Blockchain and cryptocurrency systems Privacy-preserving technologies Awards & Grants: ERC Consolidator Grant (2016) ACM Fellow and IEEE Fellow Leadership of ZISC Advising & Labs: Leads the System Security Group at ETH Zurich Guided postdoctoral researchers and graduate students in security and privacy Companies: 3db Access (secure distance measurement) Futurae (online authentication)
Prof. Gabriela Hug is a Full Professor at ETH Zurich's Department of Information Technology and Electrical Engineering, serving as Deputy Head of the Department and Deputy Head of the Power Systems and High Voltage Lab. She leads the Energy Science Center (ESC) and holds adjunct roles at Carnegie Mellon University. Her research focuses on modeling, control, and optimization of electric power systems for sustainable energy transitions. Education: PhD in Information Technology and Electrical Engineering, ETH Zurich (2004–2008) MSc in Information Technology and Electrical Engineering, ETH Zurich (1999–2004) Research Interests: Her work addresses challenges in smart grid integration, renewable energy systems, and advanced control strategies. Key areas include vehicle-to-grid technologies, distribution network optimization, and energy storage system planning. She emphasizes data-driven approaches and collaborative frameworks for grid resilience and flexibility. Key Achievements: Recipient of the 2019 ALEA Award (ETH Zurich) NSF Career Award (2013) IEEE Outstanding Young Engineer Award (2013) Leadership & Roles: Co-Director, NCCR Automation (Swiss National Centre of Competence in Research) Board Chair, Energy Science Center (ESC) Adjunct Faculty, Carnegie Mellon University Labs & Teams: Power Systems Laboratory (ETH Zurich) Energy Science Center (multi-disciplinary research hub)
Prof. Dr. Gonzalo Guillén Gosálbez is a Full Professor at the Department of Chemistry and Applied Biosciences , ETH Zürich. He holds a PhD in Process Systems Engineering (UPC, 2005) and has held academic positions at Imperial College London (Reader), University of Manchester (Senior Lecturer), and Universitat Rovira i Virgili (Assistant/Associate Professor). His research focuses on Sustainable Chemical Processes , integrating life cycle assessment, optimization techniques, and planetary boundary analysis to evaluate and design low-carbon technologies. Current position: Full Professor, ETH Zürich (2019–present) Prior roles: Imperial College London (2016–2019), University of Manchester (2014–2016), URV Spain (2008–2014) Education: PhD (UPC, 2005), MEng/BEng (University of Murcia) His research explores CO2 valorization , green methanol synthesis , circular marine fuels , and planetary boundary compliance in energy and chemical systems. Recent work emphasizes machine learning for process modeling, single-atom catalysis , and decentralized ammonia production . Scientific contributions include 15+ peer-reviewed articles (2023–2025) in journals like Nature Chemical Engineering , ACS Sustainable Chemistry & Engineering , and Energy & Environmental Science . Key themes: Optimization of hybrid fossil/renewable carbon systems Environmental impacts of energy transitions Catalyst design for sustainable chemistry Life cycle assessment of emerging technologies Awarded UPC Top Doctoral Student Award and Top National Student Award , he combines process systems engineering with sustainability metrics to address global challenges in chemical and energy systems.
Colin Jones is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Automatic Control Laboratory, School of Engineering. He earned his BASc and MASc in Electrical Engineering and Mathematics from the University of British Columbia (1994-2002) and a PhD in Control Theory from the University of Cambridge (2002-2005). Prior to EPFL, he was an assistant professor there and a senior researcher at ETH Zürich. Current role: Director of the Robotics, Control, and Intelligent Systems Doctoral Program at EPFL Research focus: Optimization-based and model predictive control (MPC) for renewable energy systems, green energy management, and data-driven control methods His recent work (2023-2025) spans high-speed predictive control , smart grid optimization , and physically consistent neural networks , with applications to buildings, hovercrafts, and power systems. He has secured an ERC Starting Grant for his research on optimal control of building networks. Publications include over 200 papers in journals like Automatica , IEEE Transactions , and Energy and Buildings . Notable article trends include distributed optimization , data privacy in energy systems , and nonlinear MPC for autonomous vehicles . Scientific Awards : ERC Starting Grant for optimal control of building networks Advising : Supervises 10 current PhD students and has advised 19 past PhD students, including Alessandretti Andrea and Diwale Sanket Sanjay. Grants and projects emphasize smart energy systems , predictive demand response , and nonlinear control .
Verena Zimmermann serves as Assistant Professor (Tenure Track) for Security, Privacy and Society at ETH Zurich within the Department of Humanities, Social and Political Sciences. She leads the Security, Privacy and Society research group, focusing on human-centered approaches to safety, IT security, and privacy challenges in emerging technologies. Her academic foundation includes a PhD in Usable Security from TU Darmstadt, where her dissertation From the Quest to Replace Passwords towards Supporting Secure and Usable Password Creation earned dual awards from the German Association for Data Protection and Data Security (GDD) and the Ernst-Ludwigs-Hochschulgesellschaft. Zimmermann's research pioneers the shift from viewing humans as security vulnerabilities to recognizing them as integral solutions. Her work spans password security, phishing interventions, smart home privacy, and cybersecurity education, consistently applying human factors principles to design systems that align with natural user behavior. Current projects explore emotional dimensions of security engagement, quantum governance frameworks, and LLM-related privacy concerns through interdisciplinary lenses combining computer science, psychology, and safety science. Recent publications reveal strong thematic trends toward understanding user motivations in security behavior, developing personalized training through augmented reality and adaptive systems, and translating safety science principles to cybersecurity incident management. Her work increasingly addresses societal implications of emerging technologies like quantum computing and generative AI. Her distinguished recognitions include: GDD Dissertation Award for Usable Security research Ernst-Ludwigs-Hochschulgesellschaft Dissertation Award IANUS Award (2nd place) for Moving from a 'Human-as-Problem' to a 'Human-as-Solution' Cybersecurity Mindset Zimmermann actively mentors through ETH's Human-Centered Security and Privacy Lab while collaborating internationally with institutions including ATHENE (German National Center for Applied Cybersecurity), Abertay University's Cybersecurity Division, and the Safety Science Innovation Lab. Her research receives support from Swiss and European funding bodies focused on privacy-preserving technologies and organizational security behavior. At ETH Zurich, she directs the Security, Privacy and Society group which employs design thinking, LEGO Serious Play, and mixed-methods research to tackle real-world security challenges. The team partners with industry stakeholders to develop practical solutions for phishing resistance, smart home privacy, and cybersecurity education while maintaining strong ties to the Research Training Group 2050 Privacy and Trust for Mobile Users.
Kaveh Razavi is an Assistant Professor at ETH Zurich in the Department of Information Technology and Electrical Engineering, supervising the Computer Security Group. He is also affiliated with the Department of Computer Science. Research focuses on commodity hardware and operating systems security Teaching: Computer Engineering (BSc 2022–2025), Hardware Security (MSc 2016–2025), Advanced Operating Systems (MSc 2016–2019) Research Interests: Razavi's work bridges computer systems and security, emphasizing microarchitectural vulnerabilities, hardware exploitation, and security verification. His group develops tools for analyzing hardware-software interactions and mitigating memory attacks like Rowhammer. Scientific Awards: Distinguished/Best Paper Awards at IEEE S&P, USENIX Security, MICRO Five Pwnies Awards for innovative research Dutch Veni Grant, ERC Starting Grant Jochen Liedtke Young Researcher Award Golden Owl Teaching Award (2022) ETH Medal, Intel Bounty Reward, BlackHat USA Recognition
Marie Violay is an Associate Professor at the Laboratory of Experimental Rock Mechanics (LEMR) within the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL). She also contributes to teaching and PhD program committees across multiple EPFL divisions. Specializes in rock mechanics, earthquake dynamics, and hydro-mechanical couplings Leads experimental studies on fluid-induced seismicity and reservoir deformation Research Focus : Investigates how pore fluid pressure variations affect rock strength, fault behavior, and permeability evolution. Her work spans from brittle fracture mechanics to ductile deformation processes under geothermal conditions, with applications to carbon storage, earthquake mitigation, and volcanic hazard assessment. Article Trends : Her recent publications examine stress biaxiality effects on fracture energy (2025), alteration impacts on geothermal reservoirs (2025), permeability changes in volcanic rocks (2024), and fundamental studies of water weakening mechanisms in sedimentary rocks (2024-2021). The work combines laboratory experiments, microstructural analysis, and numerical modeling. Labs & Collaborations : Coordinates the LEMR laboratory at EPFL. Collaborates with European Synchrotron Radiation Facility, Freie Universität Berlin, and industry partners like Emch&Berger AG. Leads PhD committee work in the EDME Doctoral School .
Paolo Ienne is a Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), where he leads the Processor Architecture Laboratory (LAP) within the School of Computer and Communication Sciences. His research focuses on advancing reconfigurable computing systems through innovative FPGA architectures and high-level synthesis methodologies. His primary research domains include reconfigurable computing, FPGA architecture design, dynamically scheduled dataflow circuits, and hardware acceleration techniques. Recent work emphasizes memory system optimization for FPGAs, formal verification of circuit transformations, and rapid C-to-hardware compilation flows. He has pioneered approaches for handling thousands of outstanding memory misses in FPGA accelerators and developed novel techniques for switch-block exploration without explicit pattern enumeration. Analysis of his 2023-2025 publications reveals a strong trend toward practical FPGA deployment challenges, with increasing focus on HBM integration, virtual memory systems for PCIe-attached devices, and formally verified circuit transformations. His work consistently targets real-world bottlenecks in high-level synthesis toolchains while maintaining theoretical rigor in dataflow architecture design. Professor Ienne's laboratory receives support from the Swiss National Science Foundation and industry partners including Huawei, enabling cutting-edge research in FPGA-based acceleration. His collaborative network spans major semiconductor companies and academic institutions worldwide, with frequent co-authorship on conference proceedings and journal publications in IEEE and ACM venues.
Gustavo Valverde Mora is a Lecturer at ETH Zurich's Power Systems Laboratory in the Department of Information Technology and Electrical Engineering. His research focuses on distributed energy resources, smart grid technologies, and power system control, with expertise in behind-the-meter DER integration and hosting capacity analysis. His recent work addresses key challenges in renewable energy integration, including voltage control coordination between transmission and distribution networks, data-driven local control schemes for active distribution grids, and unsupervised load disaggregation techniques using smart meter data. He has developed novel methods for DER modeling, GIS-based system analysis, and distribution network planning. Recognized with multiple awards including the 2022 Costa Rican National Technology Award, he actively contributes to IEEE Task Forces on DER integration. His research demonstrates strong emphasis on practical grid applications, combining theoretical power systems knowledge with advanced data analytics. Dr. Valverde teaches Power System Analysis (227-0526-00L) and maintains collaborations with utilities worldwide on renewable integration challenges.
Tobi Delbruck is a titular professor of physics and electrical engineering at ETH Zurich, where he leads the Sensors Group at the Institute for Neuroinformatics (INI) in Zurich, Switzerland. He collaborates closely with Shih-Chii Liu and Giacomo Indiveri as part of the 'hardware groups' at INI. Delbruck has also served as visiting faculty at Caltech and is a Fellow of the IEEE. His work focuses on bio-inspired and neuromorphic event-based sensory processing systems. Professor Delbruck's research spans multiple areas of neuromorphic engineering, with particular emphasis on event-based vision systems and low-power analog VLSI circuits. His work has significantly advanced the field of Dynamic Vision Sensors (DVS), which mimic the human retina's response to changes in brightness rather than capturing full frames. This approach enables extremely low-latency vision processing with minimal power consumption, making it ideal for high-speed applications and robotics. His research has applications in robotics, autonomous systems, and low-power embedded vision. Delbruck is an active contributor to the neuromorphic engineering community, co-organizing the annual Telluride Workshop on Neuromorphic Engineering and serving in leadership roles with IEEE. He has authored numerous influential publications and co-authored books including "Event-Based Neuromorphic Systems" and "Analog VLSI: Circuits and Principles." His jAER (Java Address-Event Representation) project provides open-source tools for real-time event-based sensory processing. Analysis of his recent publications shows a clear trend toward integrating event-based vision with deep learning techniques and applying these systems to practical robotics problems. His scientific achievements have been recognized with multiple awards including: IEEE Fellow Winner of Best Live Demonstration award at ISCAS 2012 Honorable Mention Award from Sensory Systems Technical Committee at ISCAS 2012 Overall Best Student Paper Award and Best Paper Award from Sensory Systems Technical Committee at ISCAS 2010 Winner of the 2006 ISSCC Jan Van Vessem Outstanding European Paper Award Professor Delbruck actively mentors students and has supervised numerous PhD and Master's theses in the areas of neuromorphic engineering and event-based vision systems. His group has secured significant research funding from various sources to support their innovative work in bio-inspired sensory processing. He teaches courses on "Electronics for Physicists II (Digital)" and "Neuromorphic Engineering," helping to train the next generation of researchers in this field. The Sensors Group at INI, which Delbruck leads, operates state-of-the-art facilities for designing and testing neuromorphic vision systems. The group maintains close collaborations with researchers worldwide and has developed several important open-source resources including the jAER project and bias generator design kits. Their work continues to push the boundaries of what's possible with event-based sensory processing, with applications ranging from high-speed robotics to low-power embedded vision systems.
Prof. Dr. Jing Wang is a Full Professor at the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich. His research focuses on air pollution control, nanoparticle transport, and environmental health and safety (EHS) impacts of nanomaterials. He has held roles including Assistant Professor at ETH Zürich (2010–present), Research Assistant Professor at the University of Minnesota (2007–2010), and postdoctoral associate in Particle Technology (2005–2007). Education: Bachelor’s in Engineering (2000) – Tsinghua University, Beijing Master’s in Computer Sciences (2003) – University of Minnesota PhD in Aerospace Engineering (2005) – University of Minnesota Research Interests: Air/water filtration technologies Nanoparticle emission reduction and measurement Multiphase flow mechanics Environmental impacts of nanomaterials Collaborations: Industrial partnerships include 3M, BASF, Boeing, Intel, Samsung, and others in nanoparticle measurement and filtration solutions. Honors: 2011 Smoluchowski Award (Association for Aerosol Research) 2006 ‘Best Dissertation’ Award (University of Minnesota) 2004 Doctoral Dissertation Fellowship Teaching: Courses include Air Pollution Control, Environmental Engineering Seminars, and Excursions for Environmental Engineers. Labs/Teams: Leads the Particle Technology Lab and collaborates with the Institute of Environmental Engineering at ETH Zürich.
Adam B. Badawi is a Professor of Law at the University of California, Berkeley - School of Law, where he maintains an active research agenda at the intersection of law, finance, and corporate governance. His scholarly work has established him as a leading expert in contract law, M&A transactions, securities litigation, and ESG compliance. Professor Badawi's research interests span multiple dimensions of corporate law and legal theory. His work on contractual complexity, particularly in debt agreements and M&A transactions, has provided significant insights into how legal drafting affects economic outcomes. He has extensively examined the business judgment rule, board authority, and the role of courts in corporate governance. More recently, his research has expanded into ESG-related topics, analyzing how environmental, social, and governance considerations intersect with traditional corporate law frameworks. His methodological approach often combines legal analysis with empirical techniques, including text analysis of legal documents and event studies of litigation outcomes. Professor Badawi's scholarly output demonstrates consistent high-impact research across multiple domains of corporate law. His early work focused on foundational aspects of contract theory and interpretation, while his more recent publications reflect growing interest in ESG metrics, executive compensation structures tied to sustainability goals, and the evolving regulatory landscape. The trajectory of his research shows a progression from theoretical legal analysis toward increasingly empirical and interdisciplinary approaches that bridge law with finance and data science. Professor Badawi has collaborated with numerous scholars across different institutions, including Duke University, Stanford Law School, and the University of Chicago Law School, reflecting the interdisciplinary nature of his work and its relevance to multiple academic communities.
Matthieu Cord is a Professor at Sorbonne University and Scientific Director of valeo.ai, leading research in computer vision, deep learning, and computational cooking. He heads the MLIA team at ISIR Lab, focusing on multimodal models, transformers, and efficient architectures. Research areas include computer vision, large language models with vision, and AI-driven food analytics. Key projects: VISA-DEEP AI chair, Foundation VaViM models, and SmolVLA collaboration with Hugging Face. His recent work examines scalable multimodal models , trajectory prediction , and diffusion-based segmentation , with studies on in-context learning and biased shortcut learning in visual question answering. Articles highlight DeiT variants , fishr for OoD generalization , and STEEX for counterfactual explanations . Scientific awards include IUF Honorary Membership (2009), BMVC 2017 Best Paper, and ICIP 2018 Best Paper. As an advisor, he supervised PhD theses on topics like GAN editing , semantic segmentation , and multimodal retrieval . Current roles involve mentoring the 'Research Band' at MLIA and leading EU-funded initiatives like SCAPE. His work bridges theoretical AI exploration with practical applications in autonomous driving and food technology.
Brian W. Pogue, Ph.D., is the Robert A. Pritzker Chair in Biomedical Engineering at Dartmouth College's Thayer School of Engineering, with a joint appointment as an Honorary Fellow in Medical Physics at the University of Wisconsin-Madison. His academic background includes a Ph.D. in Medical/Nuclear Physics from McMaster University and a Research Fellowship at Harvard Medical School's Wellman Center for Photomedicine. He has led significant administrative roles, including Dean of Graduate Studies at Dartmouth (2008–2012) and Chair of Medical Physics at Wisconsin (2022–2025). Research Focus : Dr. Pogue pioneers Optics in Medicine , specializing in cancer imaging, photodynamic therapy, and surgical guidance. His work integrates fluorescence imaging, radiation therapy monitoring, and molecular diagnostics to improve cancer treatment precision. Key innovations include Cherenkov imaging for radiotherapy dosimetry and hypoxia-sensitive probes for tumor resection. Publication Trends : Recent articles (2023–2025) emphasize real-time surgical guidance, hypoxia quantification, and multimodal imaging systems. Dominant themes include fluorescence tomography, radiation dosimetry, and low-cost diagnostic devices, reflecting a translational focus from preclinical validation to clinical applications. Awards & Honors : Fellow, Optica (formerly OSA) Fellow, American Institute for Medical and Biological Engineering (AIMBE) Fellow, American Association of Physicists in Medicine (AAPM) Fellow, SPIE (International Society for Optics and Photonics) Funding & Innovation : Continuously funded by the NIH since 2001 ($52M+ total), Dr. Pogue founded three startups: DoseOptics LLC (radiotherapy dose imaging) and Hypoxia Surgical LLC (tissue hypoxia cameras), bridging academic research to clinical tools.
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.
