Elliott Ash is an Associate Professor of Law, Economics, and Data Science at ETH Zurich's Center for Law & Economics. He holds a Ph.D. in Economics and J.D. from Columbia University, a B.A. in Economics, Government, and Philosophy from the University of Texas at Austin, and an LL.M. in International Criminal Law from the University of Amsterdam. His research focuses on empirical legal studies using econometrics, NLP, and ML, examining topics like judicial behavior, legislative impact, and AI-driven governance. He has been funded by the ERC, Swiss NSF, and others. Research Interests: Elliott explores automation of legal decisions, text-as-data analysis in law, and the intersection of AI with legal systems. He develops tools like BallotBot and LePaRD to enhance legal transparency and public understanding. His work bridges law, economics, and computer science, with publications in top journals like the American Economic Journal and Review of Economics and Statistics . Teaching: Courses include Building a Robot Judge , Natural Language Processing for Law , and Big Data for Public Policy . He co-organizes the Zurich Workshop in AI+Economics and Monash-Warwick-Zurich Text-as-Data Workshops. Awards: European Research Council Starting Grant, Swiss National Science Foundation Grant, and multiple grants from U.S. and Swiss institutions. His work has been featured in NPR , VoxEU , and Georgetown Law Journal . Labs/Teams: Leads the Swiss AI Initiative's Human-AI Alignment team, collaborates with the CEPR on Political Economy research, and serves as an Economic Journal Associate Editor.
Prof. Dr. Melanie Zeilinger is an Associate Professor at the Department of Mechanical and Process Engineering at ETH Zurich, leading the Intelligent Control Systems group at the Institute for Dynamic Systems and Control. She holds a diploma in Engineering Cybernetics from the University of Stuttgart (2006) and a Ph.D. in Electrical Engineering from ETH Zurich (2011). Her postdoctoral research included stints at EPFL (2011–2012), a Marie Curie fellowship at UC Berkeley and the Max Planck Institute (2012–2015), and a professorship at the University of Freiburg (2018–2019). Her research focuses on learning-based control, distributed control systems, and robotics , with applications to medical devices (e.g., hydrocephalus shunts) and human-in-the-loop systems. She organizes the Conference on Learning for Dynamics and Control (L4DC) and contributes to initiatives like the "Algorithm on My Team" project. Her awards include the ETH Medal for her PhD thesis, a Marie-Curie IO Fellowship , and an SNF Assistant Professorship grant . She serves as an Associate Editor for IEEE Control Systems Letters and actively reviews for top journals/conferences like IEEE TAC, Automatica, and NeurIPS. Key projects include: VIEshunt: A smart ventricular shunt for hydrocephalus treatment, combining control systems and medical engineering. Autonomous Racing: Contextual tuning and safety-certified learning-based MPC for real-time obstacle avoidance. Data-Driven Control: Integrating Gaussian processes and state-space models into MPC frameworks for uncertain systems. Her work bridges control theory, machine learning, and robotics, addressing societal challenges such as healthcare and energy efficiency.
Dr. John Francis Clinton is the Director of Seismic Networks and Head of the Earthquake Monitoring Section at the Swiss Seismological Service (SED), ETH Zurich. He leads the Marsquake Service for NASA's InSight mission and oversees Switzerland's broadband and strong-motion seismic networks. His expertise spans earthquake early warning systems, seismic instrumentation, and glacial seismology. Clinton is also a Co-Investigator on the Mars InSight mission and involved in international projects like EPOS and RAMSIS. Education PhD in Civil Engineering (Minor in Geophysics), California Institute of Technology (2004) MSc in Civil Engineering, California Institute of Technology (1998) BEng in Civil Engineering, University College Dublin (1997) Research Interests Dr. Clinton focuses on real-time seismology, seismic instrument design, structural health monitoring, and glacial seismology. His work bridges engineering applications with geophysical data analysis, particularly in earthquake early warning systems and induced seismicity studies. He collaborates internationally on projects such as the Valais Near Fault Observatory and Nicaragua’s Earthquake Early Warning development. Publications Overview His 15 most recent papers (2011–2015) highlight advancements in seismic network optimization, Marsquake detection algorithms, and glacial icequake mechanisms. Key themes include improving early warning accuracy, understanding subglacial dynamics, and validating high-rate GPS for structural monitoring. Awards & Memberships Member, Swiss Academy of Sciences (since 2008) Member, IRIS Quality Assurance Advisory Committee (since 2013) Chair, European Integrated Data Archives (EIDA) (2013–2015) Labs & Teams Clinton directs the SED’s Earthquake Monitoring team and collaborates with ETH Zurich’s Geophysics Masters Program. His group manages Switzerland’s seismic networks and leads the Marsquake Service, which analyzes InSight lander data for Martian seismic events.
Margarita Boenig-Liptsin is a tenure-track Assistant Professor of Ethics, Technology and Society at ETH Zurich's Department of Humanities, Social and Political Sciences, a position she has held since September 2022. Trained in Science, Technology and Society with dual PhDs from Harvard University (History of Science) and Université Paris-Sorbonne (Philosophy), she brings interdisciplinary expertise to examining the relationship between technology, power, democracy, and ethics. Her research spans several interconnected areas focusing on transformations to human identity and citizenship in relation to information technologies across time and cultures. She investigates the social and political aspects of digital technologies, identity and selfhood in technological societies, ethics of technology, and comparative cultures of innovation. Her work uniquely bridges historical analysis with contemporary ethical concerns, examining how concepts like human dignity evolve alongside technological developments from punch cards to AI governance frameworks. Her recent publications (2023-2025) reveal a strong focus on AI ethics, data justice, and the philosophical implications of algorithmic systems. These works demonstrate her consistent interest in how technology shapes democratic processes, citizenship, and ethical frameworks. Her research shows progression from historical studies of computer literacy programs to contemporary analyses of generative AI's impact on knowledge production and everyday ethics. Her scientific recognition includes: NSF funding for her collaborative project on Silicon Valley's innovation imaginary Mozilla Foundation Responsible Computer Science Challenge grant (2018-2021) Academic Data Science Alliance support (2020-2022) Sorbonne Université's Paris IAS Chair on 'Major Changes' (2021-2022) At ETH Zurich, she leads research and teaching initiatives that build connections between engineering and social sciences. Previously at UC Berkeley, she directed the Human Contexts and Ethics Program, developing the Human Contexts and Ethics component for data science education. Her work consistently emphasizes translating social science theory for diverse audiences and connecting scholarly work to community needs in Zurich, Switzerland, and Europe. She teaches courses including 'Artificial Intelligence and Human Values' and 'Research in Ethics, Technology and Society' for the Fall 2025 semester.
Olga Fink is a Tenure Track Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Intelligent Maintenance and Operations Systems (IMOS) within the School of Architecture, Civil and Environmental Engineering (ENAC). She also holds roles in PhD program committees for Civil and Environmental Engineering (EDCE) and Robotics, Control, and Intelligent Systems (EDRS). Her research focuses on machine learning for infrastructure monitoring, predictive maintenance, and physics-informed AI models. She teaches courses on machine learning, data science for infrastructure, and advanced deep learning topics. Fink advises multiple PhD students and is involved in interdisciplinary projects such as ThermoNeRF (multimodal 3D thermal modeling) and physics-informed neural networks for fault diagnostics. Her work bridges AI and engineering with applications in smart infrastructure, energy systems, and industrial IoT. Education: PhD in Engineering (inferred from role) Affiliations: IMOS Lab, ENAC-SGC, EPFL PhD Committees (EDCE, EDRS) Key Research Themes: Explainable AI, Digital Twins, Structural Health Monitoring, Domain Adaptation Her publications (2023–2025) emphasize robust AI for industrial systems, including fault detection in high-voltage equipment, multimodal data fusion, and physics-consistent models. She collaborates on EU and industry-funded projects, focusing on real-world applications like predictive maintenance and energy efficiency.
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.
Jean-Claude Besse is a Lecturer in the Department of Physics at ETH Zürich, specializing in superconducting circuits and quantum optics. His research focuses on quantum computing, microwave photonics, and artificial atoms. Research Interests: Besse works on the fabrication of superconducting circuits, modular quantum computing processors, and microwave quantum optics using artificial atoms. His work includes single-photon detection, parity measurements, entanglement stabilization, and quantum networking. He has developed technologies like high-fidelity multiplexed readout and tunable ZZ gates. Key Contributions: Besse led breakthroughs in non-destructive single-photon detection, deterministic remote entanglement, and loophole-free Bell inequality violations. His research enables error-corrected quantum communication protocols and scalable microwave quantum systems. Publications Trends: Recent articles emphasize modular quantum architectures, entanglement stabilization, and microwave photon engineering. Topics include cluster state generation, defect mode mitigation, and reinforcement learning for quantum feedback systems. Labs & Teams: Affiliated with the Laboratorium für Festkörperphysik at ETH Zürich, Besse contributes to advancing superconducting quantum technologies and microwave quantum optics.
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.
Dr. Andrea Martinelli is a Lecturer and Postdoctoral Researcher at the Automatic Control Laboratory (IfA), ETH Zurich. He holds a PhD in Automatic Control from ETH Zurich (2024) under Prof. John Lygeros, an MSc in Control Engineering (2017) from Politecnico di Milano, and a BSc in Management Engineering (2015). His research focuses on optimal control, reinforcement learning, and decentralized control strategies for large-scale systems, emphasizing scalability and applicability to renewable energy systems. He received the ETH Medal for his doctoral thesis on data-driven control methods. Education: BSc in Management Engineering, Politecnico di Milano (2015) MSc in Control Engineering with Honours, Politechnico di Milano (2017) PhD in Automatic Control, ETH Zurich (2024) Research Interests: Optimal control and reinforcement learning Data-driven methods for control systems Decentralized control of interconnected systems Dissipativity theory and passivity-based approaches Applications in renewable energy systems (DC microgrids) Teaching & Outreach: Program Manager for the CAS ETH in Automation Teaching a post-graduate course on automation in 2025 Professional Activities: Worked at Laboratoire d'Automatique (EPFL) during MSc thesis (2017) Research Assistant with Prof. R. Scattolini, Politecnico di Milano (2018)
Emilio Frazzoli is a Full Professor at ETH Zurich’s Department of Mechanical and Process Engineering. He leads the Institute for Dynamic Systems and Control and the Center for Sustainable Future Mobility, focusing on autonomous systems, robotics, and socio-technical control frameworks. Current affiliations: ETH Zurich (Dynamic Systems and Control, Sustainable Future Mobility) Research: Autonomous mobility-on-demand, game theory for resource allocation, and safety verification in multi-agent systems His work bridges robotics, control theory, and economics, with projects like the open-source AMoDeus simulation framework for autonomous taxis and karma-based resource allocation systems. Recent publications emphasize trustworthy AI, reproducibility in autonomous vehicle control, and human-robot interaction challenges. Notable projects include nuReality (VR-based pedestrian interaction studies) and CARSI II (context-driven vehicle interfaces).
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.
Tanja Käser is a Tenure Track Assistant Professor at EPFL's School of Computer and Communication Sciences (IC), leading the Machine Learning for Education Laboratory (ML4ED). Her interdisciplinary research bridges machine learning, data mining, and educational technology, focusing on personalized learning systems and human behavior modeling. PhD in Computer Science (ETH Zurich, 2015) - honored with Fritz Kutter Award Former Senior Data Scientist at Swiss Data Science Center (ETH Zurich) Postdoctoral Researcher at Stanford University's Graduate School of Education Research Focus Explainable AI for education Adaptive learning environments Behavioral pattern recognition Generative AI applications in pedagogy User modeling and personalization Learning analytics in unstructured settings Recent Publication Trends Her 2024-2023 work demonstrates: Interpretable clustering of learners Transformer-based language learning prediction GAN applications for creative education Teacher-AI collaboration frameworks Explainability validation methods Modular network architectures Scientific Recognition Fritz Kutter Award for best Swiss computer science thesis (2015) Advising & Collaborations Currently supervises multiple PhD students including: Cock Jade Maï L Glandorf Dominik Güres Fatma-Betül Neshaei Seyed Parsa Radmehr Bahar Shibu Abhinand Shved Ekaterina Research Infrastructure Operates from EPFL's ML4ED laboratory with hybrid on-site and digital educational systems research capabilities.
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. April Wang is an Assistant Professor in the Department of Computer Science at ETH Zurich. Her work focuses on Educational Technology, Human-Computer Interaction, and AI-driven tools for programming education. She is affiliated with the Professur Educational Technology group and teaches courses such as Human Computer Interaction and Ethics in Computing. Her research explores interactive learning environments, collaborative data science workflows, and AI-augmented educational systems. Her research interests span computational notebooks, live coding interfaces, and human-AI collaboration in software development. Notable contributions include frameworks like DBox for algorithm learning and EDBooks for interactive programming narratives. She also investigates challenges in real-time collaboration tools and automated documentation systems for data scientists. Recent work emphasizes understanding user needs in automated copilot systems and resolving conflicts in collaborative notebook environments. Her projects often bridge theoretical HCI principles with practical educational tools, aiming to enhance both instructor efficacy and student engagement. Prof. Wang’s teaching portfolio includes courses on user-centered interface design and ethical scientific practices. She actively contributes to advancing interdisciplinary computational literacy through initiatives like datAR, which uses everyday objects to teach data concepts.
Mirjana Stojilovic is a Researcher at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC), specifically within the Institute of Computer Engineering (IINFCOM) and the Parallel Systems Architecture Laboratory (PARSA). She also serves as a Lecturer in the SSC - Teaching department at EPFL. Her office is located at INJ 235, Station 14, 1015 Lausanne, Switzerland. Mirjana Stojilović received her Dipl. Ing. and Ph.D. degrees from the School of Electrical Engineering, University of Belgrade, in 2006 and 2013, respectively. Her academic journey includes collaborating with the Processor Architecture Laboratory at EPFL as a Guest Researcher from 2010 to 2013, working at the University of Applied Sciences Western Switzerland as a senior researcher from 2013 to 2016, and joining the Parallel Systems Architecture Lab at EPFL in October 2016. Dr. Stojilovic's research spans field-programmable technology, electronic design automation (EDA), and electrical-level attacks and countermeasures for reconfigurable hardware. Her work bridges the gap between hardware design and security, with a particular focus on vulnerability analysis and protection mechanisms for FPGA-based systems in cloud environments. She has made significant contributions to understanding side-channel attacks, fault injection techniques, and secure multi-tenancy solutions for shared hardware resources. Her extensive publication record reveals a clear research trajectory from traditional FPGA design and EDA topics toward increasingly security-focused investigations. Recent work demonstrates deep expertise in power analysis attacks, hardware trojans, and countermeasures for cloud-based FPGA systems, reflecting the growing importance of hardware security in distributed computing environments. Scientific Awards and Recognitions: Best Paper Award at 2016 International Symposium on Electromagnetic Compatibility (EMC Europe 2016) Young Scientist Award at 33rd International Conference on Lightning Protection (ICLP2016) Young Author Best Paper Award at the 20th Telecommunication Forum in Belgrade (TELFOR 2012) EPFL School of Computer and Communication Sciences (IC) Teaching Award (2015) Nominated for Best Paper Award at the International Conference on Field-Programmable Technology (FPT) (2020) Dr. Stojilovic has advised numerous PhD students including Coulon Louis, Pirayadi Rouzbeh, and Shrivastava Shashwat, along with past EPFL PhD students Glamocanin Ognjen and Mahmoud Dina. She has supervised dozens of semester and diploma projects focusing on hardware security, FPGAs, design automation, side-channel attacks, and cloud computing. Her service to the academic community includes serving on program committees for FPGA, FCCM, FPL, and DATE conferences, reviewing for multiple IEEE and ACM journals, and acting as associate editor for IEEE ESL and ACM TRETS. As a member of the Parallel Systems Architecture Laboratory at EPFL, Dr. Stojilovic leads research projects investigating security aspects of reconfigurable hardware systems. Her team works at the intersection of computer architecture, electronic design automation, and hardware security, with particular emphasis on vulnerabilities and protections for shared FPGA resources in cloud environments.
