Peter Bühlmann is a Professor at ETH Zürich within the Seminar für Statistik , focusing on high-dimensional statistics, causal inference, and machine learning. His work bridges theoretical advancements with practical software implementations in R packages like pcalg , mboost , and glmmlasso , impacting fields such as genomics, proteomics, and intensive care analytics. Key Contributions : Causal structure learning, stability selection, anchor regression, and deconfounding. Software : Developed widely used R packages for statistical modeling and causal inference. Teaching : Courses on high-dimensional statistics at ETH Zürich and international institutions. Research Trends : Recent articles emphasize causal robustness, domain adaptation, and applications in medicine. His work addresses challenges in heterogeneous data, missing values, and covariate shifts using methods like spectral deconfounding and residual prediction tests. Scientific Recognition : Co-author of a paper designated as a New Hot Paper (Meinshausen and Bühlmann, 2006) by Essential Science Indicators, indicating significant impact in high-dimensional multiple testing.
John Lygeros is a Full Professor and Head of the Institute for Automatic Control at ETH Zurich's Department of Information Technology and Electrical Engineering. He received his B.Eng. (1990) and M.Sc. (1991) from Imperial College London, and Ph.D. (1996) from UC Berkeley. Before joining ETH Zurich in 2006, he held academic positions at the University of Cambridge and University of Patras. His research focuses on: Modeling and control of hierarchical hybrid systems Large-scale dynamical systems applied to biochemical networks Control of automated transportation systems via wireless networks Energy systems and advanced manufacturing control His research demonstrates strong emphasis on optimization methods, distributed control architectures, and machine learning applications in control systems, with significant contributions to real-time optimization algorithms and data-driven control methodologies. Major scientific awards include: HSCC Test of Time Award (2024) ERC Advanced Grant (2018) O. Hugo Schuck Best Paper Award (2018) IEEE George S. Axelby Paper Award (2016) Three Golden Owl teaching awards from ETH Zurich He leads the Automatic Control Laboratory at ETH Zurich and serves as Director of the National Centre of Competence in Research 'Dependable Ubiquitous Automation'. He has advised over 60 doctoral candidates since 2017, with research spanning optimization algorithms, power systems, autonomous systems, and machine learning applications.
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.
Andras Kis is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) across multiple institutes including the Institute of Electrical Engineering (IEL), Institute of Materials Science (IMX), and teaching programs in Electrical Engineering (SEL-ENS). He leads the Laboratory of Nanoscale Electronics and Structures (LANES) and serves on the PhD program committee for Microsystems and Microelectronics. PhD, EPFL (2003) MS, Physics, University of Zagreb (1999) Baccalaureate, MIOC High School Research Focus: Pioneering work on 2D materials for electronic and optoelectronic devices, particularly transition metal dichalcogenides like MoS2 and PtSe2. His research spans: Transistor design with atomically thin semiconductors Excitonic devices and valleytronics Nanofluidics and ionic logic Optical properties of 2D heterostructures Scalable fabrication of 2D materials Defect engineering and doping techniques Scientific Impact: Based on analysis of 15 most recent publications, his work focuses on advancing 2D materials for next-generation electronics through innovations in: Van der Waals heterostructures Thermoelectric and optoelectronic applications Nanofabrication techniques Spintronic and quantum transport phenomena Memristive and neuromorphic devices Characterization of electronic and optical properties Awards & Recognition: Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Lotfi A. Zadeh Award for Emerging Technologies (2024) Highly Cited Researcher (Clarivate Analytics) Teaching & Academic Leadership: Currently teaching courses including Lab in Nanoelectronics , Physical Models for Micro and Nanosystems , and Semiconductor Devices II . He has supervised over 20 PhD students in his research group at EPFL. Laboratory & Collaborations: Directs the Laboratory of Nanoscale Electronics and Structures (LANES) which focuses on fundamental and applied research in 2D materials and nanoelectronic devices. His work bridges materials science, condensed matter physics, and microelectronics engineering.
Joachim Rosenthal is a Professor of Applied Mathematics at the University of Zurich's Department of Mathematics, leading the Applied Algebra Group. His research integrates coding theory, cryptography, and algebraic geometry with applications in communications and security systems. His primary research explores algebraic coding theory including convolutional codes, subspace codes, and post-quantum cryptography. He develops algorithms for error correction, code optimization, and cryptographic protocol analysis, with emphasis on mathematical structures in finite fields and rings. Professor Rosenthal serves as President of the Swiss Mathematical Society (2024-2025) and sits on IEEE Information Theory Society's Board of Governors. He has organized multiple international conferences on coding theory and cryptography, including the Zurich COST Meeting and Workshop on Convolutional Codes. His editorial contributions include roles at Archiv der Mathematik and SIAM Journal on Applied Algebra and Geometry. Recent publications focus on code construction methods, complexity analysis in group-based cryptography, and algebraic approaches to error-correcting codes.
Philippe Christe is an Associate Professor in the Department of Ecology and Evolution at the University of Lausanne (UNIL), Faculty of Biology and Medicine. His research centers on host-parasite interactions, with a focus on bats, birds, and their ectoparasites, integrating behavioral, physiological, and genetic approaches. He leads the Christe Group, which investigates evolutionary and ecological dynamics in host-parasite systems, particularly avian malaria and bat-mite relationships. He is actively involved in conservation initiatives, including the Jorat Peri-Urban Nature Park, and collaborates with KORA on human-wildlife interactions. Bachelor's degree in biology, UNIL (1989) PhD in Zoology and Animal Ecology, UNIL (1994) Philippe Christe’s research interests lie at the intersection of parasitology, evolutionary ecology, and conservation biology. He investigates how host defenses evolve in response to parasitic pressures, examining trade-offs between immunity and life history traits such as reproduction and survival. His work often integrates field studies with experimental and molecular techniques. Key model systems include Parus major (great tit) and Culex pipiens in avian malaria, and bat species with their ectoparasitic mites. He also explores broader ecological interactions, including predator-prey dynamics and wildlife conservation in human-modified landscapes. His recent publications reflect a strong emphasis on disease ecology, wildlife conservation, and molecular methods. Articles span topics such as avian malaria transmission, lynx population dynamics, snow leopard behavior, and habitat fragmentation effects on insects. These works employ advanced techniques like DNA metabarcoding, spatial modeling, and long-term monitoring, demonstrating a trend toward interdisciplinary, data-driven ecological research with direct conservation applications. Dubois Foundation Prize for an educational CD-Rom on bats (2004) Communication Award from the Faculty of Biology and Medicine of UNIL (2017) Philippe Christe has supervised numerous PhD and Master’s students, contributing significantly to training the next generation of ecologists and evolutionary biologists. His group collaborates widely with institutions such as the Museum of Zoology in Lausanne and KORA, and participates in large-scale conservation projects involving snow leopards, lynx, and bats. He has been involved in research grants related to host-parasite coevolution, wildlife monitoring, and conservation strategies. His leadership in establishing the Jorat Peri-Urban Nature Park and involvement in the UNIL Interdisciplinary Center for Mountain Research highlight his commitment to applied science and environmental stewardship. He leads the Christe Group, which conducts research on host-parasite coevolution, with a focus on bats and their ectoparasites, and birds affected by avian malaria. The group combines fieldwork, laboratory experiments, and molecular analyses, and includes post-docs, PhD students, and technical staff. Collaborations extend to researchers in Bern, Paris, and Spain, fostering an international and interdisciplinary research environment.
Franziska Boenisch is a tenure-track faculty member at the CISPA Helmholtz Center for Information Security , where she co-leads the SprintML lab for Secure, Private, Robust, Interpretable, and Trustworthy Machine Learning. Her research lies at the intersection of privacy-preserving machine learning and trustworthy ML , with a focus on differential privacy , model inversion attacks , and privacy risks in federated learning . She completed her PhD at Freie Universität Berlin and was a postdoctoral fellow at the Vector Institute for Artificial Intelligence under Prof. Nicolas Papernot. Her work has been recognized with awards such as the Academics Rising Start Award (3rd Prize) and the GI Junior-Fellow honor. Her research spans a wide range of topics including memorization in diffusion models , watermarking generative models , membership inference attacks , and privacy-preserving federated learning . She has published extensively in top-tier venues like ICML , NeurIPS , ICLR , and CVPR . She is actively involved in the academic community, serving as an Area Chair for NeurIPS , Track Chair for ACM AsiaCCS , and co-organizing workshops at ICML . She is currently hiring PhDs, postdocs, and research interns for her group.
Prof. Dr. Urs F. Greber is an Ordinary Professor of Molecular Cell Biology at the Department of Molecular Life Sciences, Faculty of Mathematics and Natural Sciences, University of Zurich. His research focuses on understanding how viruses interact with host cells, particularly adenoviruses and rhinoviruses that cause human respiratory diseases. He leads the Greber Lab, which investigates viral entry mechanisms, replication processes, and the cellular responses to infection. Greber's research interests span virology, molecular cell biology, and infection mechanisms. His lab explores how viruses take control over membrane and lipid functions, cytoplasmic transport processes, and cellular metabolism to support their gene expression and progeny formation. They employ system-wide profiling, molecular cell biology approaches, light microscopy, and machine learning for image analysis to map the cell state underlying viral infections of cultured and primary human cells, including lung organoids and iPSC-derived macrophages. A key focus is understanding cell-to-cell variability in infection phenotypes and the mode-of-action of antiviral compounds. The Greber Lab has published extensively on adenovirus biology, including viral entry, uncoating, nuclear import, and assembly mechanisms. Their recent work has identified broad-spectrum antiviral compounds, elucidated alternative virus entry pathways, and developed innovative imaging and AI-based approaches for quantifying virus infectivity. Their research contributes to understanding how viruses break down host defense barriers and has implications for antiviral therapy development. Greber has supervised numerous PhD and Master's students including Cornelia Bircher, Alessandro Savi, Franziska Tomas, Alfonso Gomez-Gonzalez, Anthony Petkidis, and Dominik Olszewski. His lab has received funding from the Swiss National Science Foundation, including a grant for coronavirus research during the pandemic. The lab actively collaborates with other research groups at University of Zurich, ETH Zurich, and international institutions. Current projects include exploring how viral DNA interactions contribute to infection outcome variability, investigating adenovirus egress mechanisms, and developing high-throughput screening methods for antiviral compounds.
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.
Juerg Leuthold is a Full Professor and Head of the Department of Information Technology and Electrical Engineering (D-ITET) at ETH Zürich, Switzerland. He also leads the Institute of Electromagnetic Fields (IEF) at the same institution. His academic career spans leadership roles at ETH Zürich, Karlsruhe Institute of Technology (KIT), and Bell Labs, with expertise in photonics, plasmonics, and THz technology for communication and sensing applications. Research Interests Photonics for high-speed communication Plasmonics and nonlinear optical signal processing Terahertz technology Applications in sensing and network systems Scientific Awards Optica Fellow IEEE Fellow ERC Advanced Grant (2015) Landesforschungspreis (Baden-Württemberg, 2009) Leadership & Committees Head of D-ITET (2023–present) General Chair of ECOC 2022 Board of Directors, OSA/Optica
Ke Xu is an Assistant Professor at the Department of Finance, Faculty of Business and Economics, University of Victoria. His research bridges finance, econometrics, and cryptocurrency, focusing on market microstructure, high-frequency trading, and price discovery mechanisms. He has extensively studied Bitcoin ETFs, fractional cointegration models, and machine learning applications in financial markets. Key Research Areas: Market Microstructure High-Frequency Trading Cryptocurrency Dynamics Price Discovery Machine Learning in Finance Financial Econometrics Article Trends: Xu’s work spans empirical analyses of Bitcoin ETFs, volatility modeling (e.g., affine GARCH), and algorithmic trading strategies. His recent papers explore mini flash crashes using machine learning, regulatory impacts on market quality, and sustainable crypto portfolios.
Avinash Kori is a Ph.D. researcher at Imperial College London affiliated with the Safe and Trusted AI Centre for Doctoral Training (CDT). Supervised by Prof. Francesca Toni and Prof. Ben Glocker , his research focuses on Explainable AI (XAI) , causality , and deep learning with applications in medical image analysis and optimization algorithms . His work includes publications on arXiv and conferences like MICCAI , covering topics such as robust segmentation , concept-based explanations , and symbolic reasoning in hyperbolic space . He has also explored stochastic optimization , support vector machines (SVM) , and gradient descent variants , providing theoretical and practical implementations. Recent trends in his publications highlight advancements in robust CNN models , causal logic frameworks , and hyperbolic geometry for hierarchical learning . His research is driven by the need to make AI systems more transparent and reliable for critical domains like healthcare. Scientific Awards: AAAIw Overall Best Paper Award (Feb 2021) for CNN interpretability research. He actively contributes to open-source implementations via platforms like GitHub and shares insights through blogs and paper reviews . His academic journey includes an undergraduate degree in Biomedical Engineering Design with a minor in Machine Learning from Indian Institute of Technology, Madras , followed by research internships at Siemens and Stanford University .
Dr. Hongwei Wang is a Senior Researcher at Tencent AI Lab Seattle , specializing in applied machine learning for Natural Language Processing and Interconnected Systems . His work bridges Knowledge Graphs , Recommender Systems , and Graph Neural Networks , with a focus on large language models and retrieval-augmented generation. Ph.D. (2018), B.E. (2014) in Computer Science from Shanghai Jiao Tong University Postdoctoral Researcher : Stanford University (2019-2021), University of Illinois Urbana-Champaign (2021-2022) Dr. Wang’s research explores integrating Knowledge Graphs with Graph Neural Networks to enhance recommendation systems, language models, and information retrieval. His work spans Retrieval-Augmented Generation , Representation Learning , and GAN-based Graph Modeling , with recent papers on State-Space Exploration for LLM agents and Semantic Watermarking . His 15 most recent publications (2022-2024) focus on Retrieval Granularity , Interactive Memory , and Agent Systems , with keywords spanning Computer Science , Machine Learning , and Knowledge Graphs . Trends highlight advancements in Token-Level Semantic Matching , Schema-Guided Event Prediction , and Multi-Document Summarization . Scientific Awards: 2020 CCF Outstanding Doctoral Dissertation Award 2018 Google Ph.D. Fellowship Dr. Wang contributes to open-source projects like DKN and RippleNet , with 11 repositories on GitHub. He actively engages in Knowledge Graph Conferences (KDD, WWW, AAAI) and studies Chinese Classical Poetry and Film Arts .
Peter Matthias Stoffer is an SNSF Eccellenza Professor at the University of Zurich and a Tenure-track scientist at the Paul Scherrer Institute (PSI). His research is currently funded by a SNSF project grant at PSI and an SNSF professorial fellowship, jointly hosted by the University of Zurich and PSI. Previously, he held positions as a University assistant at the University of Vienna (2020-2021), Postdoctoral researcher at UC San Diego (2019-2020), SNSF postdoctoral research fellow at UC San Diego (2017-2018), and Postdoctoral researcher at the University of Bonn (2014-2016). Stoffer's research focuses on effective field theories for physics beyond the Standard Model (SMEFT, LEFT), non-perturbative methods for low-energy hadron physics including dispersion relations and chiral perturbation theory, matching to lattice-QCD schemes, and applications to precision observables such as dipole moments, CP violation, and lepton-flavor violation. His work is particularly relevant to understanding the muon anomalous magnetic moment (g-2) and other precision tests of the Standard Model. The analysis of his recent publications reveals a strong emphasis on renormalization group equations for effective field theories, hadronic light-by-light scattering, and precision calculations related to the muon g-2 anomaly. His work spans both theoretical developments in effective field theory and practical applications to current experimental puzzles in particle physics. Stoffer has received the prestigious SNSF Eccellenza Professorship, which supports outstanding early-career researchers in establishing their own independent research groups. His research group maintains close connections between the University of Zurich and PSI, leveraging the complementary strengths of both institutions.
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.
