Prof. Rainer Wallny is a Full Professor of Physics at ETH Zurich and Head of the Institute for Particle Physics and Astrophysics. His research focuses on high-energy particle physics, particularly through the CMS experiment at the Large Hadron Collider (LHC), emphasizing Higgs boson studies and detector upgrades. He leads projects on Higgs boson characterization in photon and b-quark final states, as well as CMS pixel detector upgrades for Phase-2. His group also explores future collider technologies and contributes to teaching at all academic levels. Education: Studied Physics at Universities of Tübingen, Washington (M.Sc., 1994), and Heidelberg (Diplom, 1996) PhD in Physics from University of Zurich CERN Research Fellow (2001–2003) Faculty at UCLA (2003–2010), promoted to Full Professor in 2010 Joined ETH Zurich as Full Professor in 2010 Research Interests: Higgs boson properties and decay channels Supersymmetry searches in CMS data Detector development for CMS (pixel trackers, diamond sensors) Phase-2 LHC upgrade technologies Experimental particle physics at high-luminosity colliders Grants and Advising: Supervised over 20 PhD students since 2010 Leadership roles in CMS collaboration and detector R&D initiatives Active in curriculum design for physics education at ETH Labs & Teams: Wallny Group at ETH Zurich Institute for Particle Physics and Astrophysics (D-PHYS) Collaborations with CERN and global CMS teams
Federica Sandrone is a Lecturer at the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as a Scientist at the Laboratory of Experimental Rock Mechanics (LEMR) within the Institute of Civil Engineering. Her academic career spans over 15 years with continuous contributions to tunnel engineering and rock mechanics research. Her research focuses on the intersection of rock mechanics and tunnel engineering, with particular expertise in tunnel pathology analysis, TBM performance in challenging geological conditions, and long-term tunnel behavior. Sandrone's work bridges theoretical analysis with practical engineering applications, addressing real-world problems in tunnel infrastructure management and maintenance. Her research methodology combines field investigations, laboratory testing, and numerical modeling to understand complex geomechanical behaviors. Analysis of her recent publications reveals a consistent focus on tunnel inspection methodologies, TBM performance prediction in difficult ground conditions, and the long-term behavior of tunnel structures. Her work has evolved from fundamental tunnel pathology studies to more advanced applications involving GIS integration, probabilistic modeling, and modern inspection techniques including laser scanning and image analysis. Engineer at SBB-Infrastructure (2008-present) responsible for Tunnels Management and Maintenance Assistant for Tunnel Engineering courses (2007-present) PhD supervision including Erika Paltrinieri's 2015 thesis on TBM performance Development of tunnel inspection methodologies and condition assessment procedures Her teaching activities include courses in Rock Mechanics and Underground Construction, where students learn about the mechanical behavior of rock materials, tunnel excavation and support design, planning and management of underground works, and risk assessment in tunnel construction.
Bozidar Stojadinovic is a Full Professor and Chair of Structural Dynamics and Earthquake Engineering at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering. He leads the Institute of Structural Engineering and previously held professorships at UC Berkeley and the University of Michigan. His research focuses on community disaster resilience, seismic design, and experimental methods like hybrid simulation. Education: PhD in Civil Engineering, UC Berkeley (1995) MS in Civil Engineering, Carnegie-Mellon University (1990) BS in Civil Engineering, University of Belgrade (1988) Research Interests: Performance-based probabilistic resilience evaluation of civil infrastructure. Earthquake engineering, including seismic isolation and response modification techniques. Development of experimental testing methods, such as hybrid simulations for dynamic structural analysis. Awards: ICE Journal John Henry Garrood King Medal (2023) ACI Chester Paul Siess Award (2017) NSF CAREER Award (1999) Teaching & Advising: Teaches courses on seismic design and structural dynamics at ETH. Advised 49 doctoral students to date. His work integrates advanced methodologies to enhance structural resilience against natural hazards. Labs/Teams: Leads ETH's Institute of Structural Engineering, advancing research in seismic protection and infrastructure resilience through experimental and computational innovations.
Jürgen Sauer is a Full Professor at the University of Fribourg , affiliated with the Department of Psychology under the Faculty of Letters and Human Sciences . With over 120 publications, his research focuses on Human-Machine Interaction , Usability Testing , User Experience (UX) , and Automation Design , particularly in high-stakes environments like X-ray baggage screening and spaceflight simulations . Email: juergen.sauer@unifr.ch Phone: +41 26 300 7622 Address: RM 01 bu. C-1.117, Rue PA de Faucigny 2, 1700 Fribourg Orcid: 0000-0003-2105-1694 His research projects, funded by the Swiss National Science Foundation (FNS), include: Improving work design for airport security officers (2019-2024): Developed pictorial scales for measuring psychological constructs in security environments. Social stress and support in hybrid teams (2018-2023): Investigated machine-induced social stressors and mitigation through social support. Automation in visual inspection tasks (2014-2018): Examined adaptable automation for baggage screening and system reliability effects. Usability testing effectiveness (2012-2016): Analyzed cultural background impacts and non-usability product features influencing test outcomes. Key contributions include the Luggage Inspection Simulation (LIS) environment for modeling work environments and the development of pictorial usability scales for multilingual applicability. His work bridges ergonomics , human factors , and applied psychology , with notable collaborations with researchers like Adrian Schwaninger and Andreas Sonderegger . His recent publications (2025-2014) analyze: Human-machine performance under false alarms and miscues Social stressor dynamics in hybrid teams Usability scale animation effects Phubbing behavior in professional contexts Accessible website design for non-disabled users
Matthias Bannert is a Lecturer at the Department of Management, Technology, and Economics at ETH Zürich, where he works at the KOF Swiss Economic Institute (Konjunkturforschungsstelle). His work focuses on the intersection of economics, software development, and data management, with particular expertise in time series analysis and official statistics. Bannert designs solutions for state-of-the-art data processing, management, and publishing of economic data and research. Bannert completed his doctoral thesis titled "Survey Based Research in Economics - Essays on Methodology, Economic Applications and Long Term Processing of Economic Survey Data" at ETH Zürich in 2016. His academic journey began when he joined KOF in late 2008, initially working as a researcher for the Business Tendency Survey group before transitioning to the institute's IT department. Dr. Bannert's research interests span several interconnected domains at the nexus of economics and data science. He specializes in developing software environments for official statistics, with particular focus on processing and managing economic time series data through open-source driven data pipelines. His technical expertise includes R programming and PostgreSQL database systems, which he applies to create robust solutions for economic data analysis. Bannert is particularly interested in survey methodology, nowcasting techniques, and the development of reproducible research workflows. His work bridges the gap between theoretical economics and practical software implementation, ensuring that economic research can leverage state-of-the-art data processing techniques. Analysis of Bannert's publication record reveals a consistent focus on the application of data science techniques to economic research problems, particularly in the domain of official statistics and survey-based economics. His work demonstrates a progression from theoretical survey methodology to practical software implementation, with increasing emphasis on real-time economic forecasting and data management systems. A distinctive feature of his research is the development of open-source R packages that make advanced economic data analysis more accessible to researchers and practitioners. As an active contributor to the R language for Statistical computing and the open source community, Bannert has developed several notable software packages including timeseriesdb, tstools, and kofdata, which are available on CRAN. These tools reflect his commitment to creating reproducible, transparent, and efficient workflows for economic data analysis. Bannert serves as a data science supervisor for multiple KOF research projects and is a co-Principal Investigator in an SNF-funded Digital Lives project in collaboration with KOF's labor market expert group. His teaching activities include "Hacking for Sciences - An Applied Guide to Programming with Data" and involvement in the Nowcasting Lab, which provides live out-of-sample forecasting and model testing capabilities for economic researchers. Dr. Bannert is affiliated with the KOF Swiss Economic Institute, where he contributes to several research groups including the KOF Macroeconomic Forecasting group and the KOF Data Science and Macroeconomic Methods group. His work at KOF bridges the institute's traditional economic research with modern data science approaches, helping to position the institute at the forefront of data-driven economic analysis.
Cécile Münch-Alligné is a Professor in Hydraulic Energy at the University of Applied Sciences and Arts Western Switzerland (HES-SO) in Sion, where she serves as the Head of the Hydroelectricity Research Group and the Renewable Energy Program. She leads the Hydro Alps Lab, which conducts applied research in hydropower combining experimental and numerical approaches. Her work focuses on enhancing the flexibility of both small and large hydropower plants, with particular emphasis on adapting these systems to the evolving energy landscape and integration of renewable energy sources. Her educational background includes a BSc in Energy and Environmental Techniques, an MSc in Engineering, and a BSc in Industrial Systems, all from HES-SO Valais-Wallis. Her research spans multiple domains within hydraulic engineering and renewable energy systems, with particular expertise in CFD simulation, numerical methods, and hydraulic machine design. Münch-Alligné's research interests primarily center around improving hydropower flexibility through innovative approaches such as hydraulic short-circuit operating modes, variable speed operation, and energy recovery systems in water networks. She investigates both large-scale pumped storage power plants and micro-hydropower systems for urban water networks, with a strong focus on practical implementation and commercialization of research findings. Her work bridges theoretical modeling with experimental validation to address real-world challenges in the energy transition. Her research has been published extensively in leading journals, covering topics from Pelton turbine dynamics and Francis turbine vortex analysis to micro-turbine implementations in drinking water networks. The publications reveal a clear trend toward enhancing operational flexibility of hydropower systems to better integrate with intermittent renewable energy sources, with increasing emphasis on practical demonstration projects and commercial applications. As Principal Investigator, she has led multiple significant research projects including the SCCER 4 WP 3.2.0 2017-2020 (Supply of Electricity), Hydrolienne pour canaux artificiels Centrale de Lavey, and SOLUTION DE TRANSFERT D'ENERGIE PAR POMPAGE-TURBINAGE A PETITE ECHELLE. These projects, totaling over 2 million CHF in funding from sources including CTI, OFEN, and industrial partners, demonstrate her ability to secure substantial research funding and collaborate effectively with both academic and industry partners. Münch-Alligné leads the Hydro Alps Lab research team, which includes numerous researchers such as Steiner Amandus, Walpen Olivier, Vaccari Aldo, and others. Her collaborative approach extends to partnerships with institutions like Stahleinbau GmbH and The Ark Energy, facilitating the transfer of knowledge from research to industry application. The lab's work spans from fundamental fluid dynamics research to full-scale demonstration projects, creating a comprehensive pipeline from theory to practical implementation.
Peter Grünwald is full professor of Statistical Learning at Leiden University's Mathematical Institute and senior researcher in the Machine Learning group at CWI (Centrum Wiskunde & Informatica) in Amsterdam. His pioneering work on e-values establishes a transformative framework for statistical inference that overcomes critical limitations of classical p-values, enabling flexible experimental designs while maintaining rigorous error control. His research centers on e-values and e-processes as a unifying paradigm between Bayesian and frequentist statistics, with core innovations in safe testing, anytime-valid inference, and optional continuation. These methods allow researchers to gather additional data after initial analysis without inflating Type I errors and to determine significance levels post-hoc—addressing longstanding rigidity in Neyman-Pearson hypothesis testing. His publication trajectory reveals rapid adoption of e-values across disciplines: from foundational theory in PNAS and JRSSB to clinical applications in survival analysis (NEJSDS) and epidemiology (medrxiv meta-analysis). The 2022–2024 publications demonstrate methodological maturation, with implementations in R (safestats package) and growing use in social sciences (PsyArXiv) and causal inference (JASA). Scientific recognition includes: ERC Advanced Grant (2024) for developing flexible statistical inference theory via e-values His ERC-funded project drives current research, while his internship policy restricts non-Dutch master’s/bachelor’s students but welcomes advanced international PhD candidates. Collaborative work spans statisticians (Ly, de Heide, Koolen), machine learning researchers (Ramdas, Shafer), and medical scientists (van Werkhoven). As core member of CWI's Machine Learning group, he advances theoretical foundations with practical impact—evidenced by the first live deployment of e-values in a BCG vaccine meta-analysis. His work redefines statistical practice for adaptive data collection in clinical trials, AI, and social science research.
Dr. Stefan Ritt is a prominent researcher and Group Leader of the Muon Physics group at the Paul Scherrer Institute (PSI) in Switzerland. With over 30 years of experience in particle physics, he has made significant contributions to muon decay experiments and detector development. His research focuses on precision measurements of muon properties and searches for physics beyond the Standard Model. Ritt's primary research interests encompass particle physics, muon physics, detector development, and data acquisition systems. His work has been instrumental in advancing high-precision measurements of muon decay processes, particularly in the search for lepton flavor violation. He has pioneered developments in waveform digitizing technology, most notably through the Domino Ring Sampler (DRS) series of chips, which have revolutionized data acquisition in particle physics experiments. Analysis of his recent publications reveals a strong focus on the MEG and MEG II experiments, which search for the rare decay μ+→e+γ. His work spans detector design, data acquisition systems, trigger implementation, and precision analysis techniques. The publications demonstrate expertise in liquid xenon detectors, silicon photomultipliers, timing resolution, and high-speed waveform digitization. 1984 Jugend Forscht Landessieger 2011 IEEE Senior Member 2016 IEEE Fellow for the development of the Domino Ring Sampler series of chips 2020 IEEE Emilio Gatti Radiation Instrumentation Technical Achievement Award for contributions to the development and democratization of ultra high-speed digitizers Ritt has served as a thesis examiner for institutions including INFN Pisa and ETH Zurich, demonstrating his role in academic mentoring. His leadership extends to coordinating beam time for PSI's secondary particle beam lines and organizing major international workshops. He has been instrumental in developing the Mu3e experiment and advancing muon beam technology at PSI. As head of the Muon Physics group (comprising 12 members), Ritt oversees fundamental particle physics experiments at PSI's secondary beam lines. His group is responsible for the design and implementation of data acquisition hardware and software for the MEG II experiment and serves as co-spokesperson for the Mu3e experiment.
Gianvito Laera is a Postdoctoral Research Fellow at the University of Geneva's Department of Psychology within the Faculty of Psychology and Educational Sciences. He works in the Cognitive Aging Lab, focusing on prospective memory research with particular emphasis on time-based memory processes across the lifespan. His research integrates cognitive psychology, neuroscience, and gerontology to understand how people remember to perform future intentions. Dr. Laera received his PhD in Psychology from the University of Geneva (2018-2023), following a Master of Science in Neuroscience and Neuropsychological Rehabilitation from the University of Padua, Italy (2013-2016), and a Bachelor of Science in Psychological Sciences and Techniques from the University of Bari 'Aldo Moro', Italy (2010-2013). Prior to his doctoral studies, he worked as a Research Assistant at Keele University's Neuropsychology Lab (2016-2018) and completed a research internship at the University of Padua (2015-2016). His research primarily investigates prospective memory—particularly time-based prospective memory—which involves remembering to perform intended actions at specific future times. His work examines age-related differences in these processes, neural correlates using EEG methodology, strategic monitoring behaviors, and the impact of various contextual factors on memory performance. He employs both laboratory and web-based experimental approaches to study how people monitor time, check clocks, and manage cognitive resources when executing delayed intentions. His research has important implications for understanding cognitive aging and developing interventions to support memory in older adults. Analysis of his publication record reveals consistent focus on time-based prospective memory mechanisms across 15 recent publications. His work demonstrates sophisticated methodological approaches including meta-analyses, experimental manipulations of clock-speed, EEG measurements, and longitudinal assessments. Key trends include examining the cost of monitoring behavior, strategic clock-checking patterns, neural correlates of memory retrieval, and the relationship between personality factors and cognitive performance in aging populations. While no specific scientific awards are documented in the available information, his research has been published in high-impact journals across psychology, neuroscience, and gerontology, reflecting recognition within his field. As a postdoctoral researcher, Dr. Laera continues to develop his independent research program while collaborating with senior researchers in the Cognitive Aging Lab. His work bridges experimental cognitive psychology with real-world applications for understanding memory changes in aging populations.
Farhad Rachidi is a Full Professor at the Swiss Federal Institute of Technology (EPFL), where he serves as the Head of the Electromagnetic Compatibility (EMC) Laboratory within the School of Engineering's Department of Electrical Engineering. His research group has been active in EMC research since the early 1980s and maintains collaborations with numerous international institutions including Universities of Bologna and Rome (Italy), Uppsala University and KTH (Sweden), University of Toronto (Canada), University of Florida (USA), and others. Professor Rachidi's research spans electromagnetic compatibility, lightning electromagnetics, lightning and EMP interaction with transmission lines, electromagnetic time reversal, fault location, numerical computation of electromagnetic fields, and power line communications. His work integrates theoretical modeling with experimental validation, particularly in the context of lightning phenomena and electromagnetic interference. The research group develops innovative techniques such as electromagnetic time reversal for applications ranging from lightning detection to partial discharge localization in power systems. Analysis of his recent publications (2023-2025) reveals a strong focus on electromagnetic time reversal techniques, lightning physics and modeling, machine learning applications in electromagnetic phenomena, and advanced computational methods for electromagnetic field analysis. His work bridges fundamental electromagnetic theory with practical applications in power systems, atmospheric electricity, and security technologies. 2025 IEEE EMC Technical Achievement Award 2005 CIGRE Technical Committee Award 2006 Blondel Medal from SEE 2016 Berger Award from ICLP Best Paper Awards of IEEE Transactions on EMC (2016, 2018) Motohisa Kanda Award for most cited papers (2012-2018) 2024 Distinguished Honorary Professor at Tsinghua University 2014 Honorary Professor at Xi'an Jiaotong University Professor Rachidi has supervised numerous students through semester projects, diploma projects (equivalent to MS), and PhD programs at EPFL. His research is primarily sponsored by Swiss National Science Foundation, European Community programs, European Space Agency, Swiss Electrical Utilities, and private companies. He has served in leadership roles including President of the International Conference on Lightning Protection (2008-2014), Editor-in-Chief of IEEE Transactions on Electromagnetic Compatibility (2013-2015), and President of the Swiss National Committee of the International Union of Radio Science (2012-2020). The EMC Laboratory at EPFL, which he heads, maintains the Säntis lightning research facility and has been instrumental in advancing our understanding of lightning phenomena through direct measurements at instrumented towers. The group has developed innovative techniques including electromagnetic time reversal for fault location in power networks and lightning detection systems.
Florencia Malamud is a Researcher and Instrument Scientist at the Paul Scherrer Institute (PSI), leading the POLDI instrument in the Laboratory for Neutron Scattering and Imaging. Her work focuses on advanced neutron-based techniques for material characterization, including Bragg edge imaging, diffraction contrast imaging, and texture analysis. She specializes in studying crystallographic structures, phase transformations, and mechanical behaviors in materials such as high-Mn steels, superalloys, and superconductors. Her research integrates experimental methods like neutron diffraction and tomography to investigate industrial materials (e.g., additive manufacturing components) and historical artifacts (e.g., Napoleonic-era copper bolts). Key areas include optimizing material properties through composition and processing, and understanding deformation mechanisms in metallic materials. Malamud’s publications span materials science, metallurgy, and neutron scattering applications. She collaborates on projects involving nuclear-grade materials, aerospace alloys, and archaeological metallurgy. Her work emphasizes bridging fundamental physics with applied engineering challenges. No scientific awards are explicitly mentioned. Her advising and grants are not detailed in the provided texts. She is affiliated with PSI’s neutron scattering laboratory and contributes to instrumentation development for advanced materials research.
Prof. Dr. Robert Eberlein is a Senior Lecturer in Mechanics at the ZHAW School of Engineering , specifically working at the Institute of Mechanical Systems (IMES) . He has served as Director of IMES since 08/2017, following previous roles as Senior Lecturer at IMES (11/2013-07/2017) and industry leadership positions including CTO of Angst+Pfister Group (06/2006-10/2013). Dr. Eberlein holds a Dr.-Ing. (PhD) in Numerical Mechanics from Darmstadt University of Technology (1992-1997) and completed an exchange program at UC Berkeley (1991-1992). Education: Dr.-Ing. (PhD) in Numerical Mechanics, Darmstadt University of Technology (07/1992-07/1997); Exchange Student at University of California, Berkeley (07/1991-06/1992) Professional: Director of Institute IMES (08/2017-today); Senior Lecturer at IMES (11/2013-07/2017); CTO & Group Executive Committee, Angst+Pfister Group (06/2006-10/2013); Group Leader in Biomechanics, Sulzer Innotec (07/1998-04/2006) Dr. Eberlein focuses on experimental and numerical modeling of solid polymers and lightweight structures. His research spans material modeling, finite element analysis, and fatigue life prediction for materials like POM gears, TPU and vulcanizates. Recent work explores digital twin development for rubber spring elements and machine learning enhanced process simulation in additive manufacturing. His projects include Lifetime prediction of POM gears , Measurement of human soft tissue properties , and Optimization of plastic gear geometry . Scientific achievements include: Professor ZFH (Fachhochschulrat) - 12/2019 Dr.-Ing. (PhD) summa cum laude - Darmstadt University of Technology - 07/1997 Graduate Assistantship - Darmstadt University of Technology - 01/1993 His work appears in journals like International Journal of Non-Linear Mechanics , Rubber Chemistry and Technology , and Journal of Loss Prevention in the Process Industries . Publications since 2015 show a consistent focus on material characterization , finite element modeling , and fatigue analysis with applications in industrial components and biomedical systems.
Ben Jann is a Professor and current Department Head at the University of Bern in the Department of Social Sciences . His methodological expertise spans statistical software development, decomposition analysis, and data visualization. Role: Department Head Institution: University of Bern Department: Department of Social Sciences Research Interests : Jann specializes in creating Stata modules for advanced statistical analysis, including geospatial mapping (geoplot), robust regression (robreg10), and inequality decomposition (oaxaca-blinder methods). His substantive work examines social inequality through economic and sociological lenses, analyzing how living costs and taxation systems impact income distribution in Switzerland. He also investigates educational transitions and gender disparities in STEM occupational choices through longitudinal studies like TREE2. Recent Publications Trends : Jann’s 15 most recent articles (2025-2023) demonstrate his focus on statistical software development for social science applications. Key contributions include methods for marginal odds ratios (2023), two-level model variance decomposition (2025), and list experiment analysis (2025). His empirical work connects statistical methodology to pressing social issues like gender wage gaps (2021) and teacher content knowledge in developing countries (2021).
Prof. Dr. Heinz Burtscher serves as Professor at the FHNW University of Applied Sciences Northwestern Switzerland since 1996, where he founded and led the Institute of Aerosol and Sensor Technology until 2018. Affiliated with the School of Engineering and Environment , he specializes in Aerosol Measurement Technology and Measurement and Sensor Technology with focus on combustion-generated nanoparticles, environmental aerosol monitoring, and sensor development for particulate matter analysis. PhD in Electrical Engineering (1980) from ETH Zurich Postdoctoral qualification in experimental physics (1991) on combustion aerosols His research interests span: Characterization of small particles from combustion processes (e.g., diesel soot, wood burning) Development of field measurement techniques for particle emissions Advancements in sensor technology for ambient air monitoring Toxicological evaluation of nanoaerosols Innovations in exhaust gas cleaning systems Recent publications address sub-23 nm particle measurement , e-cigarette vapor characterization , and real-time SOA formation potential in combustion emissions. He received the Smoluchowski award (1994) from the Gesellschaft für Aerosolforschung (GAeF) and maintains active membership in GAeF and the Swiss Aerosol Group. As both educator and researcher, Burtscher teaches Power electronics , Electrical drives , and Sensor systems while leading projects on: Volcanic ash detection systems Nanoparticle exposure assessment Vehicle cabin air filtration Periodic emission inspection protocols He works closely with the Institute for Sensors and Electronics at FHNW and collaborates with ETH Zurich's combustion research groups.
Clarissa Janousch is a Research Fellow affiliated with the Jacobs Center for Productive Youth Development and the Laboratory for Experimental and Clinical Pharmacopsychology at the University of Zurich . Her work bridges developmental psychology, substance use research, and quantitative methodologies. PhD focus: Resilience conceptualization and measurement in adolescents Current research: Substance use effects on cognitive abilities and real-life functioning Methodological expertise: Quantitative approaches, latent profile/transition analyses, NLP techniques Her research spans biopsychosocial mechanisms for positive adjustment, with a strong emphasis on data-driven methods. Key publication trends include: Longitudinal NLP analysis of life events in urban cohorts Validation of substance use biomarkers via hair samples Acculturation attitudes in multicultural education Peer status dynamics as risk/protective factors Resilience profiles across cultural contexts Cannabis use impacts on young adult well-being
