Dr. Sverrir Thorgeirsson is a Professor of Computer Science at ETH Zürich, affiliated with the Department of Computer Science under the School of Computer and Communication Sciences. His work focuses on innovative educational technologies and pedagogical frameworks to enhance programming education. His research interests include visual programming languages (e.g., Algot), cognitive aspects of learning (e.g., cognitive load measurement via EEG), and strategies to improve abstraction skills and software testing comprehension in students. He emphasizes bridging the syntax-semantics gap in programming through hands-on, interactive tools. Recent publications highlight his contributions to visual programming environments, failure-based learning, and the design of pedagogical frameworks. He actively explores how cognitive science principles can optimize educational outcomes in introductory and advanced CS courses. No scientific awards were explicitly listed. His advising and grants sections remain under development, pending additional data.
Dr. Baran Gözcü is a Lecturer at the Department of Computer Science at ETH Zürich, Switzerland. His professional affiliation includes the Informatik (Computergraphik) division, located at Universitätstrasse 6 in Zürich. Contact information includes the office CNB G 101 and a direct phone number. Research interests are inferred to focus on computer graphics, visualization, and related computational methodologies within the broader discipline of computer science. Specific subtopics may include rendering techniques, interactive systems, or computational geometry, though explicit research details are not provided in the text. No awards, grants, or published articles are listed in the provided information. The lecturer's homepage can be found at sites.google.com/view/barangozcu for further details.
Roles & Affiliations: PD Dr. Alexander Ilic is a Lecturer at the Department of Computer Science and Executive Director of the ETH AI Center at ETH Zürich. He co-founded the ETH AI Center and previously led Magic Leap Switzerland, focusing on R&D in Computer Vision and Advanced Photonics. He holds a PhD from ETH Zurich and a habilitation from the University of St. Gallen. Education: PhD in Computer Science, ETH Zurich Habilitation in Entrepreneurship, University of St. Gallen MSc in Computer Science, TU Munich Research Interests: Alexander’s work spans Artificial Intelligence, Entrepreneurship, and Technology Investing. He pioneered AI-driven start-ups like Dacuda (acquired by Magic Leap) and developed cutting-edge sensors and imaging systems. His research emphasizes real-time systems, computer vision applications, and wearable technology. Notable Achievements: Co-founder of Dacuda and Magic Leap Switzerland 两次获得“Entrepreneur of the Year”（2011年和2012年） Swiss Economic Award Over 50+ patents in imaging, AR, and sensor technology Courses Taught: Data Science Lab Technology Investing Patenting Digital Innovations Technology and Entrepreneurship Labs & Leadership: Leads the ETH AI Center, driving AI innovation and interdisciplinary projects. His teams focus on applied AI in real-time systems and cross-reality devices.
Dr. Corinna Lorenz is a researcher at the Institute of Neuroinformatics, ETH Zürich, Switzerland, where she investigates neural mechanisms underlying behavior through computational and experimental approaches. Her work bridges neuroscience, machine learning, and animal behavior studies, primarily utilizing songbird models and advanced neurotechnologies. Her research focuses on computational neuroscience and neuroethology, with emphasis on vocal circuit dynamics in zebra finches. She develops innovative machine learning tools for neural data analysis, including vocal unit extraction from embedding spaces and chronic Neuropixels recordings. Additional interests span sensory processing (serotonin modulation in visual cortex) and body representation studies (rubber hand illusion), reflecting interdisciplinary expertise in neural coding and behavior. Analysis of her 12 recent publications (2012-2025) reveals three dominant themes: (1) Songbird vocal circuit dynamics during sleep/wake states and behavioral contexts, (2) Machine learning applications for unsupervised vocal analysis, and (3) Cross-species investigations of neural modulation in sensory systems. Her work consistently integrates custom hardware/software solutions with ethological paradigms. Dr. Lorenz maintains active research operations at ETH Zürich's Institute of Neuroinformatics (Y55 G 72), utilizing chronic recording methodologies and interactive data analysis frameworks. Her team develops open-source tools for vocal unit extraction and neural population analysis, contributing to reproducible neuroethology research.
Dr. Yulia Sandamirskaya is the Head of the Research Center 'Cognitive Computing in Life Sciences' at Zurich University of Applied Sciences (ZHAW), where she leads a research group focused on neuromorphic cognitive architectures for embedded AI systems. Her work integrates neural dynamics with robotic control , spanning real-time tasks such as sensing, planning, decision-making, learning, and motor control for assistive robots. She collaborates extensively with institutions like ETH Zurich and KTH Royal Institute of Technology, utilizing neuromorphic hardware such as dynamic vision sensors (DVS) and robotic platforms. Her research encompasses neuromorphic architectures for obstacle avoidance, path integration, and sequence learning, as well as theoretical frameworks like Dynamic Neural Fields (DNFs) for cognitive modeling. She explores autonomous learning mechanisms, including unsupervised and reinforcement learning, and applies these to robotics in domains such as spatial language grounding and haptic exploration . Her group has published extensively on topics like event-based vision , resonator networks , and hardware implementations of neural algorithms. Dr. Sandamirskaya has supervised multiple MSc theses on neuromorphic systems and robotic applications, with advisees working on projects like UAV obstacle avoidance, tactile object recognition, and neural-dynamic sequence generation. She actively contributes to workshops and conferences, including Science Robotics , CVPR , and IEEE conferences , and her work addresses challenges in low-power, high-speed robotic agents operating in real-world environments.
Stephan Müller is a Lecturer at the Department of Physics, ETH Zürich, affiliated with the IT Services Gruppe (ISG D-PHYS). His work focuses on educational technology, particularly leveraging Minecraft for collaborative learning and behavioral analysis through tools like Heapcraft. He specializes in data visualization, game studies, and human-computer interaction. Research interests revolve around understanding and optimizing player collaboration in digital environments, with applications in both gaming and education. His recent contributions include developing interactive tools to quantify and influence collaborative behaviors in Minecraft, blending computer science with educational methodologies. Stephan teaches the course 'Basics of Computing Environments for Scientists' (402-0010-00L) in the Autumn Semester 2025, emphasizing computational foundations for scientific research.
Prof. Alexandre Refregier is a Full Professor at the Department of Physics, ETH Zürich. He leads research in cosmology and astrophysics, focusing on dark energy, dark matter, and large-scale structure analysis using observational, theoretical, and instrumental approaches. His work spans gravitational lensing, cosmic microwave background, and galaxy cluster studies. He has contributed to major projects like the Dark Energy Survey and Euclid mission, leading instrumental development and data analysis efforts. Refregier holds a PhD from Columbia University (1997) and has held positions at institutions including Princeton University and the University of Cambridge. Education: PhD in Physics, Columbia University, 1997 M.Phil. and M.A. in Physics, Columbia University, 1992–1993 B.S. in Physics (Summa cum Laude), University of Texas at Austin, 1991 Research Interests: Dark energy/dark matter dynamics, weak lensing, baryon acoustic oscillations, cosmic microwave background analysis, and cosmological probes. His interdisciplinary methods combine theoretical modeling with cutting-edge observational techniques and instrument design. Key Contributions: Over 200 published papers (e.g., on Euclid mission instrumentation, joint lensing-CMB analyses, and baryonic feedback modeling). Active in developing simulation tools like PyCosmo and GalSBI for cosmological inference. Awards/Grants: Not explicitly listed, but his leadership in major collaborations implies significant funding and recognition. Active in Simons Foundation-supported research. Labs/Teams: Leads the Cosmology Group at ETH Zurich, involved in Euclid's science and instrument teams, and collaborates on projects like HIRAX and SKA simulations.
Shreyasvi Natraj is a doctoral student at the Department of Health Sciences and Technology (D-HEST) at ETH Zurich, Switzerland. She holds a Bachelor of Engineering in Biotechnology from R.V. College of Engineering (2015-2019) and a Master of Science in Neuroscience from the University of Geneva (2019-2022). Her interdisciplinary work bridges biomedical engineering, artificial intelligence, and hardware development. Research Interests: Biomedical device prototyping Neural network applications in healthcare Low-cost environmental/safety technologies Human-computer interaction for accessibility Projects: $50 Bacteriological Incubator Assist Bot (AR/VR sensor-based robot) Water purification module Puri-Pod Toxic gas analyzer for salt farmers CovARC (COVID risk calculator web app) Her academic journey includes research assistantships at NCCR Synapsy (2019-2023), technical roles at CERN (2018-2022), and co-founding the EPFL startup NeuralWorks. She actively contributes to GitHub repositories related to medical diagnostics and environmental monitoring.
Andreas Vitalis is a Senior Scientist in the Department of Biochemistry at the University of Zurich, where he leads the development of molecular simulation software (CAMPARI) and research platforms. He holds a Ph.D. in Molecular Biophysics from Washington University (St. Louis) and conducted postdoctoral research at UC San Diego and Zurich. His expertise spans protein aggregation mechanisms, computational biophysics, and high-performance computing. Education: Ph.D. in Molecular Biophysics, Washington University in St. Louis (2003-2009) Research Scholar, University of California San Diego (2001-2002) Diploma in Biochemistry, Ruhr-Universität Bochum (1998-2001) Research Interests: Protein aggregation (Alzheimer's, Huntington's diseases) Molecular simulation methods (enhanced sampling, FAIR data) Drug discovery platforms and computational tools Neuroscience applications of biophysical modeling His work bridges computational methods with experimental biology, emphasizing scalable solutions for complex systems. Key contributions include CAMPARI software and FAIR-compliant data management frameworks.
Paolo Rossetti is a Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), where he teaches in the Master of Informatics and Economics program. He is also actively engaged as a management consultant and committee member for Mobsya Association, promoting educational robotics. His professional background includes leadership roles at Sun Microsystems and collaborations with Politecnico di Milano, University of Trento, and University of Padova. His research and professional interests focus on improving organizational performance through human-centered interventions. Key areas include: Process and performance improvement eLearning, mobile learning, and blended learning Lean Six Sigma and visual thinking Social network analysis and knowledge sharing Idea and change management Business Process Management (BPM) and model-driven software development Internet of Things (IoT) and digital transformation for SMEs While no formal academic publications are listed in the provided text, his recent work involves applied research contracts focused on extending software modeling to IoT scenarios, facilitating BPM adoption, and applying idea management in digital transformation projects—indicating a strong trend toward practical, industry-aligned innovation in information systems and organizational development. He has contributed to the design of globally used tools for talent management, competency modeling, and performance evaluation during his tenure at Sun Microsystems. These tools were deployed worldwide by learning specialists and consultants. His advisory and consulting roles include: Management Consultant and Committee Member, Mobsya Association (2016–present) Learning and Content Strategy for WebRatio and IoT business development (2013–2016) Content development contracts with Politecnico di Milano and University of Trento Idea management consultancy for Nosco in Italy and Switzerland He previously founded flipfly srl, an eLearning startup, and held progressive leadership roles at Sun Microsystems from 1995 to 2008, including WW Talent Management Program Manager and various regional education leadership positions. He has also served as a university professor at Politecnico di Milano (IT Service Management, 2005–2006) and University of Padova (Distributed Software Development, 1997–2001).
Jan Pieter Abrahams is a Professor and Group Leader of the Nanodiffraction group at the Laboratory for Multiscale Bioimaging, Paul Scherrer Institute (PSI) in Switzerland. His work focuses on developing electron diffraction technologies for atomic-resolution imaging of frozen hydrated biological samples, leveraging PSI's detector expertise to advance structural biology beyond conventional microscopy limitations. Current applications target mitochondrial stress mechanisms in neurodegeneration and aging, with active collaborations across international institutions. Research Interests: Abrahams pioneers electron diffraction and cryo-EM methodologies, emphasizing computational-phasing innovations and machine learning integration. His group specializes in: Overcoming dynamical scattering for atomic-level cellular visualization Hybrid pixel detector applications (JUNGFRAU, EIGER) in electron microscopy Deep learning frameworks for diffraction data processing (e.g., DiffraGAN) Structural analysis of protein nanocrystals in disease contexts Mitochondrial protease mechanisms in aging Bacterial cell division and sporulation structures Publication Trends: Recent work (2020–2024) reveals heavy emphasis on AI-driven structural biology, including generative networks for diffraction phasing and lossless data compression. Instrumentation advancements (e.g., Boersch phase shifters) and disease-focused studies (Alzheimer’s amyloid-beta, malaria heme processing) dominate, showcasing interdisciplinary convergence of physics, computation, and biomedicine. Scientific Awards: No specific awards or fellowships documented in source text Advising and Collaborations: Abrahams has mentored PhD students including Thakkar, Pooja; Rheinberger, Jan; Schärer, Martin; and Wennmacher, Julian. His team collaborates with PSI's detector group on sensor development (GaAs/CdTe) and international labs for structural studies. Funding likely stems from PSI instrumentation projects and disease-focused research initiatives. Labs and Teams: He directs the Nanodiffraction group under PSI's Center for Life Sciences, comprising scientists (van Genderen, Latychevskaia) and postdocs (Blum). The lab integrates cryo-EM, electron diffraction, and computational modeling to visualize cellular processes at nanometer scales, with strong ties to detector engineering and pharmaceutical structural analysis.
Eva C. Herbst is a Postdoctoral Researcher in Shoulder Biomechanics at ETH Zurich's Institute for Biomechanics, Department of Health Sciences and Technology. She works in close collaboration with Prof. Dr. Stephen Ferguson at ETH and Prof. Dr. med. Philipp Moroder at the Schulthess Clinic, developing computational models to investigate dynamic joint loading in patients and maximize clinical impact. Her research integrates multi-body dynamics and finite element modeling to create shoulder biomechanics models for implant development and patient analysis. With a background in comparative biomechanics and paleontology, she maintains a strong interest in the link between form and function across biological contexts, applying evolutionary perspectives to clinical problems. Clinical biomechanics of the shoulder Computational modeling for implant development Finite element analysis and multibody dynamics Biomechanical analysis of patient-specific scenarios Comparative biomechanics across evolutionary time scales Dr. Herbst has developed several important computational tools that have gained recognition in the biomechanics community, including Spherical Frame Projections for visualizing joint range of motion, Trabecular Segmentation techniques for bone analysis, and MyoGenerator, a Blender add-on for 3D muscle modeling. She founded Finite Element Zurich to make finite element modeling more accessible by sharing resources, code, and workflows. Her publication record shows a clear progression from evolutionary biomechanics toward clinical applications, with recent work focusing on shoulder arthroplasty, osseous shoulder morphology, and patient-specific computational modeling. Her earlier research examined paleopathology in early tetrapods, cervical morphology in sloths, and salamander locomotion. She actively shares her research tools through GitHub, FigShare, and Morphosource, demonstrating a strong commitment to open science practices.
Mattia Albertini is a Post-Doctoral Researcher at the Institute for Economic Research (IRE) within the Faculty of Economics at Università della Svizzera italiana (USI). He previously completed his Ph.D. at the Institute of Economics (IdEP), USI, and participated in the Swiss Program for Beginning Doctoral Students in Economics. He holds a Master of Science in Economics with a minor in Data Science from USI and a Bachelor in Economics from the University of Pavia. Bachelor in Economics, University of Pavia Master of Science in Economics (minor in Data Science), Università della Svizzera italiana Ph.D. in Economics, Università della Svizzera italiana Swiss Program for Beginning Doctoral Students in Economics, Swiss National Bank His research focuses on applied microeconometrics with applications in health, labor, public, urban, and environmental economics. A recurring theme in his work is the spatial dimension of economic outcomes, including residential integration, real estate market dynamics, and geographic proximity to borders or hazards. He integrates data science techniques, particularly programming in Python and STATA, to develop tools for empirical analysis and reproducible research. The collection of articles reflects a strong trend in applied econometrics, causal inference, and spatial analysis. His work spans health economics (e.g., benzodiazepine prescribing), labor and urban economics (e.g., migration, job accessibility), and environmental and insurance economics (e.g., natural hazard impacts). Methodologically, he engages with difference-in-differences, event study designs, spatial modeling, and text analysis, often building or applying computational tools to address research questions. He has contributed to teaching at both the Bachelor's and Master's levels, particularly in microeconomics, macroeconomics, and data-intensive courses such as Textual Analysis and Spatial Data for Economists. Teaching Assistant, Microeconomics A (Bachelor) Teaching Assistant, Macroeconomics B (Bachelor) Teaching Assistant, Textual Analysis and Spatial Data for Economists (Master) Mattia Albertini is actively involved in open science, sharing code for econometric methods, data visualization, and application development (e.g., a gluten-checking app) on GitHub. His interdisciplinary approach combines economic theory, statistical modeling, and computational tools to investigate real-world policy-relevant questions.
Matija Piškorec is a Senior Research Associate at the Faculty of Informatics, University of Zurich. His research spans machine learning, complex systems, and blockchain technologies, with a focus on statistical inference of social influence and network analysis. Primary Affiliation: Faculty of Informatics, University of Zurich Research Interests Machine learning and complex systems Statistical inference of influence in online social networks Blockchain technologies and distributed ledger systems Information visualization and interactive web applications in computational biology Publications His recent work explores blockchain networks like Polkadot and Ethereum, analyzing their structure and consensus mechanisms. Earlier research focuses on social network influence, financial data cohesiveness, and computational biology tools. Awards No scientific awards or honors were explicitly mentioned in the text. Additional Contributions Developed web-based visualization tools (e.g., MultiNets) and applied machine learning to diverse domains, including microbiology and finance.
Chat Wacharamanotham is an external lecturer and researcher at Swansea University's Computational Foundry, having joined from the University of Zurich (UZH) in July 2022. Prior to UZH, he was affiliated with RWTH Aachen University in Germany. His work bridges interactive technologies and scientific decision-making, particularly in the context of statistics. His research interests lie at the intersection of Human-Computer Interaction, Interactive Statistics, and Scientific Decision-Making . He investigates how interactive tools can support scientists in planning experiments and interpreting statistical reports, using methodologies such as Human-Centered Design, Contextual Inquiry, and lab experiments with eye- and motion-tracking. His work emphasizes transparency, usability, and cognitive support in data analysis workflows. The recent publications highlight a consistent focus on interactive statistical tools, experimental design support, and gaze-based analysis . Projects like Argus, Touchstone2, and Statsplorer demonstrate a trajectory toward building interactive systems that guide users through complex statistical reasoning. The research integrates visualization, user interface design, and empirical evaluation, primarily within the HCI domain. While no scientific awards are listed in the provided text, his contributions to the field are evident through his active publication record in premier venues like CHI and IEEE TVCG. Chat Wacharamanotham is involved in teaching, including a seminar on Experiments in Human-Computer Interaction for Master's students. Although he is no longer available for thesis supervision, he continues to contribute to academic instruction at UZH. His research is conducted within a collaborative lab environment, as evidenced by co-authored works with teams from various institutions.
