Find Academic Supervisors

Michael HerzogView profile

Professor

• Psychophysics
• Visual Perception
• Cognitive Neuroscience
• +3 more

Michael Herzog is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Life Sciences and the Brain Mind Institute , where he leads the Psychophysics Laboratory . He contributes to teaching in programs such as SSV (Swiss Doctoral Program in Systems and Synthetic Biology) and EDNE (European Doctoral Neuroscience Program). Research Focus : Visual perception, non-retinotopic representation, cognitive neuroscience, and neural mechanisms of vision Teaching : Courses on statistics/experimental design and behavioral/cognitive neuroscience Leadership : PhD program committee member for the doctoral program in neuroscience His work explores how visual information transforms from retinotopic to non-retinotopic representations, addressing stability in perception despite retinal changes. Recent publications examine visual crowding, attentional modulation, and computational models of perception. Current and former PhD students include Allouche Melissa Mohamad, Lauffs Marc Michael, and 30+ advisees. His lab employs psychophysical experiments, EEG, and computational modeling to study vision in health and schizophrenia.

Franziska SchranzView profile

Researcher

• Building Physics
• Energy Efficiency
• Computational Physics
• +4 more

Franziska Schranz is a Researcher at the Zurich University of Applied Sciences (ZHAW) School of Engineering and part of the Institute of Computational Physics . Her work focuses on energy efficiency in buildings through computational simulations and machine learning. Current projects: Urban Positive Clean Neighborhood Energy Transition (team member), Polysun-ML (co-project leader) Past projects: Smart Urban Green Spaces , Detailed Building Energy Evaluation Her research spans building physics , smart building systems , and urban energy sustainability , integrating machine learning with computational modeling to optimize energy use in structures. She has contributed to peer-reviewed conference publications analyzing 2D cross-section simulations for office buildings and thermographic energy evaluations. Her work supports innovation in building digitalization , energy renovation , and profitable energy futures .

Touradj EbrahimiView profile

Professor

• Image and Video Compression
• Media Security
• Multimedia Signal Processing
• +5 more

Touradj Ebrahimi is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he heads the Multimedia Signal Processing Group (MMSPG) within the School of Engineering's Institute of Electrical Engineering. He holds a Ph.D. in Electrical Engineering from EPFL and serves as the Convenor of the JPEG standardization committee. His research spans AI-powered imaging, multimedia signal processing, and media security. Research Interests: Professor Ebrahimi's work focuses on next-generation image/video compression (including JPEG AI and DNA-based storage), quality of experience in immersive media, trustworthy media authentication (JPEG Trust), and explainable AI for biometric systems. His group pioneers methods for point cloud compression, deepfake detection, and privacy-preserving multimedia. Publication Trends: Recent articles emphasize AI-driven compression standards, quality assessment for emerging media (point clouds, HDR), and explainability in computer vision. Key themes include JPEG AI standardization, DNA storage for visual data, and robustness evaluation of deepfake detectors. Awards & Honors: IEEE Star Innovator Award in Multimedia IEEE and Swiss National ASE Awards ISO Certificates for MPEG-4/JPEG 2000 contributions Best Paper Award (IEEE Trans. Consumer Electronics) Fellow of IEEE and SPIE Leadership: He founded RayShaper SA, Genista SA, and Emitall SA. Represents Switzerland in ISO/IEC JTC1/SC29 and ITU, advising European Commission initiatives and venture capital firms on multimedia technologies. Facilities: Leads the MMSPG lab at EPFL, focusing on intelligent multimedia systems. The group collaborates globally on standardization (JPEG, MPEG) and EU projects.

Carsten MagnusView profile

Lecturer

• Theoretical Biology
• Mathematical Modeling
• Virology
• +3 more

Dr. Carsten Magnus is a Lecturer at the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich , Switzerland, with affiliations to the Computational Evolution group in Basel since 2015. His work bridges mathematics and theoretical biology to explore HIV dynamics, antibody neutralization, and viral evolution. Education includes a Mathematics degree from Münster, Germany, followed by a PhD in Theoretical Biology at ETH Zurich (2007–2010) under Roland Regoes. He conducted postdoctoral research at ETH Zurich, Oxford (with Angela McLean), and Zurich (with Alexandra Trkola), supported by Swiss National Science Foundation (SNF) and Deutsche Forschungsgemeinschaft (DFG) grants. His research interests focus on HIV-1 antibody interactions, phylodynamic modeling, and mathematical frameworks for viral entry and immune escape. He extends phylodynamic tools to study within-host HIV diversification and applies stoichiometric analysis to quantify neutralization thresholds. Article trends highlight computational approaches to viral evolution (HIV, Zika, influenza), antibody efficacy, and host adaptation. Key themes include phylodynamics , immunology , mathematical biology , and bioinformatics with subfields like HIV transmission , BEAST software , and antiviral kinetics . Scientific awards include the Flash poster award for innovative science communication using pop culture references (e.g., Minions characters) in virology education. He actively mentors and collaborates on master’s/PhD projects, emphasizing interdisciplinary research. Laboratory : Computational Evolution group at D-BSSE, Basel, Switzerland, where he develops models for HIV dynamics and phylodynamic inference tools.

• Natural Language Processing
• Text Analysis
• Speech Processing
• +4 more

Mark Cieliebak is a Professor for Speech and Text Processing at the Zurich University of Applied Sciences (ZHAW), School of Engineering, where he leads the Natural Language Processing (NLP) research group at the Centre for Artificial Intelligence. He has held this position since December 2018, following prior roles as a lecturer at ZHAW (2012-2018). His educational background includes a Dr. sc. techn. in Computer Science from ETH Zürich (1999-2003) and a Diplom in Computer Science from Universität Dortmund (1990-1999). His research focuses on Natural Language Processing , Text and Speech Analysis , and Machine Learning applications . Primary domains include dialogue systems evaluation, low-resource speech recognition (particularly Swiss German), automated text generation assessment, and NLP for social media analysis. He also explores educational applications through flipped classroom methodologies and machine learning operations. Cieliebak's publications (2020-2024) demonstrate strong emphasis on NLP evaluation frameworks, speech corpus development for dialects, and generative AI validation. Recurring themes include robustness testing, bias mitigation in automated metrics, and multilingual processing challenges. His work frequently involves large-scale dataset creation and ensemble learning techniques. Scientific Awards: SwissNLP Award 2023 Best Paper Award - Honorable Mention at EMNLP 2020 ZHAW Teaching Award 2015 He leads numerous research projects including: Unified Model for Text Generation Evaluation End-to-End Swiss German Speech Translation Holistic Analysis of Misinformation in Social Networks Automated News Processing (AutoNews) Chatbot Development for Language Learners He co-founded SpinningBytes AG (2015-present) and maintains extensive industry collaborations. As head of the NLP research group, he oversees doctoral candidates and master's students, though specific advisee names aren't listed.

Adrian SchwaningerView profile

Professor

• Ergonomics
• Human Factors
• Cognitive Psychology
• +3 more

Adrian Schwaninger is a Professor at the University of Applied Sciences Northwestern Switzerland (FHNW), School of Applied Psychology, where he serves as Head of the Institute for Humans in Complex Systems since May 2009. He has held academic teaching positions at the University of Zurich (1999-2015), ETH Zurich (1999-2008), and Zurich University of the Arts (2009-2012). His research focuses on human-machine systems, particularly in aviation security contexts. Professor Schwaninger's research interests span Ergonomics and Human Factors, Cognitive Psychology, Aviation Security, Human-Technology Interaction, and Quantitative Methods. His work primarily investigates how humans interact with complex technological systems, with a particular emphasis on airport security screening procedures. He has conducted extensive field studies with airport security screeners examining cognitive performance, visual inspection techniques, and the impact of various work conditions on security screening effectiveness. His recent publications demonstrate a strong focus on aviation security systems, particularly examining 3D vs 2D imaging for baggage screening, virtual reality training applications, the effects of night work and circadian rhythms on performance, and decision support systems in security contexts. These studies consistently apply rigorous quantitative methods to real-world security screening environments, producing findings with immediate practical applications for improving aviation security procedures worldwide. Professor Schwaninger is an active member of several professional organizations including the European Civil Aviation Conference (ECAC), Society for Industrial Engineering (GfA), Human Factors and Ergonomics Society, and multiple IEEE societies focused on aerospace, robotics, and systems engineering. His work bridges academic research with practical applications in security technology and human performance optimization.

• Computer Networking
• Network Security
• Software-Defined Networking
• +4 more

Laurent Vanbever is an Associate Professor at ETH Zürich's Department of Information Technology and Electrical Engineering and heads the Computer Engineering and Networks Lab. His research focuses on networking systems, with a strong emphasis on network security, routing protocols, software-defined networking (SDN), and distributed systems. He explores topics such as BGP convergence, energy-efficient router designs, and mitigating routing attacks on cryptocurrencies. His work bridges theoretical advancements with practical implementations, addressing challenges in network scalability, resilience, and sustainability. Key research areas include network verification, programmable packet processing (P4), and the security of decentralized systems like blockchain. Recent projects analyze transient forwarding anomalies, SDN-based network optimizations, and energy consumption in ISP networks. His contributions to network measurement and control plane innovations have significant implications for Internet architecture and operational practices. Vanbever actively publishes in top-tier conferences/journals and collaborates on open-source networking tools. His lab develops frameworks to enhance network performance and security, such as verifying link loads and mitigating BGP hijacks. Current efforts include exploring energy-efficient network designs and safeguarding cryptocurrency infrastructure against routing vulnerabilities.

Torben PetersView profile

Lecturer

• 3D Computer Vision
• Deep Learning
• Generative Models
• +2 more

Torben Peters is a Lecturer in the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich. His research focuses on 3D computer vision, deep learning, and generative models applied to geospatial analysis and photogrammetry. Research Focus: Peters develops computational tools for processing LiDAR point clouds, aerial imagery, and satellite data. His work enables automated environmental monitoring (e.g., forest inventories and avalanche mapping) and urban modeling through advanced segmentation and 3D reconstruction techniques. Generative models like TetraDiffusion expand capabilities in geometric deep learning. Publication Trends: Recent articles emphasize scalable geospatial AI, including war damage assessment in Ukraine, global biomass datasets, and self-supervised shape completion. Methodological innovations center on reducing annotation dependencies and improving geometric accuracy. Teaching: Leads courses on image-based mapping and geodetic data processing at ETH Zürich.

Jan Dirk WegnerView profile

Professor

• Geospatial Computer Vision
• Large-Scale Machine Learning
• Remote Sensing
• +9 more

Prof. Jan Dirk Wegner holds a professorship at ETH Zürich within the Department of Civil, Environmental and Geomatic Engineering (Baug), specifically in the Institute of Geodesy and Photogrammetry. His research focuses on integrating advanced technologies such as Geospatial Computer Vision, Large-Scale Machine Learning applied to Ecology, and Deep Convolutional Neural Networks with traditional fields like Remote Sensing and Photogrammetry. His work bridges geomatics, environmental science, and computational methods to address complex spatial data challenges. Prof. Wegner’s affiliations include ETH Zürich’s I. f. Geodäsie u. Photogrammetrie (HIL D 44.2, Stefano-Franscini-Platz 5, Zürich). While no specific grants, awards, or advised students are listed in the provided texts, his role as staff in the 'Lehre Bau, Umwelt und Geomatik' (Teaching in Construction, Environment, and Geomatics) suggests active involvement in academic instruction and curriculum development. His research emphasizes interdisciplinary applications of geospatial technologies, particularly in ecological monitoring and large-scale environmental data analysis. Key technical areas include leveraging machine learning for ecological remote sensing, optimizing photogrammetric workflows with deep learning, and advancing geospatial data interpretation through neural networks. His work contributes to both foundational and applied aspects of geomatics, with potential implications for environmental policy, urban planning, and sustainable resource management.

• Machine Learning
• Statistical Pattern Recognition
• Deep Learning
• +3 more

André Anjos is a Lecturer at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) and the Institute of Microengineering (IEM). He is part of the LIDIAP (IDIAP Laboratory), focusing on research and teaching in statistical pattern recognition and machine learning. His course, 'Fundamentals in Statistical Pattern Recognition,' equips PhD students with core methodologies in machine learning and deep learning. He supervises PhD student Özbulak Gökhan. Anjos holds an administrative role within EPFL's VPA-AVP-DLE division, contributing to academic governance. His work bridges theoretical foundations and practical applications in signal processing and biometrics.

Roland SiegwartView profile

Professor

• Robotics
• Autonomous Systems
• Control Systems
• +4 more

Prof. Roland Siegwart is a Full Professor of Autonomous Systems at ETH Zurich's Department of Mechanical and Process Engineering since 2006. He leads the Wyss Zurich Translational Center and previously served as Vice President for Research and Corporate Relations (2010–2014). His academic background includes a Diploma (1983) and PhD (1989) in Mechanical Engineering from ETH Zurich, followed by a decade as a professor at EPFL Lausanne (1996–2006) and visiting roles at Stanford University and NASA Ames. His research focuses on robot systems operating in complex environments, emphasizing adaptive autonomy for applications like aerial robotics, driver assistance, and service robots. He has coordinated EU projects, co-founded multiple spin-offs, and holds IEEE Fellow status. Awards include the IEEE RAS Inaba Technical Award and leadership roles in IFRR and robotics journals. Key contributions span reactive navigation, multi-modal localization (e.g., CompSLAM), and UAV path optimization. His work bridges theoretical robotics with real-world applications like corrosion inspection drones and Mars exploration path planning. Current projects emphasize open-source space systems (ATMOS) and neural radiance fields for perception.

Jörg GoldhahnView profile

Professor

• Translational Medicine
• Medical Technology
• Biomechanics
• +3 more

Prof. Jörg Goldhahn is a Professor at ETH Zurich's Department of Health Sciences and Technology, serving as Translational Science Tutor for the MSc in Human Movement Science and Sport Medical Technology. His research focuses on accelerating medical translation pathways from idea to clinical application, with expertise in biomarker development, wearable devices, and musculoskeletal health technologies. He advises master's students on interdisciplinary coursework including biomechanics, medical implants, and clinical research methods. Goldhahn's research group explores digital health innovations such as sweat-based diagnostics and therapeutic drug monitoring. He contributes to interprofessional education initiatives, emphasizing collaboration between medical and nursing students. His work bridges clinical and engineering disciplines, addressing challenges in orthopedic treatments and aging-related health technologies. Recent projects include developing wearable systems for continuous health monitoring and advancing cartilage regeneration therapies. Goldhahn actively engages in curriculum development at ETH Zurich, promoting inclusive education and ethical considerations in medical technology.

Yang LinView profile

Researcher

• Machine Learning
• Intelligent Image Sensors
• Computer Vision
• +5 more

Yang Lin is a doctoral assistant at the AQUA Lab within the School of Engineering at École Polytechnique Fédérale de Lausanne (EPFL). He works on integrating single-photon avalanche diodes (SPADs) with artificial and spiking neural networks for biological and medical imaging applications, particularly fluorescence lifetime imaging. Ph.D. in Computational and Quantitative Biology (expected 2025), École Polytechnique Fédérale de Lausanne B.Eng. in Automation (2020), Shanghai Jiao Tong University His research focuses on developing intelligent image sensors by combining SPAD technology with neural networks, including ASIC SPAD sensors, FPGA-based processing units, and optical setups for biomedical applications. He is exploring spiking neural networks (SNNs) for energy-efficient, real-time imaging with SPADs. Yang's recent publications highlight advancements in quantum ghost imaging, SPAD sensor integration with neural networks, and fluorescence lifetime imaging. He has presented at conferences like WACV 2024 and received recognition for his work at BMPN 2022. Best Talk of a Young Researcher, BMPN 2022 He designs hardware-software co-systems for biomedical imaging and is open to research or engineering roles post-2025.

Markus StroblView profile

Professor

• Neutron Imaging
• Materials Science
• Additive Manufacturing
• +5 more

Prof. Markus Strobl is a Professor at the Paul Scherrer Institute (PSI) within the Laboratory for Neutron Scattering and Imaging , part of the Center for Neutron and Muon Sciences . His research focuses on advanced neutron-based characterization techniques, including neutron imaging, diffraction, and tomography, applied to materials science challenges in additive manufacturing, battery technology, and corrosion analysis. He leads efforts in developing novel experimental setups for in-situ studies of material behavior under extreme conditions. Key research areas include: Neutron dark-field imaging for nanostructure analysis Crystallographic texture manipulation in metals via additive manufacturing Operando studies of electrochemical systems (batteries, fuel cells) Characterization of microstructural evolution in laser powder bed fusion materials Recent work highlights the application of neutron techniques to study phase evolution in graphite electrodes, hydrogen transport in Ni-MH batteries, and corrosion mechanisms in concrete-reinforced steel. His group has pioneered advancements in neutron imaging instrumentation, including the FALCON diffractometer add-on and event-mode data acquisition systems. Scientific recognition includes the Energy Technology Division Graduate Student Award (2024). His lab actively collaborates on international projects like the HighNESS neutron source development at the European Spallation Source (ESS).

Robert RienerView profile

Professor

• Rehabilitation Robotics
• Biomedical Engineering
• Human Biomechanics
• +5 more

Robert Riener is a Full Professor at the Department of Health Sciences and Technology (D-HEST), ETH Zurich, and holds a professorship in medicine at the Balgrist University Hospital (University of Zurich). His academic journey includes a Dipl.-Ing. and Dr. degree from TU München (1993, 1997), followed by postdoctoral work at Politecnico di Milano and habilitation in Biomechatronics. He has led D-HEST (2016–2018) and pioneered robots for rehabilitation and sports. His research focuses on human biomechanics, virtual reality, sleep robotics, and rehabilitation robotics, with over 500 publications and patents. Riener initiated the Cybathlon, a championship for athletes using assistive technology, recognized with multiple awards including the European Excellence Award and IEEE RAS/EMBS Key Innovator Award. His education includes studies at TU München and the University of Maryland, followed by a career at ETH Zurich since 2003. Riener’s work bridges engineering and medicine, addressing neuroprosthetics, robotic rehabilitation systems (e.g., ARMin), and sleep-related robotics. Awards include the Swiss Technology Award, humanTech Innovation Prize, and AAAS Leshner Fellowship. His current projects involve robotic beds for sleep disorders, wearable exosuits, and gait assistance technologies. Key research trends in his articles include advancements in robotic control systems, wearable exoskeletons, and data-driven approaches to rehabilitation. His work emphasizes clinical validation and adaptive human-robot interfaces. Riener’s contributions span from fundamental biomechanical studies to large-scale implementations like Cybathlon, reflecting interdisciplinary innovation. Notable awards include the euRobotics Technology Transfer Awards (2011, 2012, 2021), IEEE Best Paper Awards, and an honorary doctorate from the University of Basel. His grants and collaborations involve EU-funded projects and industry partnerships. Riener heads labs focused on rehabilitation robotics, biomechanics, and sleep technology, fostering international collaborations and translating research into clinical applications.