Find Academic Supervisors

• Planetary Seismology
• Geophysics
• Mars Geology
• +3 more

Nikolaj Louis Dahmen is a Lecturer at the Institute of Geophysics, ETH Zurich, within the School of Earth and Planetary Sciences. His research focuses on Martian seismology, leveraging data from NASA’s InSight mission to analyze seismic activity and crustal structure. Dahmen specializes in applying machine learning techniques for seismic denoising and event detection, significantly expanding the catalog of marsquakes and improving their analysis. He earned his Doctoral Thesis in 2024, titled 'The Seismicity of Mars Recorded by InSight,' supervised by Prof. Domenico Giardini. His work addresses challenges in low-signal-to-noise ratio environments and contributes to understanding Martian tectonic processes. Education: Doctoral Thesis (2024) at ETH Zurich Key Research Areas: Planetary seismology, machine learning applications, seismic data processing, Martian crustal structure Dahmen’s research has led to advancements in detecting and cataloging marsquakes, including the discovery of the largest recorded marsquake (S1222a). His methods enhance seismic signal analysis by mitigating environmental noise, enabling precise event localization and waveform interpretation. Collaborations include the Marsquake Service (MQS) and projects like MarsQuakeNet, which automate event detection using deep learning. His contributions extend to crustal studies through surface wave analysis and meteorite impact investigations, providing insights into Mars’ subsurface composition. Dahmen’s work bridges planetary science and computational methods, advancing our understanding of Mars’ geophysical dynamics.

Mathias KneubühlerView profile

Senior Lecturer

• Remote Sensing
• Imaging Spectroscopy
• Earth Observation
• +7 more

Mathias Kneubühler is a Senior Lecturer and Scientific Section Head of Remote Sensing Spectroscopy at the Department of Geography, Faculty of Science, University of Zurich. He leads the Spectroscopy Lab and has been a key figure in advancing imaging spectroscopy and Earth observation research. He is actively involved in international remote sensing initiatives, including serving as the Swiss ESA-DOSTAG Delegate and Co-Chair of the EARSeL Special Interest Group on Imaging Spectroscopy. PhD in Remote Sensing, University of Zurich (1997–2002) MSc in Geography, University of Zurich (1992–1996) His research focuses on imaging spectroscopy , spectro-directional measurements , and ecosystem monitoring , with applications in plant phenology , biodiversity assessment , and land surface dynamics . He investigates how multi-angular and hyperspectral data can improve the understanding of vegetation structure, function, and environmental responses. His work integrates field spectroscopy, airborne and satellite remote sensing, and advanced data processing techniques. The recent publications highlight a strong trend in imaging spectroscopy for ecological applications, including plant trait mapping , camouflage detection , tree species identification , and phenology modeling . These studies often involve UAV and satellite data fusion, BRDF correction, and machine learning, demonstrating interdisciplinary innovation in remote sensing science. Co-Chair, EARSeL Special Interest Group on Imaging Spectroscopy (2016–present) President, Swiss Commission for Remote Sensing (2015–2020) Swiss ESA-DOSTAG Delegate (2004–2024) He has supervised several PhD and Master’s students, including Marius Vögtli, Christian Rossi, and Mojdeh Miraki, contributing to the next generation of remote sensing scientists. His leadership in organizing scientific workshops and campaigns underscores his role in fostering collaborative research. He is associated with the Spectroscopy Lab at the University of Zurich, which conducts cutting-edge research in spectro-directional measurements and environmental monitoring.

Esther HänggiView profile

Professor

• Cyber Security
• Quantum Cryptography
• Information Security
• +3 more

Esther Hänggi is a Professor and Co-Head of the Applied Cyber Security Research Lab at Lucerne University of Applied Sciences and Arts (HSLU), within the Lucerne School of Computer Science and Information Technology. She holds a Dr. sc. ETH Zurich in quantum information and cryptography and a MSc in Physics from EPF Lausanne. Her research focuses on cyber security, quantum cryptography, and quantum computing, with emphasis on practical applications like quantum-safe cryptography and post-quantum algorithms. She has led projects such as the Quantum-safe Hardware Security Module and contributed to initiatives like the IFZ FinTech. Her work bridges theoretical advancements and real-world implementations, including privacy amplification libraries and quantum key distribution systems. Notable awards include the ETH Medal for her doctoral thesis. She actively collaborates with institutions like the Swiss Quantum Initiative and the European Cyber Security Organisation, promoting quantum resilience in security systems.

Suryanarayana SankagiriView profile

Researcher

• Discrete Choice Models
• Recommendation Systems
• Blockchain Security
• +4 more

Suryanarayana Sankagiri is a postdoctoral researcher at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, affiliated with the Information and Network Dynamics (INDY1) group under Professor Matthias Grossglauser. Previously, he earned his Ph.D. in Electrical & Computer Engineering (2018-2022) from the University of Illinois at Urbana-Champaign , where he was supervised by Bruce Hajek and participated in the Coordinated Science Lab . He also holds an M.S. in Electrical & Computer Engineering from the University of Illinois (2016-2018) and a B.Tech. in Electrical Engineering from the Indian Institute of Technology Bombay (2012-2016). Education : Ph.D., Electrical & Computer Engineering, University of Illinois (2018-2022) M.S., Electrical & Computer Engineering, University of Illinois (2016-2018) B.Tech., Electrical Engineering, IIT Bombay (2012-2016) Suryanarayana's research focuses on discrete choice models and their application to recommendation systems , with a particular emphasis on learning from choice data and developing novel models for human decision-making. His broader interests include blockchain security under adverse network conditions, network dynamics , probabilistic modeling , and algorithm design . Recent work explores nonconvex matrix factorization and contextual dueling bandits for recommendation systems. His publications span theoretical and applied domains, including high-impact venues like ICML , Stochastic Systems , and IEEE Transactions on Networking . Themes include blockchain efficiency , hidden community detection in preferential attachment graphs, and temporal analysis of Indian classical music. Current projects involve refining recommendation systems through sparse comparison data and designing protocols for resilient blockchain networks. Scientific Awards : zkCapital Paper of the Week (2021) Rambus Fellowship (2021) Mavis Future Faculty Fellowship (2019) List of Teachers Ranked as Excellent (2019) Nomination for IIT Bombay Undergraduate Colloquium (2016) Best Poster Award, IIT Bombay Undergraduate Research Symposium (2013) Suryanarayana has advised no students listed in the provided materials. His work has been supported by fellowships such as the Mavis Future Faculty Fellowship and Rambus Fellowship . He contributes to the INDY1 group at EPFL, which investigates information and network dynamics through interdisciplinary approaches combining probability , network theory , and algorithmic design .

Jean-Yves Le BoudecView profile

Professor

• Network Calculus
• Time-Sensitive Networking
• Deterministic Networking
• +7 more

Jean-Yves Le Boudec is a Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences and the Institute of Electrical Engineering. He has been a key figure in advancing the theory and application of network calculus and deterministic networking, contributing significantly to standards such as IEEE Time-Sensitive Networking (TSN) and IETF DetNet. His research focuses on network calculus , time-sensitive and deterministic networking , traffic regulation , worst-case delay analysis , and cyber-physical systems , with cross-cutting applications in smart grids , real-time communication , and network security . He has co-authored foundational texts on network calculus and developed theoretical frameworks for traffic regulators, service curves, and delay bounds in complex networked systems. The recent publications highlight a strong trend in analyzing and improving performance guarantees in deterministic networks, including scheduling mechanisms like Deficit Round-Robin and Cyclic Queuing and Forwarding, traffic shaping via interleaved regulators, and security against time-synchronization attacks in power systems. The work spans theoretical modeling using stochastic and min-plus/max-plus algebra, practical algorithm design, and application to critical infrastructure. IEEE Fellow Le Boudec has advised numerous researchers and PhD students, including Ehsan Mohammadpour, Ludovic Thomas, and Seyed Mohammadhossein Tabatabaee. His collaborative projects often involve grants related to European and Swiss research initiatives in networking and smart grid technologies. He leads a research group focused on networked systems at EPFL, contributing to both theoretical advances and real-world implementations in industrial and energy-critical networks. His lab work centers on modeling and verification of time-sensitive network behaviors, integrating formal methods with practical experimentation. The team investigates regulators, shapers, and synchronization mechanisms, aiming to ensure robustness, predictability, and security in next-generation communication infrastructures. Future work continues to explore the interplay between communication, control, and energy systems in highly reliable environments.

• Mathematical Physics
• Differential Geometry
• Topology
• +4 more

Prof. Alberto S. Cattaneo is a faculty member at the University of Zurich, affiliated with the Department of Mathematics. He holds the rank of Professor and has been actively involved in teaching and research since at least 1998. His research interests span mathematical physics, differential geometry, topology, and interdisciplinary areas like computational biology, genomics, and digital forensics. He has developed courses on topics such as field theory, quantum mechanics, and differential manifolds, reflecting his expertise in theoretical and applied mathematics. Prof. Cattaneo has contributed to numerous publications, including works on distributed genomic analysis, sensor pattern noise (PNU) in forensics, and algorithm optimization for big data frameworks like Hadoop and Spark. His work bridges pure mathematics with applications in bioinformatics and cybersecurity. Though no awards are explicitly mentioned, his extensive publication record and teaching roles highlight his academic standing. He maintains an active presence through courses and research collaborations, with no indication of part-time roles or retirement.

Feiran ZhaoView profile

Researcher

• Data-Driven Control
• Adaptive Control
• Reinforcement Learning
• +2 more

Feiran Zhao is a Researcher at the Institute of Automatic Control, part of the Department of Mechanical and Process Engineering at ETH Zürich. He holds a B.S. in Control Science and Engineering from Harbin Institute of Technology (2018) and a Ph.D. from Tsinghua University (2024). His research focuses on data-driven control, adaptive control, reinforcement learning, and their applications in engineering systems. Zhao is currently a postdoc under Prof. Florian Dorfler at ETH's Automatic Control Lab. Research interests span topics like policy optimization for LQR systems, quantized feedback control, and model predictive control acceleration. His work bridges machine learning and classical control theory, with applications in robotics, power systems, and aerospace engineering. His publications (2019–2025) explore theoretical foundations of policy gradient methods, convergence analysis, and practical implementations in autonomous systems. Though no awards are explicitly listed, his active research in high-impact areas suggests potential recognition. As part of the Automatic Control Lab, Zhao collaborates on projects involving data-enabled control strategies and real-world system applications. No student advisees are currently listed.

Renato PajarolaView profile

Professor

• Computer Graphics
• Scientific Visualization
• 3D Modeling
• +5 more

Prof. Dr. Renato Pajarola is the Head of the Visualization and MultiMedia Lab at the Department of Informatics, University of Zurich. His research focuses on computer graphics, scientific visualization, and geometric processing, with applications in 3D scanning, point cloud analysis, and real-time rendering. He leads a team developing advanced visualization techniques for high-dimensional data, parallel rendering frameworks, and interactive systems for complex datasets. Key research areas include: 3D reconstruction of indoor environments Tensor approximation for volume visualization Interactive ray tracing and point cloud processing Parallel rendering frameworks (e.g., Equalizer) Scientific computing and sensitivity analysis His recent publications emphasize: High-dimensional data exploration using tensor methods Efficient rendering techniques for large-scale point clouds Integration of citizen-reported weather data for environmental analysis Prof. Pajarola’s lab collaborates on projects like VIAN (visual annotation tool for film analysis) and Terrender (web-based terrain visualization). His Erdős number is 3, reflecting interdisciplinary research connections in mathematics and computer science.

• Speech Processing
• Automatic Speech Recognition
• Auditory Modeling
• +3 more

Philip Neil Garner is a Researcher at the Idiap Research Institute (LIDIAP), affiliated with École Polytechnique Fédérale de Lausanne (EPFL). His current position is listed as "EPFL member Current" with email philip.garner@epfl.ch. He maintains an active research profile with publications spanning from 2013 to 2025. Garner's research focuses on the intersection of physiological auditory modeling and machine learning for speech processing. His work bridges cochlear physiology with automatic speech recognition systems, investigating how biological principles of hearing can inform and improve computational models. Key areas include modeling the cochlea as an active amplifier using Hopf oscillators, exploring neural oscillations in speech perception via spiking neural networks, and developing interpretable affective speech synthesis systems. His research demonstrates consistent interest in creating biologically plausible models that maintain compatibility with modern deep learning frameworks. Analysis of his recent publications reveals a clear trajectory toward integrating physiological auditory models with state-of-the-art speech recognition systems. His work increasingly focuses on creating hybrid models that maintain physiological plausibility while leveraging pre-trained acoustic models. The research shows particular attention to modular approaches that allow different components (cochlear models, neural networks) to interact meaningfully, with emphasis on understanding how end-to-end learning affects physiological interpretations of speech processing. Garner has supervised multiple doctoral students including Louise Coppieters De Gibson, Bastian Schnell, and Sibo Tong, whose theses address cochlear modeling, affective speech synthesis, and multilingual speech recognition respectively. His research has received funding from the Swiss National Science Foundation as indicated in two publications. While specific grants aren't detailed, his work demonstrates consistent collaboration with Hervé Bourlard and Alexandre Bittar across multiple projects. As a core researcher at Idiap Research Institute, Garner works within a multidisciplinary team focused on speech processing and artificial intelligence. His publications indicate collaboration across units including LIDIAP, EDEE, STI, IEL, and LCAV at EPFL, suggesting integration within both the Idiap institute and broader EPFL research ecosystem. His work connects computational neuroscience with practical speech technology applications, positioning him at the intersection of theoretical auditory modeling and applied speech processing.

Torsten BraunView profile

Professor

• Machine Learning
• Networking and Telecommunications
• Edge Computing
• +3 more

Prof. Torsten Braun is a Professor and Head of the Communication and Distributed Systems (CDS) research group at the Institute of Computer Science, University of Bern. His research focuses on advanced networking technologies, edge computing, and machine learning applications in telecommunications. He leads projects addressing challenges in 5G/6G networks, federated learning optimization, and intelligent systems for smart cities. His work integrates theoretical frameworks with practical implementations, emphasizing distributed systems, service-oriented architectures, and IoT security. Key research areas include edge caching strategies for VR/AR applications, trajectory prediction using reinforcement learning, and resilient network design against jamming attacks. Braun has contributed to innovations in vehicular networks (V2X), RAN intelligence, and decentralized machine learning frameworks. He holds leadership roles in developing adaptive resource management systems for edge-cloud environments and has pioneered solutions for energy-efficient federated learning in heterogeneous IoT ecosystems. Publications span topics like spatial-temporal point cloud sensing, mobility-aware service orchestration, and secure positioning systems. His team explores cross-disciplinary applications such as LoRaWAN-based urban heat monitoring and blockchain-inspired public key infrastructures for IoT (Veritaa-IoT). Braun actively engages in standardization and industry collaborations to advance next-generation network architectures.

• Multiresolution Methods
• Numerical Analysis
• Computational Mathematics
• +4 more

Michael Multerer is an Associate Professor at the Faculty of Informatics, Università della Svizzera italiana (USI). His research focuses on multiresolution methods, scattered data analysis, and numerical analysis with applications in computational mathematics and engineering. He leads projects such as the SNSF Starting Grant on multiresolution methods for unstructured data, emphasizing nonlinear approximation and kernel-based techniques. Research Interests: Development of fully discrete multiresolution methods for unstructured data Wavelet theory and kernel matrix algebra Uncertainty quantification in partial differential equations Scattered data compression and approximation Key Software Contributions: FMCA: Fast multiresolution covariance analysis for scattered data Bembel: Boundary element library for solving Laplace and Helmholtz equations SPQR: Anisotropic sparse grid quadrature in MATLAB Funding: Holder of the SNSF Starting Grant (2025) for advancing multiresolution techniques in unstructured data processing. Labs/Teams: Active in the research group at USI’s Faculty of Informatics, collaborating with institutions like TU Darmstadt and University of Basel on numerical methods and engineering applications.

Laura ErmertView profile

Researcher

• Seismic Interferometry
• Ambient Noise Monitoring
• Computational Seismology
• +3 more

Dr. Laura Ermert is an Established Researcher at the Swiss Seismological Service (SED) of ETH Zurich. Her work focuses on computational seismology, ambient noise monitoring, and seismic interferometry. She holds a PhD from ETH Zurich (2013–2018) under Prof. Andreas Fichtner, followed by postdoctoral positions at the University of Washington, Harvard University, and the University of Oxford. Her research explores shallow structure monitoring, basin resonances, and the influence of ocean microseism sources on ambient noise cross-correlation amplitudes. She has contributed to projects like the DEEP initiative for geothermal reservoir modeling and collaborated on Mexico City basin subsidence studies funded by the Packard Fellowship. Dr. Ermert co-developed Python tools like noisi for ambient noise analysis and pioneered methods for ambient seismic source inversion. Her studies include modal analysis of Alpine valley resonances and global-scale ambient noise inversion. She actively promotes gender equity in seismology through collaborative initiatives.

Anne-Claude GavinView profile

Professor

• Lipid Metabolism
• APOE Lipidation
• Alzheimer's Disease Mechanisms
• +4 more

Anne-Claude Gavin is a Professor at the University of Geneva's Faculty of Medicine within the Department of Cell Physiology and Metabolism. Her research group, based at CMU office C05.1535.a, focuses on lipid metabolism with particular emphasis on APOE lipidation mechanisms and their implications in Alzheimer's disease. The laboratory actively recruits PhD candidates for high-level collaborative projects, with a recent opening targeting autumn 2025 start dates for research on APOE polymorphism and metabolic stressors. Her research interests center on lipid-protein interactions, particularly APOE homeostasis across isoforms and cell states, ceramide transport mechanisms, and the role of lipid dysregulation in neurodegenerative diseases. Recent work integrates structural biology, cellular imaging, and systems approaches to dissect molecular mechanisms of lipid transfer proteins like CERT and STARD4. Her group has made significant contributions to understanding how APOE variants differentially modulate cellular cholesterol metabolism and inflammatory responses in astrocytes. Analysis of recent publications (2023-2025) reveals strong thematic continuity in lipid-centric research, with increasing focus on Alzheimer's disease mechanisms through APOE studies, structural characterization of lipid transfer proteins, and cellular aging processes in hematopoietic systems. Key methodologies include molecular dynamics simulations, fluorescent biosensor development, and system-wide lipid transfer protein mapping. While no specific awards are listed in the provided materials, her research has garnered media attention including coverage in RTS's CQFD program (March 2022) discussing protein contributions to Alzheimer's disease. Her laboratory maintains active recruitment for doctoral positions, indicating ongoing grant funding for projects like the collaborative study on APOE lipidation mechanisms. Active recruitment for PhD positions in lipid metabolism Media features on Alzheimer's research Collaborative projects with clinical implications The laboratory operates within the Lipid Metabolism research group at the University of Geneva's Centre Médical Universitaire (CMU), utilizing advanced techniques including molecular dynamics, chemoproteomics, and genetically encoded fluorescent probes to investigate lipid dynamics in cellular systems. Current work emphasizes translational connections between fundamental lipid biochemistry and neurodegenerative disease pathways.

Shuting HanView profile

Research Fellow

• Neuroscience
• Cortical Dynamics
• Sensory Processing
• +3 more

Dr. Shuting Han leads a Junior Research Group at the University of Zurich under the Helmchen Lab, funded by the SNSF Ambizione Fellowship since 2024. She holds a Research Fellow position focusing on cortical dynamics underlying sensory processing and memory. Her research examines how distributed cortical areas interact during sensory processing and memory formation, utilizing multi-area two-photon calcium imaging, virtual reality behavior paradigms, electrophysiology, and advanced data analysis techniques. Key projects include investigating sensory representation in cortical areas, predictive processing in neural circuits, cortico-cortical interactions, memory consolidation across the neocortex, and developing high-throughput imaging methodologies. Her recent publications demonstrate expertise in cross-modal predictions, cortical microstates during consciousness alterations, and neural ensemble dynamics. She directs research on top-down predictive signals in neocortex and develops tools for volumetric neural imaging. SNSF Ambizione Fellowship Dr. Han mentors PhD students Maï Ly Leclair and Saidong Ma in the Helmchen Lab. Her group develops custom multi-area two-photon microscopes and applies machine learning for neural data analysis, bridging experimental neuroscience with computational approaches to decode cortical information processing.

• Seismology
• Geophysics
• Seismic Tomography
• +5 more

Prof. Dr. Andreas Fichtner is a Full Professor of Seismology and Wave Physics at ETH Zurich's Department of Earth and Planetary Sciences. He leads research in seismic tomography, fiber-optic sensing, and high-performance computing, deploying innovative techniques for imaging Earth's interior. His work includes developing distributed fiber-optic sensing for seismic monitoring in urban areas, volcanoes, and glaciers. Beyond seismology, he explores applications in medical ultrasound imaging and metamaterial design. Research interests span seismic wave inversion, uncertainty quantification, and fiber-optic technology. Notable achievements include co-founding Mondaic, a spin-off providing full-waveform modeling solutions. Awards include the 2011 Keiiti Aki Award (AGU), 2015 Early Career Scientist Award (IUGG), and 2018 Hoffmann Prize. He currently serves on the Board of Directors of the Seismological Society of America. Key contributions include pioneering fiber-optic seismology in ice streams and volcanoes, advancing multi-scale inversion methods, and integrating seismic data for continental-scale tomography. His research bridges geophysics with engineering, medical imaging, and computational science.