Find Academic Supervisors

Sossan FabrizioView profile

Associate Professor

• Power Systems
• Energy Storage Systems
• Renewable Energy Integration
• +4 more

Prof. Sossan Fabrizio is an Associate Professor of Power Systems at HES-SO Valais-Wallis, focusing on energy storage, renewable integration, and smart grid technologies. He holds a PhD from DTU (2014) and has held roles at EPFL, ETHZ, and Mines ParisTech. His research emphasizes optimizing distribution grids, hydropower flexibility, and EV charging infrastructure. He leads projects like STOR-HY (Hybrid Hydropower Control) and STORE (Swiss Renewable Energy Storage). Education: Bachelor's/Master's in Computer Engineering, University of Genova (2010) PhD in Electrical Engineering, Technical University of Denmark (2014) Research Interests: Planning/scheduling/control of distributed energy resources, energy storage systems, and grid dispatchability. Areas include hydropower penstock stress reduction, EV charging infrastructure optimization, and model predictive control. Articles Overview: Over 20 peer-reviewed publications since 2013, focusing on grid integration of storage, renewable curtailment, and frequency control. Recent work includes optimal EV charging station planning (2023) and stress-informed MPC for hydropower plants (2022). Advising/Grants: Supervised PhD students like Stefano Cassano (defended 2023) and Biswarup Mukherjee. Secured grants including Horizon 2020 STOR-HY (2024) and Swiss Innovation Agency projects. Leads the ResiNet initiative on grid resiliency. Labs/Teams: Co-founded ModBESS (2020) for microgrid monitoring systems. Active in experimental facilities like the CIGRE MV network and Waterloo Institute’s hydropower lab.

• 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.

Yuping LiView profile

Assistant Professor

• Molecular Microbiology
• Bacteriophage Biology
• Jumbophage Genetics
• +12 more

Yuping Li is a Tenure-track Assistant Professor at the Biozentrum, University of Basel, where she leads a research group focused on the genetics and evolution of bacteria-jumbophage interactions. She was appointed in 2024 and received an SNSF Starting Grant the same year. Her research explores the unique biology of jumbophages—phages with large genomes and eukaryote-like properties—and their co-evolution with bacterial hosts, particularly the Pseudomonas phage phiKZ and the bacterial 'jumbophage killer' (Juk) immune systems. Nationality: Chinese Current Position: Tenure-track Assistant Professor, University of Basel, Biozentrum (since 2024) Previous Position: Postdoctoral Researcher, University of California, San Francisco (2019–2024) Visiting Scientist: EMBL, Heidelberg (2022–2023) Her research interests center on molecular microbiology, bacteriophage biology, bacterial immunity, and evolutionary genetics . She investigates how jumbophages form protective 'nuclei' inside bacterial cells to evade host defenses and how bacteria have evolved counter-mechanisms like the Juk system. This work combines genetics, microscopy, biochemistry, and structural biology to understand infection dynamics and evolutionary arms races. The ultimate goal is to harness jumbophages in fighting antibiotic-resistant bacteria. The recent publications show a strong trend in phage-host interactions, anti-CRISPR mechanisms, microbial evolution, and systems-level analysis of adaptation . Her work bridges fundamental virology with applied antimicrobial strategies, often using high-throughput sequencing, proteomics, and mathematical modeling. Articles span top journals like Cell , Nature Communications , and PLoS Biology , reflecting interdisciplinary impact. Scientific Awards: SNSF Starting Grant (2024) Postdoctoral Independent Research Grant, Program for Breakthrough Biomedical Research, UCSF (2021–2022) CEHG Predoctoral Fellowship, Stanford University (2018–2019) Genentech Foundation Predoctoral Fellowship (2016) Outstanding Student Scholarship (2007–2011) Yuping Li advises PhD students and postdoctoral fellows, including Elena Kaube, Dr. Marina Mahler, and Dr. Sam van Beljouw. Her group is supported by competitive grants such as the SNSF Starting Grant. She collaborates with leading scientists like Dr. Joseph Bondy-Denomy (UCSF) and Dr. Nassos Typas (EMBL). Her lab employs cutting-edge techniques in genetics, proteomics, and structural biology to dissect phage infection and bacterial immunity mechanisms. Her research group is part of the Biozentrum at the University of Basel, a leading institution in life sciences, and she is affiliated with the NCCR AntiResist initiative, focusing on antimicrobial resistance solutions.

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 .

• Deep Learning
• Distributed Machine Learning
• Federated Learning
• +7 more

Tao Lin is a Tenure-Track Assistant Professor and Principal Investigator of LINs Lab at Westlake University, School of Engineering. He leads cutting-edge research in deep learning optimization, generalization, and robustness, particularly in distributed and federated settings. Prior to this, he was a Ph.D. student at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, under the supervision of Prof. Martin Jaggi and Prof. Babak Falsafi. Doctor of Science, School of Computer and Communication Sciences, EPFL, Switzerland (2017–2022) Master of Science, School of Computer and Communication Sciences, EPFL, Switzerland (2014–2017) Bachelor of Engineering (with honors), College of Electrical Engineering, Zhejiang University, China (2010–2014) His research focuses on the intersection of optimization and generalization in deep learning, leveraging theoretical and empirical insights into loss landscapes and training dynamics to design efficient and robust learning and inference methods. This includes work on decentralized and federated learning under noisy, heterogeneous, and hardware-constrained environments. His work spans algorithmic innovation, theoretical analysis, and practical system integration. The recent publications from his lab demonstrate a strong trend in advancing federated learning, efficient inference for large language models, multimodal foundation models in pathology, and robust training under distribution shifts. Key themes include communication efficiency, model personalization, gradient tracking, and hardware-aware learning. His group has published at top venues including NeurIPS, ICML, ICLR, CVPR, and ECCV, with several papers receiving oral or spotlight presentations. ECCV Best Paper Candidate, 2024 Top 2% Scientists Worldwide 2024 (Stanford University) Doctoral Program Thesis Distinction Award, EPFL, 2022 Outstanding Performance Bonus, EPFL, 2021–2022 Top Reviewer: NeurIPS, ICML, AISTATS He advises multiple Ph.D. and master’s students, including Yongxin Guo, Futing Wang, Peng Sun, and Yuxuan Sun, whose work has been accepted at premier conferences. He has secured competitive grants as PI and participant, including the National Natural Science Foundation of China for Excellent Young Scientists Fund (Overseas) and the Science and Technology Innovation 2030 – Major Project. He also contributes to the community through service as an area chair (NeurIPS, ICML), reviewer for top journals and conferences, and organizer of workshops and academic events. His open-source contributions, such as Post-local SGD, have been integrated into PyTorch. Tao Lin teaches graduate courses such as Research Methodology of Computer Science and Technology and Deep Learning at Westlake University. He is actively involved in academic governance, serving on committees for student seminars, academic exchange, doctoral studies, and teaching leadership. The LINs Lab runs a regular research seminar on Deep Learning and Optimization, fostering a collaborative and dynamic research environment.

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.

Jérôme ChenalView profile

Researcher

• Urban and Regional Planning
• Environmental Science
• Public Health
• +3 more

Jérôme Chenal is a Senior Scientist and Director of the Excellence in Africa Center at the École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Institute of Environmental Engineering . He is also an Affiliate Professor at UM6P (Morocco). His work intersects urban and regional planning , environmental science , public health , and geospatial analysis , with a focus on informal settlements and sustainability in the Global South . Research Interests : Urban resilience, smart cities in Africa, ecosystem services, WASH services, urban health inequities, remote sensing for humanitarian response, and sustainable development in Sub-Saharan Africa. Advising : Supervised PhD students including Rim Mrani, Martí Bosch Padrós, Rémi Jaligot, and Andrea Salmi, with a focus on urban morphology, health accessibility, and digital urbanism. Scientific Networks : Collaborated with institutions in Switzerland, Kenya, Côte d'Ivoire, Cameroon, and Morocco. Published in journals like Water , Science of The Total Environment , and Sustainability , addressing topics such as water distribution, sanitation safety, and urban resilience. Teaching : Leads courses on Urban Planning in the South and contributes to doctoral programs, emphasizing interdisciplinary approaches to urban challenges.

Franck IutzelerView profile

Professor

• Numerical optimization
• Statistical learning
• Stochastic programming
• +5 more

Franck Iutzeler is a Professor of Applied Mathematics at Université de Toulouse, working within the Statistics & Optimization team of the Institut Mathématique de Toulouse and teaching in the Department of Mathematics. He previously served as an Assistant Professor at Université Grenoble Alpes from 2015 to 2023 and completed his Habilitation à Diriger des Recherches in 2021. His research focuses on the intersection of optimization, statistics, and optimal transport theory to develop robust data-driven models. Key areas include numerical optimization, statistical learning, stochastic programming, and optimal transport. He is particularly interested in distributionally robust optimization using Wasserstein metrics and has developed the skwdro Python library for implementing these methods. Iutzeler's recent publications demonstrate a strong focus on Wasserstein Distributionally Robust Optimization (WDRO), with multiple papers in top venues like NeurIPS and SIAM Journal on Optimization. His work bridges theoretical guarantees with practical implementation, particularly through the skwdro library which provides efficient code for WDRO in machine learning applications. ANR JCJC grant for project STROLL: Harnessing Structure in Optimization for Large-scale Learning Co-PI of ANITI chair on Trust and Responsibility in Artificial Intelligence led by JM. Loubes and J. Bolte Iutzeler actively supervises PhD students including Yu-Guan Hsieh (awarded Université Grenoble Alpes's PhD award), Gilles Bareilles, Waïss Azizian, and Victor Mercklé. He has secured research funding through the ANR (MAD project on Automatic Differentiation) and ANITI. His current research includes statistical fairness using optimal transport theory and automatic differentiation for stochastic optimization. He leads the development of the skwdro library for Wasserstein Distributionally Robust Optimization and is involved with ANITI (Toulouse's AI Cluster), where he also took responsibility for the 2nd year of the Master SID in Data Science & Engineering in September 2024.

Monika Maurhofer BringolfView profile

Professor

• Plant Pathology
• Microbial Ecology
• Biological Control
• +5 more

Monika Maurhofer is a Professor at the Department of Environmental Systems Science, ETH Zurich , specializing in multitrophic interactions within the rhizosphere. Her research bridges plant pathology, microbial ecology, and biological control of plant diseases and insect pests. 1988: Dipl. sc. nat., ETH Zurich 1993: Dr. sc. nat., ETH Zurich Research focuses on biocontrol pseudomonads and their molecular interactions with plants, fungi, and insects. Key projects include: Understanding Pseudomonas protegens mechanisms in rhizosphere colonization Comparative genomics of entomopathogenic bacteria Developing disease-suppressive compost diagnostics Investigating microbial consortia for pest control 2024-2025 publications highlight her work on entomopathogenic pseudomonads and nematode-bacteria symbiosis , with applications in sustainable agriculture. She received the Golden Owl Award for teaching excellence in 2014 and 2017. Current collaborations include Syngenta Crop Protection and interdisciplinary teams at University of Zurich and University of Basel.

Fabian AbiusiView profile

Researcher

• Microalgae Biotechnology
• Sustainable Food Processing
• Bioprocess Engineering
• +3 more

Dr. Fabian Abiusi is a post-doctoral researcher in Sustainable Food Processing at ETH Zurich's Institute of Food, Nutrition and Health, part of the Department of Health Sciences and Technology (D-HEST). His work focuses on developing innovative bioprocesses to convert industrial food by-products into high-quality microalgal biomass using mixotrophic cultivation strategies. His research emphasizes enhancing microalgae productivity through oxygen-balanced systems and improving protein bioaccessibility via in vitro digestion models and cell disruption techniques. His academic background includes a PhD (details unspecified) followed by postdoctoral research at ETH Zurich. Key research themes include acidophilic microalgae (e.g., Galdieria sulphuraria), photobioreactor optimization, and leveraging extremophilic organisms for sustainable food production. He has contributed to projects like the MAB2.0 initiative integrating algae into wastewater treatment systems. Abiusi's publications highlight advancements in mixotrophic cultivation, protein bioaccessibility assessment, and utilization of volcanic microalgae for nutritional applications. Though no awards are explicitly listed, his work aligns with emerging trends in circular bioeconomy and alternative protein sources. His research group collaborates on lab-scale to pilot-scale systems, aiming to bridge gaps between microbial biotechnology and food industry applications.

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.

Harish GopalakrishnanView profile

Researcher

• Combustion Engineering
• Thermoacoustics
• Sustainable Energy
• +3 more

Dr. Harish Gopalakrishnan is a Researcher at Zurich University of Applied Sciences' School of Engineering, affiliated with the IEFE Distributed Thermal Energy Systems department. His work focuses on combustion dynamics, thermoacoustic stability, and sustainable energy systems, particularly for hydrogen-based and carbon-free fuels. Research Interests: Thermoacoustic stability analysis in combustion systems Hydrogen and sustainable aviation fuel combustion Flame dynamics and autoignition front propagation Reactor-network modeling for emissions prediction Hydrodynamic stability of swirl flows Publication Trends: His publications over the past seven years emphasize hydrogen combustion systems, intrinsic thermoacoustic instabilities, and modeling frameworks for sustainable fuel applications. Recent work explores transverse thermoacoustic mode prediction and flame response to velocity oscillations. Projects: He leads combustion research initiatives including "Combustion dynamics of spray flames operating on sustainable aviation fuels" and "Thermoacoustic analysis of hydrogen flames in micro/meso-scale combustion systems" , with ongoing collaborations at institutions like IIT Madras and ASME Turbo Expo. Labs & Teams: Dr. Gopalakrishnan contributes to the IEFE Distributed Thermal Energy Systems lab at ZHAW, focusing on advanced combustion technologies for aerospace and energy applications.

• Thermal Energy Storage
• Process Engineering
• Environmental Engineering
• +6 more

Prof. Jörg Worlitschek is Head of the Institute of Mechanical Engineering and Energy Technology (IME) and Professor at the Lucerne School of Engineering and Architecture, part of Lucerne University of Applied Sciences & Arts. He holds a PhD in Thermal Process Engineering from ETH Zurich and has extensive industry experience, including roles at Mettler Toledo. His research focuses on thermal energy storage (TES), crystallization processes, and sustainable energy systems. Education: Studies in Chemical Engineering at University of Erlangen M.Sc. in Energy and Process Engineering from Technical University of Berlin PhD in Thermal Process Engineering from ETH Zurich (2003) Research Interests: Thermal Energy Storage (TES) systems for buildings and grids Phase Change Materials (PCMs) for latent heat storage Integration of solar and PV systems with TES Decarbonization of heating systems Process optimization in crystallization and heat transfer Achievements & Projects: Founder of the Competence Center Thermal Energy Storage (CC TES) Co-founder of SpinOff Cowa (compact energy storage solutions) Key contributor to projects like SWEET PATHFNDR and SwissSTES Over 150 peer-reviewed publications and 6 patents Awards: Recipient of the Best Paper Award at the 2015 Greenstock Conference for contributions to energy storage research. Labs/Teams: Leads the IME Institute and collaborates with SCCER Heat & Electricity Storage and international networks like IEA Annex 35.

• Multi-Agent Systems
• Hypermedia Systems
• Web of Things
• +3 more

Andrei Ciortea is an Assistant Professor in Interaction and Communication based Systems at the University of St. Gallen, affiliated with the ICS-HSG (Interaction and Communication Systems) department. His research focuses on Internet-scale multi-agent systems, hypermedia systems, the Web of Things, and socio-technical systems. He explores topics such as autonomous agents, hypermedia environments, and the integration of digital twins in industrial automation. Key research interests include the design of adaptive coordination mechanisms, affordance-driven interaction models, and semantic hypermedia search. His work emphasizes practical applications in manufacturing, energy systems, and sustainable design. Notable contributions include the HyperBrain project leveraging large language models for human-inspired guidance and the Solid-based Pody framework for agent embodiment in web systems. He received the Best Paper Award at the 6th International Conference on the Internet of Things (IoT 2016). His publications span topics like digital twin ecosystems, circular design strategies, and governance frameworks for autonomous agents on the web. Current research trends highlight the interplay between agent autonomy, hypermedia architectures, and socio-technical interactions in smart environments. Dr. Ciortea collaborates on interdisciplinary projects involving AI ethics, transparent machine intelligence, and real-time collaboration in linked data systems. His work bridges theoretical agent models with real-world industrial applications, emphasizing scalable, interoperable solutions for distributed systems.

Ilya KarlinView profile

Lecturer

• Fluid Dynamics
• Computational Fluid Dynamics
• Thermodynamics
• +3 more

Prof. Ilya Karlin is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich. His research focuses on advanced computational fluid dynamics, particularly leveraging lattice Boltzmann methods for simulating complex fluid phenomena. Key areas include non-ideal fluid behavior, multiphase flows, combustion processes, and hydrodynamic closures. He has contributed extensively to improving numerical methods for compressible flows, turbulent systems, and reactive mixtures in porous media. His work bridges kinetic theory with continuum mechanics, addressing challenges in hydrodynamic manifolds and non-local effects. Dr. Karlin's publications emphasize rigorous mathematical analysis alongside computational innovation, such as spectral closure techniques and entropy-based models. His research often explores the interplay between microscopic kinetic descriptions and macroscopic hydrodynamic equations. He has developed novel algorithms like the 'particles on demand' method for handling strong discontinuities in flows. Recent work includes studies on rarefaction effects, capillarity-viscosity balance, and exact hydrodynamic manifolds for BGK equations. His studies span diverse applications from microfluidics and phase transitions to detonation modeling and environmental fluid mechanics. While no specific awards are listed in the provided text, his prolific publication record indicates significant contributions to the field of computational fluid dynamics.