Find Academic Supervisors

• Modelling and simulation of multi-physics systems
• Machine learning and data analysis
• High performance computing
• +3 more

Dr. Tobias Kaufmann is the Acting Head of the FHNW Institute of Mathematics and Natural Sciences and a Lecturer in Mathematics at FHNW's School of Engineering and Environment. He teaches in bachelor's programs including Mechanical Engineering, Electrical and Information Technology, Computer Sciences, and Energy and Environmental Technology. His research focuses on multi-physics system modeling, machine learning, high-performance computing, ultrasonics, radar, and vacuum measurement technologies. He holds a PhD in theoretical physics from the University of Zurich and completed postdoctoral research at ETH Zurich and the University of California, Irvine. Education Background: Tobias Kaufmann earned a Diploma in Theoretical Physics and a Teaching Diploma from the University of Zurich. He also holds a CAS in Higher Education from the University of Applied Sciences of Eastern Switzerland. His professional career spans roles as a Professor at the University of Applied Sciences of Eastern Switzerland, a Data Scientist at Geopraevent, a Scientist at ABB Corporate Research, and a Principal Investigator at ETH Zurich's Department of Physics. Research Interests: His work bridges computational physics and engineering applications, emphasizing: Multi-physics system modeling and simulation Machine learning for data analysis and predictive systems High-performance computing for large-scale simulations Ultrasonic and radar sensing technologies Continuum mechanics and electrodynamics Notable Projects: As project leader, he has managed initiatives like the Innosuisse-funded 'Optimized Side Seamer for Fleximed tube bodies' with Neopac AG and SF-funded projects on particle-based CFD simulations, smart power tools, food industry classifiers, and cable car dynamics simulators. Collaborations include Hilti AG, Winterhalter AG, and Bartholet AG. Technical Contributions: His inventions include non-intrusive liquid level measurement systems (patented with ABB) and acoustic signal propagation methods. He has also contributed to Google's AI research, including text prediction and communication template systems.

• Biomechanical Engineering
• Hip Fracture Prevention
• Food Biotechnology
• +3 more

Dr. Anita Fung is a Researcher at the Institute for Biomechanics, part of the Department of Health Sciences and Technology at ETH Zürich. Her work spans interdisciplinary research in biomechanical engineering and food biotechnology. She is affiliated with the Laboratory for Orthopaedic Technology and contributes to the Professorship for Biomechanics. Her primary research focuses on hip fracture prevention through biomechanical simulations and experimental methods, as well as innovative applications of microalgal proteins in food technology. Key areas include prophylactic implant design, finite element modeling of bone-implant interactions, and structural analysis of sustainable meat analogues. Dr. Fung’s research employs advanced techniques such as high-speed x-ray imaging, ex vivo testing, and computational modeling to evaluate fracture risks and improve medical devices. Her food science work explores protein properties of microalgae for high-moisture extrusion processes, addressing challenges in sustainable food systems. She has collaborated on studies analyzing footwear effects on running injuries and long-term prosthetic bone remodeling. Her publications span topics from ceramic-based femoral augmentation to biomechanical modeling of sideways fall impacts. She actively contributes to interdisciplinary projects, blending clinical biomechanics with food biotechnology to advance medical and sustainable food technologies.

Benedikt HelgasonView profile

Senior Lecturer

• Biomechanics
• Finite Element Analysis
• Orthopedic Surgery
• +4 more

PD Dr. Benedikt Helgason is a Senior Lecturer at the Department of Health Sciences and Technology, ETH Zürich. He works at the Institute for Biomechanics (Laboratory for Orthopaedic Technology), focusing on computational modeling of bone mechanics and medical device innovation. His research spans: Finite element analysis of bone-implant interactions Fracture risk prediction algorithms Computational modeling Medical device design and testing Machine learning applications in biomechanics Recent work demonstrates expertise in generating super-resolution 3D models from clinical CT scans, optimizing spinal fusion cages through topology design, and developing frameworks for early health technology assessments. He investigates prophylactic intramedullary nailing for hip fracture prevention and evaluates neural network models for screw stability prediction. Key collaborations include the AGES-Reykjavik study cohort for aging research and experimental validation of finite element models using high-speed x-ray techniques. His team develops validated, non-linear explicit FE models for screw-bone interactions and explores bioresorbable magnesium-fiber reinforced bone cements. Contact: bhelgason@ethz.ch

Johannes Josef SchneiderView profile

Researcher

• Applied Complex Systems Science
• Artificial Chemistry
• Microfluidics
• +3 more

Dr. Johannes Josef Schneider is a Researcher at the Zurich University of Applied Sciences (ZHAW) School of Engineering, affiliated with the Applied Complex Systems Science research group. His work focuses on computational modeling of complex systems, particularly artificial chemistry and microfluidic droplet networks. Research interests span: Artificial chemistry implementation in droplet-based systems Geometric constraints in particle agglomeration 3D arrangement of droplets and vesicles Computational methods for pandemic intervention modeling Network formation in polydisperse systems Schneider has contributed to several key projects including Bio-HhOST (as Deputy Project Leader) and SARS-CoV-2 intervention modeling. His collaborative research involves extensive work on chemical programmability using droplet agglomerations and ethical aspects of computational modeling. Research outputs demonstrate consistent focus on: Development of computational frameworks for chemical synthesis Analysis of droplet dynamics in constrained geometries Modeling of spatial population dynamics Investigation of vesicular interactions

• Operational Research
• Staff Scheduling
• Job Shop Scheduling
• +4 more

Andreas Klinkert is a Professor at the Zurich University of Applied Sciences (ZHAW) , specifically affiliated with the School of Engineering and the Institute of Data Analysis and Process Design . His work focuses on operational research and optimization problems in complex industrial and logistical environments. Project Leader: Airport Ground Staff Scheduling (2023) Team Member: SARS-CoV-2 Intervention Modelling Extension Project Leader: Operational Staff Planning (2021) Project Leader: Automated Staff Scheduling (2020) Deputy Project Leader: Flight Network Simulation at Swiss International Air Lines His research integrates computational modeling with practical applications in staff rostering, production planning, and airport logistics. With a focus on combinatorial optimization and dynamic scheduling, he has developed algorithmic solutions for real-world problems across multiple industries. Klinkert has contributed to the field through publications on topics like job shop scheduling with blocking constraints, multi-skill staff rostering, and large-scale crew scheduling. His work often involves interdisciplinary collaborations and practical implementations of optimization algorithms in industrial settings.

Christoph KochView profile

Professor

• Database Theory
• Query Optimization
• Data Management Systems
• +4 more

Christoph Koch is a Full Professor of Computer Science at École Polytechnique Fédérale de Lausanne (EPFL), leading the Data Analysis Theory and Applications Laboratory (DATA). His academic journey includes previous roles as Associate Professor at Cornell University (2007-2010) and Saarland University (2005-2007), with academic foundations from TU Vienna (PhD 2001, Habilitation 2004) and research at CERN. Education: PhD in Artificial Intelligence (TU Vienna & CERN, 2001), Habilitation (TU Vienna, 2004) Appointments: EPFL (2010-present), Cornell University (2007-2010), Saarland University (2005-2007), TU Vienna (2003-2005) His research focuses on database theory and systems , with recent work spanning query optimization , transaction processing , and parallel data management . His publications address topics like robustness under SQL isolation levels , quantifier elimination for query optimization , and Datalog extensions . Articles trend toward high-dimensional data cubes , transactional concurrency , and embedded DSLs for performance-critical systems . Scientific accolades include: Best Paper Awards: PODS (2002) ICALP (2005) SIGMOD (2011) VLDB (2014) GPCE (2017) ERC Consolidator Grant (2011) Google Research Award (2009) ACM SIGLOG Alonzo Church Award (2021) He has advised numerous PhD students including Immanuel Trummer (now at Cornell), Milos Nikolic (Edinburgh), and Lionel Parreaux (HKUST). His lab contributes to query engine architectures , parallel processing systems , and quantum computing applications in database optimization.

Mark PaulyView profile

Professor

• Geometric Computing
• Geometry Processing
• Digital Fabrication
• +7 more

Mark Pauly is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) School of Computer and Communication Sciences, where he directs the Geometric Computing Laboratory (GCM). His research focuses on computational design, geometry processing, and digital fabrication of material systems through efficient algorithms and mathematical abstractions. Education: PhD (ETH Zurich, 2003), MS (TU Kaiserslautern, 1999) Research spans geometric computing, deployable structures, programmable materials , and human performance capture , with applications in architecture, soft robotics, and digital fabrication. Recent publications emphasize inverse design of surface-based inflatables, flexible microstructures, and curved beam assemblies. Scientific contributions include 2016 Eurographics Outstanding Technical Contributions Award , 2010 ERC Starting Grant , and 2023 ACM SIGGRAPH Asia Best Paper Award Honorable Mention Co-founded EPFL spin-offs: Faceshift AG (real-time facial animation) and Rayform SA (computational caustic design) His work integrates mathematics, computer science, and materials engineering to solve geometric inverse problems. Articles show increasing focus on auxetic materials , elastic mechanisms , and computational design for advanced manufacturing .

Frédéric MilaView profile

Professor

• Condensed Matter Theory
• Quantum Magnetism
• Frustrated Spin Systems
• +5 more

Frédéric Mila is a full Professor and Chair of Theoretical Condensed Matter Physics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences (SB), Institute of Physics (IPHYS), and the Condensed Matter Theory Group (CTMC). He also holds roles in the Doctoral Program in Physics (EDPY) and the School of Physics and Engineering (SPH-ENS). His research centers on quantum magnetism, frustrated systems, and strongly correlated electrons. His research interests include quantum magnetism, frustrated spin systems, quantum phase transitions, tensor network methods, and quantum spin liquids . He employs both analytical approaches and advanced numerical techniques to study complex quantum phenomena in low-dimensional and geometrically frustrated materials. His recent publications reveal a strong focus on magnetization plateaus, quantum dimer models, spin liquids, and high-field quantum phases , particularly in compounds like SrCu2(BO3)2 and theoretical models such as the Shastry-Sutherland and triangular lattice antiferromagnets. His work often bridges theory with experimental findings from neutron scattering and high-field measurements. Scientific Awards: Charpak-Ritz Prize (2024) – Awarded by the French and Swiss Physical Societies. Advising and Grants: Prof. Mila actively mentors a large group of doctoral students and has supervised numerous PhD theses at EPFL. His students have worked on diverse topics including SU(N) spin chains, tensor networks, frustrated magnetism, and quantum Monte Carlo methods. His sustained publication record in top journals indicates continuous funding and active research leadership. Labs and Teams: He leads the Condensed Matter Theory Group (CTMC) at EPFL, which focuses on theoretical and computational aspects of quantum materials. The group collaborates closely with experimentalists and uses state-of-the-art numerical tools to investigate quantum phases of matter.

Yves RevazView profile

Senior Lecturer

• Astrophysics
• Galaxy Formation and Evolution
• Dwarf Galaxies
• +7 more

Yves Revaz is a Senior Lecturer and Researcher at the Laboratory of Astrophysics (LASTRO) within the School of Basic Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is affiliated with both the LASTRO astrophysics laboratory and the Science Program for High-schools (SPH) teaching unit, and serves on the Physics Doctoral Program Committee. His work bridges advanced computational astrophysics with educational outreach and virtual reality visualization. Revaz's research focuses on the formation and evolution of galaxies, particularly dwarf galaxies, using high-resolution numerical simulations. He develops and employs the GEAR chemo-dynamical code and the pNbody analysis library to study chemical evolution, dark matter properties, and the impact of primordial magnetic fields. His work connects galaxy-scale processes with cosmological models, especially in the context of ΛCDM. He also leads VIRUP, a virtual reality platform that enables immersive exploration of cosmic data from both observations and simulations, and has produced educational VR films on the structure of the Universe. His recent publications highlight key themes: the abundance and distribution of dwarf satellite galaxies, the circumgalactic medium in Milky Way-like systems, radiative transfer modeling at exa-scale, and the use of dwarf galaxies as cosmological probes. These works are part of major collaborative efforts such as the AGORA simulation comparison project and the Euclid space mission. Yves Revaz supervises PhD students and teaches courses in general physics (mechanics) and astrophysics (stellar and galactic dynamics). He has mentored several doctoral candidates to completion at EPFL, contributing significantly to training the next generation of astrophysicists.

Christian Gabriel TheilerView profile

Associate Professor

• Plasma Physics
• Tokamak Boundary Physics
• Magnetic Confinement Fusion
• +3 more

Christian Gabriel Theiler is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the Swiss Plasma Center (SPC) under the School of Basic Sciences . He leads research on tokamak boundary physics and detachment dynamics , contributing to projects like the TCV Tokamak and Toroidal Fusion . He also serves as a Teaching Assistant for physics courses and chairs the PhD Program Committee in Physics . Research Focus : Tokamak boundary physics, plasma turbulence, divertor design, and diagnostic techniques. Awards : IAEA Nuclear Fusion Award (2020) SNSF Eccellenza Grant (2019-2023) EUROfusion Enabling Research Grant (2019-2020) Young Scientist Award (IUPAP) (2015) Key Collaborations : MIT, EUROfusion, SNSF, and ASDEX Upgrade teams. Students : Supervises multiple PhD candidates and has mentored past students in plasma physics. His recent research trends emphasize detachment physics in advanced divertor configurations, plasma shaping effects on turbulence, and machine learning for filament tracking. Publications span topics like parallel flows , SOLPS-ITER validation , and neutral interactions in fusion plasmas. Teaching includes General Physics and Plasma Physics courses.

Laurent VillardView profile

Professor

• Plasma Physics
• Nuclear Fusion
• Computational Physics
• +3 more

Laurent Villard is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Basic Sciences and Department of Physics. He specializes in plasma physics and nuclear fusion research, focusing on instabilities caused by energetic particles in tokamaks, equilibrium and stability calculations for plasma configurations, and high-performance computing simulations for magnetized plasma turbulence. His research collaborations include Joint European Torus (JET), General Atomics (USA), Keldysh Institute (Moscow), and Max-Planck Institute for Plasma Physics. He has supervised multiple PhD theses in plasma physics and fusion energy.

Jérôme Henri KämpfView profile

Lecturer

• Urban Physics
• Modelling, simulation and optimisation
• Building Energy Efficiency
• +8 more

Jérôme Henri Kämpf is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI), Institute of Electrical Engineering (IEM), and the Laboratory of Intelligent Systems (LIDIAP). He also serves as a Senior Research Scientist in Energy Informatics at the Idiap Research Institute. His academic career spans roles at EPFL’s LESO-PB laboratory, including PhD student, post-doc, and team leader in sustainable urban development and urban systems simulation, followed by a professorship in Building Energy Efficiency at HEIA-FR (HES-SO Fribourg) from 2016 to 2018. PhD in On the Modelling and Optimisation of Urban Energy Fluxes, EPFL, 2009 Master in Pedagogics, Haute Ecole Pédagogique Lausanne, 2005 Master in Computer Science, University of Lausanne, 2003 Master in Physics, University of Lausanne, 2001 His research focuses on urban physics, modeling, simulation, and optimization of urban energy systems, daylighting, thermal comfort, and sustainable urban design. He has made significant contributions to urban energy simulation tools such as CitySim, BTDF-based daylight modeling, and real-time photometric systems. His work bridges computer science, physics, and building engineering to develop data-driven solutions for urban sustainability. The 15 most recent publications highlight a consistent focus on urban energy modeling, daylight simulation, and thermal comfort. Key themes include the integration of HDR sky monitoring for daylight control, urban greening for cooling, and parametric interfaces for urban simulation. His research employs advanced computational methods, including evolutionary algorithms and wavelet transforms, applied to building and urban-scale energy performance. He has advised several PhD students, including Chantal Basurto Dávila, Silvia Coccolo, Diane Perez, and Yujie Wu. While no formal scientific awards are listed, his extensive publication record in high-impact journals and conferences reflects strong scholarly recognition. He has been involved in significant research grants and collaborative projects related to urban sustainability, energy informatics, and climate-responsive design. Kämpf is associated with key research teams including the LESO-PB laboratory at EPFL and the Idiap Research Institute. His work in the Urban Systems Simulation team and contributions to the CitySim platform demonstrate leadership in integrating simulation tools into architectural and urban design workflows.

Michele VidulisView profile

Academic

• Geometric Computing
• Geometry Processing
• Optimization
• +4 more

Michele Vidulis is a Doctoral Assistant and PhD student at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Geometric Computing Laboratory (GCM) in the School of Computer and Communication Sciences. She is pursuing her doctoral studies in the Doctoral Program in Computer and Communication Sciences (EDIC). Institution: École Polytechnique Fédérale de Lausanne (EPFL) School: School of Computer and Communication Sciences (IC) Department: Department of Computer Science (IINFCOM) Laboratory: Geometric Computing Laboratory (GCM) Status: Doctoral Assistant and Student She earned her Master of Science in Computational Science and Engineering from both the Polytechnic University of Milan and EPFL (2018–2021), and her Bachelor of Science in Mathematical Engineering from the Polytechnic University of Milan (2015–2018). Her research interests center on geometric computing, geometry processing, optimization, and physics-based simulation. These areas involve developing computational methods for modeling, analyzing, and simulating geometric data, with applications in computer graphics, scientific computing, and engineering. Her work likely focuses on algorithmic and mathematical foundations for manipulating complex shapes and physical systems. Michele is actively contributing to research at the Geometric Computing Laboratory, although no specific publications or scientific awards are listed in the available information. As a doctoral assistant, she combines research with academic responsibilities under the supervision of senior faculty members.

Shuqi WangView profile

Researcher

• Computational Neuroscience
• Machine Learning
• Neural Data Analysis
• +3 more

Shuqi Wang is a Doctoral Assistant at the Computational Neuroscience Laboratory (LCN) within the Brain Mind Institute (BMI) of the School of Life Sciences at Swiss Federal Institute of Technology in Lausanne (EPFL), holding dual staff appointments across the School of Life Sciences (SV) and School of Computer and Communication Sciences (IC). Wang simultaneously pursues doctoral studies in the Doctoral Program in Computer and Communication Sciences (EDIC), reflecting deep interdisciplinary engagement between neuroscience and computational disciplines. Research focuses on adapting machine learning for neural data analysis, specifically characterizing neural activity structure/properties in response to task inputs and reconstructing neural circuits from extracellular recordings. This work bridges theoretical neuroscience with advanced computational methods to decode neural coding principles and circuit organization, emphasizing high-dimensional neural representations and experience-dependent plasticity mechanisms. Recent publications (2021-2025) reveal consistent innovation in applying machine learning to neuroscience challenges, including neural coding hierarchies, inhibitory circuit reorganization, manifold learning in recurrent networks, and differentiable neural simulation. These contributions demonstrate expertise in spiking network modeling, statistical inference of neural data, and developing computational frameworks that integrate theoretical neuroscience with cutting-edge machine learning. Wang operates within EPFL's Computational Neuroscience Laboratory (LCN), a cross-school initiative between Life Sciences and Computer Science that develops mathematical models of neural computation under Professor Wulfram Gerstner's leadership. The lab's collaborative environment fosters work on neural dynamics, learning algorithms, and brain-inspired computing through strong ties to BMI and IINFCOM.

Ekrem Fatih YilmazerView profile

Researcher

• Computer Graphics
• Rendering
• Scientific Visualization
• +3 more

Ekrem Fatih Yilmazer is a Doctoral Assistant and PhD student at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the Realistic Graphics Lab (RGL) in the School of Computer and Communication Sciences . His position is active under the Institute of Computer Science (IINFCOM), and he is enrolled in the Doctoral Program in Computer and Communication Sciences (EDIC). Institution: École Polytechnique Fédérale de Lausanne (EPFL) School: School of Computer and Communication Sciences (IC) Department: Institute of Computer Science (IINFCOM) Lab: Realistic Graphics Lab (RGL) Status: Doctoral Assistant (Staff), PhD Student (EDIC) His research is centered in computer graphics, with a focus on realistic image synthesis, rendering techniques, and visual computing. The Realistic Graphics Lab at EPFL is known for its work in physically based rendering, light transport simulation, and computational imaging, indicating his involvement in advanced visual simulation and graphics algorithms. No publications are currently listed in the provided text, so no trends can be inferred at this time. There are no scientific awards mentioned in the provided information. As a doctoral assistant, Ekrem is likely involved in research projects funded by EPFL or collaborative grants, though specific funding sources are not disclosed. He may also contribute to academic mentoring within his lab, although no formal advisees are listed. His dual role supports both research and academic training within a leading computer science institution. He is a member of the Realistic Graphics Lab (RGL) at EPFL, a research group focused on advancing the state-of-the-art in image synthesis, rendering, and visual content creation using computational methods.