جست‌وجوی استاد و پژوهشگر

Slavica Jonicمشاهده پروفایل

عضو هیئت علمی

• Cryo-Electron Microscopy
• Biomedical Signal Processing
• Artificial Intelligence
• +۴ مورد دیگر

Slavica Jonic is a Research Director at CNRS, affiliated with Sorbonne University at the Institute of Mineralogy, Materials Physics, and Cosmochemistry (IMPMC-UMR 7590) in Paris, France. She obtained her PhD in Image Processing from EPFL (Switzerland) in 2003 and a Research Director Habilitation from UPMC (France) in 2015. She leads the 'Image analysis for biomolecular structural and dynamics studies' subgroup under the BiBiP team and co-leads the IMPMC transversal axis on 'Theory, Artificial Intelligence, Big Data.' Her research focuses on developing algorithms that integrate image analysis , molecular mechanics simulation , and artificial intelligence to explore conformational dynamics of biomolecules via in vitro and in situ cryo-EM and cryo-ET. Key software contributions include ContinuousFlex , HEMNMA , StructMap , MDTOMO , and MDSPACE , which are used to study complexes like nucleosomes, ribosomes, SARS-CoV-2 spike, and ATPase p97. Her work is supported by ANR , CNRS , Sorbonne University , and GENCI . She mentors PhD students and Master interns and serves on editorial boards for journals like BMC Methods and Frontiers in Molecular Biosciences . She also organizes workshops on cryo-EM and AI.

Alexander Heinleinمشاهده پروفایل

استادیار

• Numerical methods for partial differential equations
• Scientific computing
• Domain decomposition methods
• +۶ مورد دیگر

Dr. Alexander Heinlein is an Assistant Professor in the Numerical Analysis group at the Delft Institute of Applied Mathematics (DIAM), Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS), Delft University of Technology (TU Delft). His work bridges scientific computing and machine learning through scientific machine learning (SciML) , focusing on domain decomposition methods and multiscale approaches for solving complex partial differential equations on modern hardware like GPUs. Research interests include: Developing high-performance computing algorithms for nonlinear PDEs with applications in fluid-structure interaction and photonic crystals Advancing physics-aware machine learning techniques for groundwater heat transport and post-burn contraction prediction Creating parallel preconditioners like FROSch for challenging problems in computational mechanics Building hybrid numerical-ML frameworks with domain decomposition for multi-physics applications His recent publications highlight a 128-235x speedup in biomedical simulations through deep operator networks , and keynote presentations on geometric challenges in machine learning-based surrogate models at international conferences like CASML 2024. Scientific awards include: 2025 NWO Open Technology Programme grant for the RAPID-Wind project on offshore wind turbine foundations Students and collaborations involve: Yuhuang Meng (PhD candidate, 2024) Jing Zhao (co-supervisor) Prof. Jun Zou (Chinese University of Hong Kong collaboration, 2024) He leads software development for COMSOL and Trilinos extensions while maintaining open-source reproducibility standards.

Víctor Elviraمشاهده پروفایل

مدرس ارشد

• Bayesian Inference
• Sequential Monte Carlo Methods
• Importance Sampling
• +۵ مورد دیگر

Víctor Elvira is a Senior Lecturer at the University of Edinburgh, specializing in Bayesian inference, sequential Monte Carlo methods, and computational statistics. He serves as an Associate Editor for IEEE Transactions on Signal Processing and organizes major academic events like the Sequential Monte Carlo Workshop (SMC 2024) and Summer School in Bayesian Filtering (SSBF 2024) . Key research areas: Bayesian filtering, importance sampling, state-space modeling, and machine learning applications Recent work focuses on sparse graphical models, differentiable particle filters, and Monte Carlo optimization Scientific Awards : 2025 EURASIP Early Career Award 2024 ELLIS Fellow 2023 Leverhulme Research Fellow 2021 Alan Turing Fellow 2018 Fulbright & Marie Curie Fellow 2018 IEEE Senior Member He has delivered PhD courses on Monte Carlo methods and Bayesian filtering in Madrid (2025) and Barcelona (2025), and maintains open-access software implementations for publications like Sparse Graphical Linear Dynamical Systems and Graphical Inference in Linear-Gaussian State-Space Models .

Isabelle Guyonمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Isabelle Guyon is a Full Professor at University Paris-Saclay and a Research Scientist at Google DeepMind since 2022. She is also a community lead for the open-source Codalab competitions project and President of ChaLearn, a non-profit organizing machine learning challenges. Her career spans academia, industry, and non-profit leadership, with affiliations at INRIA and the LISN laboratory. PhD in Paris under Gerard Dreyfus and Leon Personnaz Bell Labs researcher (1990s) Graduate of ESPCI Her research focuses on machine learning challenges and benchmarks across diverse domains including causality , computer vision , deep learning , and high energy physics . Recent projects explore power grid optimization , LLM-assisted paper reviewing , and systematic bias mitigation in AI applications. Key awards include the BBVA Frontier in Knowledge Award (2020), ICMI Ten-Year Impact Award (2023), and IEEE Best Paper Award (2023). She is also an ELLISS fellow and AMIA fellow .

• Process Automation
• Analytical Chemistry
• Sustainable Technologies
• +۷ مورد دیگر

Vorlet Olivier is an Associate Professor at the University of Applied Sciences and Arts Western Switzerland (HES-SO), affiliated with the Fribourg School of Engineering and Architecture under the ChemTech Institute. His research spans process automation, analytical chemistry, and sustainable technologies, with a focus on counterfeit drug detection, membrane technology for winemaking, and digitalization in industrial processes. His work includes developing low-cost capillary electrophoresis devices (OpenCE) for resource-limited settings, utilizing IoT for material shelf-life monitoring, and innovating membrane contactors for gas management in wines. He has also contributed to renewable energy projects like solar hydrogen production via hematite photoanodes and CO2 capture using ionic liquids. Key publications highlight his expertise in flow chemistry, spectroscopy, and process analytical technologies (PAT). Vorlet's collaborations with institutions like EPFL and projects funded by HES-SO Rectorat and industry partners underscore his role in bridging academic research with industrial practice. He employs open-source hardware/software frameworks to enhance device maintainability and accessibility in developing regions.

Tobias Kockmannمشاهده پروفایل

پژوهشگر

• Proteomics
• Mass Spectrometry
• Bioinformatics
• +۳ مورد دیگر

Tobias Kockmann is a Researcher at the Functional Genomics Center Zurich (FGCZ), a joint center of University of Zurich and ETH Zurich. Since 2017, he has served as a full-time employee specializing in proteomics, providing scientific and technical expertise across various proteomic methodologies while supporting user lab projects and maintaining research infrastructure. His educational background includes: Diploma in Biology and Informatics from University of Freiburg PhD in Epigenetics from ETH Zurich Research experience in a collaborative project between ETH Zurich and Novartis focused on protease substrate deconvolution using mass spectrometry Kockmann specializes in bottom-up proteomics with expertise spanning label-free screening workflows (both data-dependent and data-independent analysis modes), chemical and metabolic labeling techniques (TMT, SILAC, NeuCode), and targeted quantification strategies (SRM, PRM). His current focus includes making trapped ion mobility spectrometry (TIMS) accessible to the local research community and developing proteomics data analysis software in collaboration with the proteome informatics group. His work bridges technical proteomics expertise with computational approaches to advance biomedical research. Analysis of Kockmann's recent publications reveals a strong focus on applied proteomics across diverse biological contexts. His work spans parasitology (particularly Angiostrongylus vasorum research), dermatology, neuroscience, and molecular biology. Common themes include host-pathogen interactions, quantitative analysis of biological systems, and development of proteomics methodologies and software tools. His collaborative approach is evident through numerous co-authorships across different research domains. Kockmann actively contributes to methodological development in proteomics through internal research projects and collaborations. While specific grant information isn't detailed in the available text, his involvement in numerous publication projects suggests participation in various funded research initiatives. His technical expertise positions him as a valuable collaborator in interdisciplinary research teams requiring advanced proteomic analyses. At FGCZ, Kockmann works within the proteomics facility, collaborating closely with the proteome informatics group. His "special project" involves implementing trapped ion mobility spectrometry (TIMS) for the local research community, indicating his role in advancing the center's technological capabilities. His work environment emphasizes both service provision for user projects and internal methodological development.

Leonhard Heldمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Open Science
• +۵ مورد دیگر

Leonhard Held is a Professor of Biostatistics at the University of Zurich’s Faculty of Medicine, affiliated with the Epidemiology, Biostatistics and Prevention Institute (EBPI). He actively promotes open and reproducible research in health sciences, serving as Director of the UZH Center for Reproducible Science and as the university’s Open Science delegate. His research focuses on methodological aspects of epidemiological, clinical, and pre-clinical studies, with emphasis on meta-analysis, causal inference, and Bayesian statistical frameworks. Recent work explores reproducibility metrics, data-sharing practices, and the impact of school closures on infectious disease spread. Key trends in his publications include meta-regression for replication projects, survivor average causal effects in RCTs, and reproducibility challenges in oncology trials. He contributes to statistical software development (e.g., R package ‘polyCub’) and methodological guidelines for robust research practices. As a leader in open science, he advocates for training researchers in data-intensive workflows and developing sustainable open research data infrastructure, as evidenced by his involvement in Swiss stakeholder engagement studies.

• Computational Biology
• Computational Chemistry
• Drug Design
• +۲ مورد دیگر

Vittorio Limongelli is a Full Professor at the Faculty of Biomedical Sciences, Università della Svizzera italiana (University of Italian Switzerland). His research focuses on computational biology, drug design, and molecular simulations, with applications in pharmacology and medicinal chemistry. PhD in Drug Sciences (2007) Postdoctoral research at ETH Zurich His work explores advanced computational methods for drug/target binding interactions, including enhanced sampling simulations and machine learning approaches. Notable research themes include G protein-coupled receptor dynamics, bile acid receptor modulation, and extracellular vesicle profiling for disease risk assessment. Scientific awards include the Premio Scrocco (2013), Young Researcher in Medicinal Chemistry award (2016), EFMC Prize runner-up (2017), and recognition as a top 5 scientist in physical/chemical sciences for the USERN Prize (2020). He received an ERC Consolidator Grant in 2020. Email: vittorio.limongelli@usi.ch Office: East Campus, Sector D, Office D5.07 (Level P5), Via la Santa 1, 6962 Lugano-Viganello

Athanasios Mokosمشاهده پروفایل

پژوهشگر

• Computational Physics
• Geochemistry
• Fluid Dynamics
• +۵ مورد دیگر

Dr. Athanasios Mokos is a researcher at the Paul Scherrer Institute (PSI) in Switzerland, specializing in computational physics and fluid dynamics. His work bridges nuclear engineering, geochemistry, and environmental engineering through advanced numerical simulations. Expertise in SPH (Smoothed Particle Hydrodynamics) Focus on reactive transport and multiphase flow Key applications in nuclear reactor safety and subsurface processes Research spans pore-scale modeling of cement-clay interactions, gas transport in geological media, and GPU-accelerated simulations for multiphysics problems. His publications emphasize machine learning integration, environmental remediation, and coastal/coastal structure hydrodynamics. Current trends in his work include Digital Twin frameworks for carbonate precipitation, CRUD analysis in nuclear fuel assemblies, and validation of surface wetting models via lattice Boltzmann methods. His position at PSI involves high-performance computing and multiphase flow simulations, with contributions to desalination membrane design and sediment grain dynamics.

Enrico Celioمشاهده پروفایل

مدرس

• Sustainability Science
• Land-Use Planning
• Ecosystem Services
• +۴ مورد دیگر

Dr. Enrico Celio is a Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. He specializes in sustainability science, with a focus on participatory modeling, land-use planning, and ecosystem service assessments. His work integrates Bayesian networks and transdisciplinary approaches to address global development challenges in regions like Madagascar and Myanmar. Affiliated with ETH Zurich's Institute of Space and Landscape Development (D-BAUG) Teaches courses including Design Studio and participatory modeling modules Research Interests Celio's research bridges environmental science and policy through: Land-use decision modeling in tropical regions Ecosystem service mapping and governance Contextual adaptation of transdisciplinary methods His work emphasizes stakeholder engagement and participatory tools like the gBay platform. Projects Key initiatives include: PLUMALA: Participatory land-use modeling in telecoupled landscapes LP+: Developing agricultural planning processes in Switzerland Telecoupled Landscapes Project: Sustainable ecosystem service provision funded by Swiss r4d Grants & Funding Recipient of grants from: Swiss Programme for Research on Global Issues for Development (r4d) Federal Office for Agriculture (BLW)

Javier Argota Sánchez-Vaquerizoمشاهده پروفایل

مدرس

• Urban Digital Twins
• Participatory Governance
• Mobility Systems
• +۲ مورد دیگر

Javier Argota Sánchez-Vaquerizo is Lecturer in Computational Social Science at ETH Zurich, bridging architecture, urban design, and data science to transform urban decision-making. His work develops urban digital twins integrating human-computer intelligence for participatory governance and sustainable cities. Research integrates: Digital twin architectures for urban complexity Mobility system democratization VR-enabled participatory design Mixed-traffic optimization Deliberative democracy frameworks Recent publications demonstrate empirical validation of large-scale urban simulations (Barcelona traffic), VR studies of pedestrian perception, and comparative analyses of bike-sharing accessibility. Methodological innovations include multi-agent lane management (FAIRLANE) and open-source route recommendation systems prioritizing multi-criteria equity. Collaborates with Singapore's Future Cities Laboratory and European Research Council projects. Exhibited architectural work at Venice Biennale. Current projects examine metaverse-urbanism intersections and institutional frameworks for democratic digital twins.

Bruno Sudretمشاهده پروفایل

استاد

• Uncertainty Quantification
• Reliability Analysis
• Sensitivity Analysis
• +۳ مورد دیگر

Prof. Bruno Sudret is a Full Professor of Risk, Safety, and Uncertainty Quantification at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. His research focuses on computational methods for uncertainty quantification, reliability analysis, and Bayesian approaches for model calibration. He has contributed to the development of the UQLab software framework and the UQWorld community platform. Before joining ETH Zurich in 2012, Sudret held roles at the University of Berkeley (postdoc), EDF R&D (researcher and group head), and Phimeca Engineering (Director of Research and Strategy). Education: Master's in Science from Ecole Polytechnique (1993), Master's and PhD in Civil Engineering from Ecole Nationale des Ponts et Chaussées (1996, 1999). His work emphasizes stochastic simulators, surrogate modeling, and reliability-based design optimization. He serves on editorial boards for journals like Reliability Engineering and Systems Safety and Structural Safety .

David Florian Vetschمشاهده پروفایل

مدرس

• Hydraulic Structures
• River Morphology
• Sediment Transport
• +۲ مورد دیگر

David Florian Vetsch is Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering and head of the Numerical Modelling research group at the Laboratory of Hydraulics, Hydrology and Glaciology. His research develops numerical models for hydraulic engineering challenges including sediment transport, river morphodynamics, vegetation dynamics, and turbulence modeling. Since 2002, Vetsch has led development of BASEMENT, an open-source software for hydro- and morphodynamic simulations. His work addresses fundamental and applied problems in river engineering, hydraulic structures, and environmental fluid dynamics.

Carol V. Alexandruمشاهده پروفایل

پژوهشگر

• Software Engineering
• Command Line Interface (CLI)
• Software Analysis
• +۳ مورد دیگر

Carol V. Alexandru is a Senior Research Associate at the University of Zurich's Department of Informatics. Her research focuses on understanding developer interactions with command line interfaces (CLI), contrasting them with visual tools like IDEs. She investigates barriers to CLI adoption and develops tools to enhance CLI usability. Key projects include LISA, a high-performance library for fine-grained historical software analysis; Signal/Collect Console, a debugging tool for graph computations; and Facets of Software Evolution, a software quality analysis platform. She has contributed to teaching roles since 2013, including course administration for Informatics I, Advanced Software Engineering, and Programming Languages and Paradigms. Her work bridges software engineering theory and practical tool development, emphasizing scalable historical analysis and developer-centric tool design.

• Financial Econometrics
• Time Series Analysis
• Risk Management
• +۱ مورد دیگر

Simon Broda is a Lecturer at the Lucerne School of Business's Institute of Financial Services Zug (IFZ), Lucerne University of Applied Sciences and Arts. His research focuses on: Financial econometrics and time series analysis Risk modeling for heavy-tailed distributions Development of statistical software tools His publications showcase expertise in ARCH modeling, risk measurement, and statistical computing. Recent work emphasizes practical financial applications through open-source software development. Awards: Multiple Lecturer of the Year honors Erich Schneider Memorial Award for outstanding thesis