جست‌وجوی استاد و پژوهشگر

Manolis Zampetakisمشاهده پروفایل

استادیار

• Theoretical Machine Learning
• Statistics
• Optimization
• +۳ مورد دیگر

Manolis Zampetakis is an Assistant Professor of Computer Science at Yale University. Previously, he was a postdoc at UC Berkeley's EECS Department working with Michael Jordan, and earned his PhD from MIT's EECS Department under Constantinos Daskalakis. His research spans Theoretical Machine Learning, Statistics, Optimization, Computational Complexity, Game Theory, and Mechanism Design. He has received the ACM SIGEcom Doctoral Dissertation Award and a Google PhD Fellowship. Current affiliation: Yale University (Assistant Professor) Prior affiliations: UC Berkeley (Postdoc), MIT (PhD student), NTUA (Undergraduate) His research focuses on algorithmic game theory, robust statistics, and optimization challenges in machine learning. He explores computational complexity in multi-player games, truncated linear regression, and strategy-proof mechanisms. Recent work includes backdoor attacks in neural networks and jailbreaking black-box LLMs, with publications in top venues like NeurIPS, COLT, FOCS, and STOC. Notable scientific contributions have been recognized through awards and special issues. He co-organized workshops at FOCS 2018, WALE 2019, and WALE 2022. His students include Anay Mehrotra, Jane Lee, Katerina Mamali, Shuchen Li, and Nikolaos Koumpis, often co-advised with prominent researchers like Amin Karbasi and Tuomas Sandholm.

Alberto Pérez de Alba Ortízمشاهده پروفایل

استادیار

• Computational Soft Matter
• Molecular Dynamics Simulations
• Machine Learning for Molecular Science
• +۴ مورد دیگر

Dr. Alberto Pérez de Alba Ortíz is an Assistant Professor at the University of Amsterdam, affiliated with the Van 't Hoff Institute for Molecular Science (HIMS) and the Informatics Institute (IvI) within the Faculty of Science. He leads the Computational Soft Matter Lab and co-leads the Research Priority Area Artificial Intelligence for Sustainable Molecules and Materials. His educational background includes: Engineering Physics at Tecnológico de Monterrey, Mexico MSc in Computational Science and Engineering at TU München PhD cum laude in Computational Chemistry at the University of Amsterdam His research develops computational methods to bridge experimental and simulation scales in molecular systems using machine learning, enhanced sampling molecular dynamics, and high-throughput free-energy calculations. Key applications span nanoplastics impact on proteins, thermal energy storage via salt hydrates, sustainable food design with plant proteins, and inverse design of self-assembling materials including quasicrystals and zeolites. His work integrates physics-based modeling with AI to address sustainability and biomedical challenges. Scientific awards include: NWO Veni grant (2024) Personal Fellowship during PhD studies PhD cum laude distinction He actively supervises PhD researchers Eline Kempkes, Edwin Bedolla Montiel, and Chaohong Wang, alongside MSc students Lisa Roether, Filip Kopczyński, Nathanyel Schut, and Jari Hoffmann. Current projects include evolutionary algorithms for molecular simulation acceleration, small-data machine learning for reaction prediction, and protein stability analysis beyond Earth. Major funding includes the NWO Veni grant for nanoplastic risk prediction and AI4SMM initiative projects. He leads the Computational Soft Matter Lab, co-founded the Computational Science Lab, and contributes to the HIMS Diversity team and Amsterdam Young Academy (member since November 2024).

Sebastian Brandstäterمشاهده پروفایل

مدرس

• Scientific Machine Learning
• Inverse analysis & Bayesian Inference
• Uncertainty Quantification
• +۵ مورد دیگر

Dr. Sebastian Brandstäter serves as Lecturer at the Institute for Mathematics and Computer-Based Simulation, Bundeswehr University Munich since 2022. His academic trajectory includes research associate positions at Hamburg University of Technology (2021) and Technical University of Munich (2016-2021). His research focuses on: Scientific Machine Learning for biomechanical systems Uncertainty Quantification and Bayesian Inference Global Sensitivity Analysis of complex models Multi-Physics & Multi-Scale Modeling of biological tissues Open-source scientific software development Dr. Brandstäter's work centers on gastrointestinal biomechanics, particularly computational modeling of gastric electromechanics and motility. He has pioneered applications of Gaussian-process metamodelling for sensitivity analysis in vascular and gastric systems, and develops open-source frameworks (QUEENS, 4C) that enable efficient multi-query analysis of large-scale models. He actively supervises student theses on patient-specific modeling and computational biomechanics, teaches advanced numerical methods courses, and contributes to the scientific community through conference organization, peer review, and international collaborations. His recent work demonstrates increasing emphasis on data-driven surrogate modeling and solver-independent computational frameworks for biomedical applications.

Christoph Zielhoferمشاهده پروفایل

استاد

• Physical Geography
• Fluvial Geomorphology
• Soil Geography
• +۸ مورد دیگر

Christoph Zielhofer is a full Professor of Physical Geography at the Institute of Geography , affiliated with the Faculty of Physics and Earth System Sciences at Leipzig University. As Coordinator of DFG Priority Programme SPP 2361 'On the Way to the Fluvial Anthroposphere' since 2021, he leads interdisciplinary research on human-environment interactions in floodplains. His academic career includes leadership roles as Director of the Institute of Geography (2013–2020) and Study Dean (2019–2021) , with current membership in the Faculty Board since 2010. Zielhofer's research focuses on Holocene environmental dynamics Fluvial geomorphology Soil geography Paleolimnology Climate-anthropogenic tipping points He integrates geophysical field techniques (e.g., Direct Push Sensing, SH waveform inversion) with sediment analysis to reconstruct floodplain evolution, particularly in Central Europe, the Mediterranean, and Africa. His recent publications emphasize Anthroposphere formation in river systems Ceasing Neolithic land use-climate coupling Geoarchaeological methods for mass grave localization Carbon storage in peatlands Saharan dust-climate links Scientific awards include Volksbank Award for interdisciplinary PhD thesis (2002) Scientific Advisory Board Vice-Chair , Leibniz-Institut für Länderkunde (2019) LeipzigLab working group leadership (2023) His research spans from desert margins in NW Arabia to German river catchments, with fieldwork integrating drilling techniques , hydrological modeling , and multidisciplinary collaboration . Grants include DFG coordination funds for SPP 2361 and SMWK-funded historical anthroposphere studies.

Sevrine Sailleyمشاهده پروفایل

پژوهشگر

• Marine Ecosystem Modelling
• Zooplankton Dynamics
• Food-Web Modelling
• +۳ مورد دیگر

Dr. Sevrine Sailley serves as a Senior Scientist at Plymouth Marine Laboratory (PML) within the Marine System Modelling group, where she leads research on zooplankton, food-web, and higher trophic level dynamics. She additionally coordinates PML's Fisheries and Aquaculture Science to Impact Challenges and chairs the ICES Working Group on Integrative Physical-biological Ecosystem Modelling (WGIPEM), demonstrating significant leadership in marine science policy and international collaboration. Her research centers on marine ecosystem modelling with particular emphasis on: Climate change impacts on marine biodiversity and fisheries sustainability Zooplankton dynamics and food-web interactions across trophic levels Carbon and nutrient cycling processes in polar and temperate ecosystems Development of integrated methodologies bridging natural and social sciences Application of inverse modelling and plankton functional type frameworks Analysis of her publication record (2009-2021) reveals progressive focus from fundamental plankton dynamics to applied climate impact assessments, with recent work (2021) providing critical projections of fish biomass reductions in East Africa under climate change scenarios. Her research consistently employs advanced modelling techniques to address real-world marine conservation challenges while contributing to major assessments like the UK Climate Change Risk Assessment. Dr. Sailley actively participates in funded research projects including CS-NOW and the UK 4th Climate Change Risk Assessment, which support her work in ecosystem dynamics and climate impacts. While specific student mentoring details aren't documented, her senior scientist role at PML suggests involvement in training early-career researchers through collaborative projects and institutional supervision frameworks. Her leadership in ICES WGIPEM facilitates international research coordination and methodological standardization across marine ecosystem modelling communities. Within PML's Marine System Modelling group, Dr. Sailley drives research on higher trophic level processes, integrating her expertise in zooplankton dynamics with broader ecosystem analyses. Her work connects laboratory-based modelling with field observations to enhance predictive capabilities for marine ecosystem responses to environmental change, supporting PML's mission in advancing marine science for societal benefit.

Markus Reichsteinمشاهده پروفایل

استاد

• Ecosystem response to climate variability
• Climate extremes and ecosystem resilience
• Artificial intelligence in Earth system science
• +۴ مورد دیگر

Prof. Dr. Markus Reichstein serves as Director of the Department of Biogeochemical Integration at the Max Planck Institute for Biogeochemistry and Professor of Global Geoecology at Friedrich Schiller University Jena. He is Founding Director of both the Michael Stifel Center Jena for Data-Driven and Simulation Sciences and the ELLIS Unit Jena, positioning him at the forefront of integrating artificial intelligence with Earth system science. His research focuses on understanding ecosystem responses to climate variability from an Earth system perspective, with particular emphasis on climate extremes and ecosystem resilience. Prof. Reichstein combines artificial intelligence with systems modeling approaches to analyze experimental data, ground-based observations, and satellite Earth observations across multiple spatial scales. His recent publication record shows a strong emphasis on applying machine learning to biogeochemical processes, with numerous 2025 publications addressing carbon cycle modeling, soil moisture prediction, drought impacts, and AI applications for climate risk assessment. These works demonstrate his interdisciplinary approach that bridges ecology, climate science, and computational methods. Piers J. Sellers Mid-Career Award from the American Geophysical Union (2018) ERC Synergy Grant (2019) Gottfried Wilhelm Leibniz Prize (2020) AGU Fellow (2025) As department director and through his various leadership roles, Prof. Reichstein oversees substantial research funding and mentorship opportunities. His department regularly welcomes new researchers and students, fostering an environment of international collaboration. The integration of the Michael Stifel Center and ELLIS Unit with his department creates unique opportunities for students interested in the intersection of AI and environmental science. The Department of Biogeochemical Integration, under Prof. Reichstein's leadership, serves as a hub for innovative research on Earth system processes, combining traditional ecological approaches with cutting-edge computational methods to address pressing climate challenges.

• Polymer Science
• Surface Science
• Nanotechnology
• +۳ مورد دیگر

Professor Manfred Stamm is a leading polymer scientist at the Leibniz Institute for Polymer Research Dresden (IPF), with a distinguished career spanning fundamental and applied research in polymer surface phenomena and nanotechnology. His work bridges theoretical modeling and experimental innovation across multiple DFG-funded initiatives. Core research domains include: Polymer surface modification and wetting dynamics Switchable interfaces using photochemical and gradient-functionalized brushes Nanoscale fabrication via block copolymer self-assembly Adhesion science linking nanoscopic interphases to macroscopic behavior Functional materials for lithium-sulfur batteries and biomedical applications Professor Stamm has directed over 20 major DFG projects including Priority Programs, Collaborative Research Centers, and International Networks. His work demonstrates consistent interdisciplinary impact—from foundational studies of polyelectrolyte conformations to applied developments like strength-optimized textile preforms and 'inverse switching' hydrogel coatings. Though all listed projects are now completed, his methodologies continue influencing responsive materials design. His research legacy features significant international collaboration, particularly through Materials World Networks, with applications spanning energy storage, microfluidics, and biomaterials. The absence of current DFG projects reflects typical late-career transition patterns rather than diminished scientific relevance.

Johannes Fürstمشاهده پروفایل

استاد

• Glaciology
• Ice Sheet Modeling
• Glacier Dynamics
• +۶ مورد دیگر

Dr. Johannes Fürst is a Professor in the Department of Geography and Geosciences at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where he conducts research in glaciology and ice sheet modeling. He is based at the Institute of Geography in Erlangen, Germany, with office in Room 02.121 at Wetterkreuz 15. His research focuses on four main areas: reconstruction of glacier thickness on Svalbard, data assimilation using ice flow models on ice sheet scales, effects of the ice shelf support effect on Antarctic outlet glaciers, and ice-dynamic influences on the volume development of the Greenland ice sheet. His work bridges theoretical glaciology with practical applications for understanding climate change impacts on the cryosphere. Prof. Fürst's recent publications (2023-2025) demonstrate expertise across multiple glacial environments including Antarctica, Greenland, Patagonia, Svalbard, and the European Alps. His research combines numerical modeling with remote sensing data to study glacier dynamics, ice thickness reconstruction, and climate-glacier interactions. Notable recent work includes development of a Kalman filter-based framework for assimilating remote sensing observations, studies on Patagonian icefields, and reconstruction of Antarctic Peninsula ice thickness. His scientific approach integrates multiple methodologies including advanced ice flow modeling, data assimilation techniques, deep learning applications for glacier monitoring, and mechanical modeling of permafrost-glacier systems. This interdisciplinary approach allows him to address complex questions about glacier response to climate change across different spatial and temporal scales.

Yan Sunمشاهده پروفایل

استاد

• Topological Materials
• Condensed Matter Physics
• Electromagnetic Response Theory
• +۵ مورد دیگر

Yan Sun is Professor at the University of Tennessee, Knoxville and leads the Topological Transport Theory group at the Max Planck Institute for Chemical Physics of Solids (MPI CPfS) in Dresden. His research bridges electromagnetic response theory, symmetry principles, and topology to predict novel transport phenomena in quantum materials, with emphasis on experimental realization through collaborations. Research Interests: Sun investigates symmetry-forbidden transport effects in topological systems, including anomalous Hall/Nernst effects, spin Hall phenomena, magnetoresistances, and higher-order responses like second-order Hall effects and giant photovoltaic effects. His group combines model Hamiltonians with density functional theory to connect fundamental physics with material properties, focusing on magnetic Weyl semimetals and topological catalysts. Publication Trends: Recent works demonstrate expertise in topological insulators/semimetals, with 2018–2015 publications emphasizing Berry curvature engineering, symmetry-protected states, and prediction of materials for spintronics applications. Research consistently targets transport anomalies arising from topological charge and magnetism. Scientific Awards: None mentioned in source text. Advising and Collaborations: Leads active MPI CPfS group with current members Yang Zhang (Visiting Scientist) and Jonathan Noky (Research Technician), plus former member Quinan Xu. Maintains extensive experimental partnership with Claudia Felser’s group on topological/magnetic materials for spintronics, catalysis, and surface-state characterization. Labs and Teams: Directs the Topological Transport Theory group within MPI CPfS’s Topological Quantum Chemistry department, focusing on database development for inversion-symmetry-broken Weyl semimetals and nonlinear optical responses. Research integrates theoretical modeling with experimental validation to realize predicted quantum phenomena.

Markus Münzenbergمشاهده پروفایل

استاد

• Ultrafast Magnetism
• THz Spintronics
• Spin Transport
• +۸ مورد دیگر

Prof. Dr. Markus Münzenberg is a leading researcher at the Institute of Physics, University of Greifswald , focusing on ultrafast magnetism and THz spintronics . His work bridges quantum physics, nanotechnology, and interdisciplinary applications , including neuronal networks and topological systems. Research Focus: Ultrafast spin dynamics, THz spintronic emitters, magnetic skyrmions, spin-caloric transport, and 3D nanostructuring via laser lithography. Labs & Facilities: Equipped with metal MBE/sputtering, cleanroom lithography (Nanoscribe, e-beam), THz pump-probe setups, and Kerr microscopy for domain imaging. Publication Trends highlight expertise in femtosecond laser interactions , spin-orbit coupling , and topological magnetic phenomena . Key subfields include attosecond magnetism , neuromorphic computing , and bio-nano interfaces . Scientific Awards & Projects: ERC FET-Open SpinAge consortium DFG SPP2137 Skyrmionics program DAAD-PPP collaboration with Charles University Prague BMBF-funded ZIK-HIKE center for bio-nanomechanical systems Collaborations span institutions like MIT, Max Planck Institutes, TU Graz, and Kiel University, with emphasis on theoretical/experimental synergy in spin dynamics and quantum materials.

René Schenkendorfمشاهده پروفایل

استاد

• Process Systems Engineering
• Uncertainty Analysis
• System Identification
• +۴ مورد دیگر

Prof. Dr. René Schenkendorf is a Professor and head of the Process Systems Engineering group at the Institute of Energy and Process Systems Engineering, Braunschweig University of Technology. He has held this position since 2016, following research roles at the German Aerospace Center (2013-2016) and PhD studies at the Max Planck Institute for Dynamics of Complex Technical Systems (2007-2012). His academic credentials include: Dipl.-Ing. in Engineering Cybernetics, Otto-von-Guericke-University Magdeburg (2007) Dr.-Ing. in Engineering Cybernetics, Otto-von-Guericke-University Magdeburg (2014) Prof. Schenkendorf's research centers on data-driven process engineering, with core expertise in Uncertainty Analysis, System Identification, and Design of Experiments. He pioneers hybrid methodologies merging Physics-Informed Neural Networks with traditional modeling to solve industrial challenges in manufacturing, sustainable energy, and pharmaceutical synthesis. His work emphasizes practical implementation of digital twins and statistical process control for real-world optimization. Recent publications (2021-2024) reveal a strategic shift toward AI-integrated process engineering, particularly in physics-informed machine learning for parameter identification and model inversion. This trend underscores his commitment to bridging theoretical uncertainty quantification with industrial applications like sustainable aviation fuel production. As leader of the Process Systems Engineering group, he directs research advancing data-centric methodologies for process control and optimization. His active publication record indicates ongoing supervision of graduate students and successful grant acquisition in process systems engineering, though specific project details remain undisclosed in the source material.

Miriam Primbsمشاهده پروفایل

استاد

• Applied Mathematics
• Numerical Methods
• Mathematical Simulation
• +۴ مورد دیگر

Professor Miriam Primbs is a faculty member at Hochschule Ruhr West (HRW) in the Institute of Natural Sciences, where she teaches Mathematics and Simulation. She has been a professor at HRW since 2011 and coordinates the HRW research focus MARTA since 2022. Professor Primbs studied Mathematics and Physics (Diplom and 1. Staatsexamen) and earned her PhD in Mathematics at the University of Duisburg-Essen. Her career includes a research stay at IMATI CNR in Italy, teaching on the school ship Thor Heyerdahl, and working in Research and Development at Siemens Energy Mülheim before joining HRW. This blend of academic and industry experience informs her teaching and research approach. Her research focuses on applying mathematical and numerical methods to technical problems across engineering disciplines, from mechanics to electrical engineering. As coordinator of the MARTA research focus, she leads various projects including those funded by BMBF and collaborations with industry partners like Siemens Energy. Her scholarly work spans wavelet analysis, numerical methods, signal processing, and power systems analysis. Professor Primbs teaches Engineering Mathematics I and II, Mathematics for E-Commerce, MATLAB, Scientific Simulation, and LaTeX Basics. She employs a flipped classroom approach for foundational courses, providing students with tailored materials and prompt feedback through weekly exercises. In higher semesters, she emphasizes project-based learning and specialized topics. Currently supervising doctoral student Martin Wachs in cooperation with University of Duisburg-Essen Member of the Senate Committee for Research and Transfer at HRW Encourages industry collaboration for practical research applications Professor Primbs maintains strong connections between academic research and industrial applications, leveraging her Siemens Energy experience to bridge theory and practice in mathematical engineering.

Carleen Reijmerمشاهده پروفایل

استادیار

• Climate Science
• Glaciology
• Polar Meteorology
• +۷ مورد دیگر

Carleen Reijmer is an Assistant Professor in the Department of Physics and Astronomy at Utrecht University's Faculty of Science, where she conducts research through the Institute for Marine and Atmospheric Research (IMAU). She is an active member of Michiel Roland Van den Broeke's research group, focusing on polar climate processes and ice sheet dynamics. Dr. Reijmer's research interests center on polar meteorology, ice sheet modeling, and climate change impacts on polar regions. Her work combines field observations from automatic weather stations across Antarctica and Greenland with sophisticated numerical modeling, particularly using the RACMO2 regional climate model. She has made significant contributions to understanding surface energy balance, snow-albedo feedback mechanisms, and turbulent fluxes over ice sheets. Her publication record shows a consistent focus on quantifying surface melt processes, ice sheet mass balance, and the response of polar regions to global warming. The research demonstrates strong interdisciplinary connections between meteorology, glaciology, and climate science, with particular emphasis on how atmospheric processes influence ice sheet behavior. With 159 publications and over 7,500 citations, Dr. Reijmer has established herself as a significant contributor to polar climate research. Her work provides critical insights into how polar ice sheets contribute to sea level rise and how these regions are responding to ongoing climate change. Dr. Reijmer actively collaborates with researchers across international institutions and has contributed to major polar research initiatives. Her work involves both field campaigns deploying automatic weather stations and advanced modeling approaches to understand the complex interactions between atmosphere and ice in polar regions.

• Nuclear Physics
• Heavy Ion Research
• Nuclear Structure
• +۳ مورد دیگر

Dr. Janik R. is a nuclear physics researcher at GSI Helmholtzzentrum für Schwerionenforschung GmbH in Darmstadt, Germany, actively involved in cutting-edge research on nuclear structure with a focus on exotic nuclei far from stability. Their work primarily centers on investigating shell evolution, shape transitions, and nuclear collectivity in neutron-rich and proton-rich isotopes using advanced gamma-ray spectroscopy techniques and lifetime measurements. Dr. Janik R.'s research interests span nuclear structure physics, with particular emphasis on shell evolution in exotic nuclei, nuclear spectroscopy of rare isotopes, beta-decay studies, and the investigation of traditional and new shell closures. Their work often involves international collaborations and utilizes major facilities including GSI/FAIR, RIKEN's RIBF, and connections to CERN's ISOLDE facility. Their publication record shows significant contributions to understanding nuclear structure phenomena, particularly in regions near shell closures such as N=32, N=40, and N=126. Recent work includes spectroscopy of exotic potassium and calcium isotopes, studies of shape transitions in rare earth nuclei like tungsten-190, and investigations of nuclear structure in proton-rich systems such as palladium-94. Dr. Janik R. is actively involved in experimental nuclear physics instrumentation development, contributing to detector systems like FATIMA (FAst TIMing Array) for lifetime measurements and STRASSE (Silicon Tracker for RAdioactive nuclei Studies at SAMURAI Experiments) for quasi-free scattering measurements. Their work supports the DESPEC experiment at FAIR Phase-0, which serves as a precursor to the full FAIR facility. Research areas include: Nuclear structure of exotic nuclei Shell evolution and new magic numbers Gamma-ray spectroscopy techniques Lifetime measurements of nuclear excited states Beta-decay studies of neutron-rich nuclei Shape transitions and collectivity in atomic nuclei

• Nuclear Physics
• Atomic Physics

Y. M. Volkov is a researcher at GSI Helmholtzzentrum für Schwerionenforschung, specializing in experimental nuclear physics. Volkov's work focuses on investigating nuclear properties of isotopes, particularly copper nuclei, using advanced measurement techniques. Research interests include: Nuclear structure and spectroscopy Magnetic moment measurements Isotopic behavior studies Energy level configurations in atomic nuclei In a notable 2009 publication in Physical Review Letters , Volkov contributed to research revealing unexpected level inversion in copper-75 isotopes, advancing understanding of nuclear shell models.