جست‌وجوی استاد و پژوهشگر

• Numerical Analysis
• Sparse Grids
• Machine Learning
• +۳ مورد دیگر

Prof. Dr. Michael Griebel is a leading academic at the Institute for Numerical Simulation (INS) at the University of Bonn , Germany. His work focuses on numerical methods for partial differential equations (PDEs), sparse grid techniques, and applications in computational science, machine learning, and materials modeling. Research Interests : Numerical analysis, sparse grids, high-dimensional approximation, tensor product methods, stochastic processes, and multiscale simulations. Collaborations : Co-author of over 50 publications with researchers in computational mathematics, fluid dynamics, and quantum chemistry. Prominent research trends include advancements in sparse grid methods for uncertainty quantification, kernel-based regression, and efficient solvers for ill-posed problems. His work on space-filling curves and domain decomposition enables scalable parallel algorithms for complex simulations. Scientific Contributions : Editor of 10+ volumes in Lecture Notes in Computational Science and Engineering . Co-developer of the EXAHD exascale sparse grid framework for plasma physics simulations. Foundational work on tensor product spaces and their applications to electronic structure theory. Innovations in adaptive wavelet solvers and parallel multigrid methods. Software and Projects : Key developer of sparse grid solvers and adaptive algorithms. His INS Preprint Series archives over 200 technical reports, reflecting his group’s impact on computational methods.

Artemis Alexiadouمشاهده پروفایل

استاد

• Syntax
• Morphology
• Syntax and its interfaces with morphology
• +۵ مورد دیگر

Professor Artemis Alexiadou is a distinguished linguist serving as Director of the Leibniz-Centre General Linguistics (ZAS) and holding an S-Professorship in General Linguistics at the Institute of German Language and Linguistics, Humboldt University of Berlin. She has been affiliated with ZAS and the Institute of German Language and Linguistics since October 1, 2022. Her academic journey began with a degree in Philology specializing in Linguistics from the University of Athens (1986-1990), followed by an MA in Linguistics from the University of Reading (1990-1991), and culminated in a Ph.D. in Linguistics from Universität Potsdam (1994). Professor Alexiadou's research focuses on theoretical syntax and morphology, with particular expertise in syntax and its interfaces with morphology, the lexicon and interpretation, Diachronic Syntax, Language Breakdown and Development, and Heritage Languages. Her work has significantly advanced our understanding of nominalization, verbal alternations, and the syntax-morphology interface. She has held prestigious positions including Professor of Theoretical and English Linguistics at the University of Stuttgart (2002-2015) before moving to Humboldt University. Her recent publications reveal a strong emphasis on Heritage Greek linguistics, examining phenomena such as gender agreement, aspect, and the plural indefinite article across different registers. The publication trends indicate a growing focus on experimental and comparative approaches to heritage language phenomena, particularly in the Greek diaspora communities in the USA and Germany. This reflects her leadership in the Research Unit on (Experimental) Syntax and Heritage Languages (RUESHeL). Gottfried Wilhelm Leibniz Prize (2014) Doctor honoris causa from the Norwegian University of Science and Technology (2016) Member of the Leopoldina, National Academy of Sciences (2014) Member of the Norwegian Academy of Science and Letters (2018) ERC Synergy Grant LeibnizDream (2021-2026) Professor Alexiadou has supervised numerous research projects and currently leads the ERC Synergy Grant LeibnizDream project, which investigates how language compresses thought structures. She serves on multiple scientific boards including the International Research Network Heritage Languages in Europe and the DFG Review Board 104 Sprachwissenschaften. Her editorial work includes membership on the boards of Glossa, Linguistic Inquiry, and Syntax, among others. She directs the Compressor Team at Humboldt University, which focuses on language acquisition and processing.

• Construction Grammar
• Usage-Based Morphology
• Cognitive Linguistics
• +۴ مورد دیگر

Dr. Robert Daugs is a Lecturer and post-doctoral researcher at the Department of English and American Studies, Kiel University. His research bridges cognitive-functional linguistics with empirical methodologies, focusing on construction grammar, usage-based morphology, and corpus-driven analysis of modality. Research Focus: Cognitive linguistics, constructional change, corpus analysis Teaching: Empirical approaches to English language structure Contact: daugs@anglistik.uni-kiel.de Daugs’ work explores how usage patterns shape linguistic systems diachronically, particularly in modal expressions and morphological constructions. His recent projects include compiling a Northern California English corpus and modeling pragmatic associations. Scientific contributions include studies on privative prefixes (near-, pseudo-), hella-intensification dynamics, and modal contraction processing. Notable awards include the 2019 John Sinclair Bursary for outstanding PhD candidate research. Current teaching topics include Usage-Based Morphology, Construction Grammar, and Academic Skills training. His research emphasizes methodological coherence through corpus linguistics across courses.

Thomas Vogelمشاهده پروفایل

استاد

• Differential Geometry
• Topology
• Contact Geometry
• +۴ مورد دیگر

Thomas Vogel is a Professor at the Mathematical Institute of Ludwig Maximilian University of Munich, where he leads the Differential Geometry and Topology working group. His research focuses on geometric structures in low-dimensional topology, including Engel structures, contact geometry, and foliation theory. Vogel teaches courses across various mathematical disciplines including linear algebra, differential geometry, topology, and symplectic geometry. His research explores the existence and classification of geometric structures on manifolds, with particular emphasis on Engel structures and their relationship to contact geometry. Vogel's work combines topological methods with differential geometric techniques to study rigidity and flexibility properties of geometric structures in dimensions three and four. Vogel's publications demonstrate consistent focus on geometric topology and differential systems, with recent work exploring connections between Engel structures, open book decompositions, and knot theory. His articles frequently appear in top-tier mathematics journals including Annals of Mathematics, Geometry & Topology, and Communications in Mathematical Helvetica. He actively organizes seminars and reading courses on advanced mathematical topics including Morse theory, knot theory, representation theory, and the h-cobordism theorem. Vogel maintains regular office hours and coordinates multiple teaching activities within the mathematics curriculum.

• Stochastic Processes
• Statistical Mechanics
• Quantum Systems
• +۴ مورد دیگر

Prof. Dr. Sabine Jansen is a faculty member at the Mathematical Institute of Ludwig Maximilian University of Munich (LMU) . Her research focuses on stochastic processes, statistical mechanics, and quantum systems, particularly through her work in cluster expansions, Gibbs measures, and random geometric systems. She is affiliated with the Working Group on Stochastics and Financial Mathematics and participates in the DFG Collaborative Research Center CRC TRR 352 ( Mathematics of many-body quantum systems and their collective phenomena ) and the DFG priority program SPP2265 ( Random Geometric Systems ). Her office is located at Theresienstr. 39, 80333 Munich (Room 214, Block B, 2nd floor), and she can be contacted at Sabine.Jansen@math.lmu.de or jansen@math.lmu.de . Key Research Areas : Stochastic processes, cluster expansions, quantum statistical mechanics, many-body systems, and probabilistic methods in mathematical physics. Notable Collaborations : DFG-funded projects (CRC TRR 352, SPP2265), Munich Center for Quantum Science and Technology (MCQST), and international collaborations with institutions like Leiden University. Publications : Recent work includes studies on large deviations, intertwinings for continuum systems, virial inversion, and combinatorial approaches to generating functions. Labs & Teams : Leads the Stochastics and Financial Mathematics working group, contributing to quantum systems research at LMU and MCQST.

Philipp Mertschمشاهده پروفایل

استاد

• Astrophysics
• Cosmic Ray Physics
• High-Energy Astronomy
• +۳ مورد دیگر

Philipp Mertsch is a Professor at the Institute for Theoretical Physics and Cosmology (TTK) at RWTH Aachen University in Germany. He leads a research group focused on astrophysics, particularly cosmic rays, galactic structure, and high-energy phenomena. His work involves collaborations with institutions like the Max Planck Institute for Astrophysics (MPA Graching), GSSI L'Aquila, and others across Europe. Professor Mertsch's research interests span multiple areas of astrophysics and cosmic ray physics. His work focuses on understanding the origin and propagation of cosmic rays in the Galaxy, the structure of the interstellar medium, and high-energy phenomena. He employs advanced computational techniques including Bayesian inference and information field theory to analyze complex astrophysical data. His group is particularly known for work on 3D reconstructions of galactic gas, cosmic ray anisotropies, and modeling of high-energy neutrino emissions. His recent publications show a strong focus on galactic astrophysics, particularly on cosmic ray physics, 3D mapping of the Milky Way, and high-energy phenomena. There's a clear trend toward increasingly sophisticated modeling techniques, including Bayesian inference and information field theory. His work often bridges theoretical predictions with observational data from instruments like AMS-02, IceCube, and Fermi-LAT. ERC Synergy Grant (2024) for project "mw-atlas" to construct a 3D atlas of the Milky Way Professor Mertsch has supervised several PhD students including Marco Kuhlen who successfully defended his thesis. He leads the GaGaDiCT research group which focuses on galactic gamma-ray and cosmic-ray physics. His group has received significant funding including the ERC Synergy Grant. The GaGaDiCT group maintains active collaborations with researchers across Europe and runs regular workshops like the GaGaDiCT workshop 2024. They're involved in multiple international projects and have a strong presence at major conferences like the International Cosmic Ray Conference.

• Formal Methods
• Safety-Critical Systems
• Probabilistic Verification
• +۴ مورد دیگر

Sebastian Junges is an Assistant Professor in the Software Science Group at Radboud University, Nijmegen, since 2021. He holds a PhD in Computer Science from RWTH Aachen University (2020), and previously worked as a PostDoc at UC Berkeley (2020-2021) and a Research Assistant at RWTH Aachen (2015-2020). His research focuses on formal methods for analyzing safety-critical systems, particularly using extensions of Markov decision processes (MDPs) to ensure dependability in automated systems like network protocols, hardware architectures, and robotics. Education: PhD in Computer Science, RWTH Aachen University, 2020 M.Sc. in Computer Science, RWTH Aachen University, 2015 B.Sc. in Computer Science, RWTH Aachen University, 2012 His research interests include probabilistic verification, policy synthesis for MDPs, and the intersection of formal methods with artificial intelligence. He has contributed to tools like the Storm probabilistic model checker and led projects on scalable analysis of probabilistic models. His work addresses challenges like ensuring safe decision-making in autonomous systems and certifying compliance with safety standards through rigorous algorithmic approaches. Publications focus on advancing MDP analysis, POMDPs, and robust policy synthesis. Recent trends include integrating uncertainty management, decision-tree-based approaches, and compositional verification techniques. He actively contributes to conferences like CAV, AAAI, and TACAS, and serves on program committees and steering groups for formal methods and AI.

Volker Michelمشاهده پروفایل

استاد

• Geomathematics
• Inverse Problems
• Gravimetry
• +۴ مورد دیگر

Prof. Volker Michel is a Professor of Mathematics in Engineering at the Department of Mathematics, University of Siegen, leading the Geomathematics Group. He holds a PhD and habilitation from the University of Kaiserslautern. His research focuses on applying advanced mathematical techniques to geoscience problems, including inverse problems, gravimetry, and medical imaging. Michel has organized major conferences and secured numerous DFG grants. He serves as editor-in-chief of the International Journal on Geomathematics and editorial roles in other journals. Notable achievements include a prize for his PhD thesis and international collaborations with institutions like the Isaac Newton Institute and NASA's JPL. His academic leadership includes heading the Department of Mathematics at Siegen from 2014–2016. Education: Industrial Mathematics Diploma, University of Kaiserslautern (1995) PhD in Mathematics, University of Kaiserslautern (1999) Habilitation in Mathematics, University of Kaiserslautern (2002) Research Interests: Geomathematics, multiscale approximation methods, inverse problems in geosciences, medical imaging techniques, numerical analysis, and functional analysis applications. His work bridges theoretical mathematics with practical geophysical and engineering challenges, emphasizing data-driven solutions for Earth sciences. Publications: His books synthesize cutting-edge methodologies, such as Geomathematics (2022), which addresses mathematical modeling in geodesy and geophysics, and Lectures on Constructive Approximation (2013), detailing wavelet and spline techniques across domains. These works reflect his expertise in translating complex mathematical theories into applicable geoscientific frameworks. Awards and Recognition: PhD Prize from Kreissparkasse Kaiserslautern (1999) Editorial leadership in top-tier journals International collaboration recognitions Grants and Advising: Secured multiple DFG-funded projects and advised numerous theses. His research group actively engages in third-party funded initiatives focusing on geomathematical problem-solving. Labs/Teams: Founded and directs the Geomathematics Group at Siegen, a hub for interdisciplinary research in mathematical geosciences.

• Machine Learning
• Materials Science
• Computational Chemistry
• +۳ مورد دیگر

Dr. Attila Cangi is the Head of Department for Machine Learning for Materials Design at the Center for Advanced Systems Understanding (CASUS) , part of the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) . His roles include leading research in computational materials science and developing scalable ML methods for electronic structure calculations. He has held permanent staff scientist positions at HZDR and Sandia National Laboratories, with postdoctoral experience at the Max Planck Institute. His research focuses on accelerating materials discovery through AI-driven simulations for energy storage, thermoelectrics, spintronics, and semiconductor modeling. Education: Ph.D. in Chemistry (Chemical and Materials Physics), University of California, Irvine (2011) M.Sc. in Physics, Rutgers University (2006) Research Interests: Dr. Cangi’s work integrates machine learning with first-principles simulations to model electronic structures, predict material properties (e.g., conductivity, magnetism), and simulate phase transitions. His lab leverages high-performance computing to address challenges in warm dense matter, plasma physics, and quantum transport phenomena. Key areas include: Development of physics-informed ML algorithms (e.g., MALA package) Electronic structure modeling at extreme conditions Design of sustainable materials for energy applications Lab & Collaborations: The Machine Learning for Materials Design group collaborates on projects like the European XFEL and employs tools such as atoMEC for average-atom modeling. Their work bridges theory and experiment, enabling predictions for novel materials under extreme environments.

Ralf Möllerمشاهده پروفایل

استاد

• Artificial Intelligence
• Humanities-Centered AI
• Causal and Probabilistic Models
• +۵ مورد دیگر

Prof. Ralf Möller is a Professor of Artificial Intelligence in Humanities at the University of Hamburg's Faculty of Humanities, Department of Philosophy. He leads the Institute of Humanities-Centered Artificial Intelligence (CHAI) and serves as spokesperson for the 'Data Linking' research field within the Cluster of Excellence ‘Understanding Written Artefacts’ (UWA, 2019–2025). His research focuses on intellectics, causal and probabilistic-relational models, and AI applications in humanities, emphasizing sustainable data management and multimodal foundation models. He heads the Data Linking Lab and the CHAI Institute, overseeing projects like the TAMAR initiative for manuscript research. His work bridges technical AI advancements with humanities needs, addressing challenges in data curation, federated information systems, and ethical AI integration. He contributes to interdisciplinary collaborations, including ethics committees and cultural heritage preservation initiatives. Key research themes include lifted inference in probabilistic graphical models, temporal data prediction, and synergistic OCR-LLM systems for damaged documents. His projects emphasize scalability, sustainability, and human-centered design principles. Supervising doctoral candidates in AI and humanities intersections, he advocates for AI systems grounded in cultural and ethical considerations. Labs/Teams: CHAI Institute, Data Linking Lab. Current Projects: UWA Cluster (2019–2025), Data Linking Infrastructure development, Humanities-Centered AI applications. Grants include leadership roles in institutional and collaborative research funding.

Swetlana Tornoمشاهده پروفایل

پژوهشگر ارشد

• Ageing
• Mobility Studies
• Intergenerational Relations
• +۶ مورد دیگر

Dr. Swetlana Torno is a postdoctoral research fellow at the Max Planck Research Group 'Ageing in a Time of Mobility' at the Max Planck Institute for the Study of Multicultural Societies (MPI-MMG) in Göttingen, Germany. She earned her doctoral degree in Social Anthropology from Heidelberg University after studying Anthropology, Geography and Biology at the Universities of Tübingen and McGill. Prior to her current position, she was an associated member of the Heidelberg Centre for Transcultural Studies and held a doctoral scholarship at the Cluster of Excellence 'Asia and Europe in Global Context'. Dr. Torno's research focuses on ageing, mobility, intergenerational relations, care, and gender in Central Asia, with extensive ethnographic fieldwork in Tajikistan. Her work reveals how care norms shape women's life courses and mobility patterns across different life stages in Tajik society, where conservative gender roles significantly influence freedom of movement. Her current postdoctoral project investigates how mass labor migration to Russia impacts elderly mobility and care arrangements, documenting gendered differences in how older men struggle with retirement transitions while older women often experience increased freedom as caregiving responsibilities evolve. Analysis of her publications shows consistent focus on Central Asian ageing contexts with particular attention to Tajikistan's family-based care systems. Her work demonstrates how remittances from labor migration shape household economies and care practices, while new technologies like smartphones help maintain family connections across distances. Despite limited state support systems (only eight nursing homes serving approximately 1,020 people nationwide in 2016), her research reveals the resilience of extended family structures in providing care while adapting to migration pressures. Dr. Torno's scholarly contributions include significant publications in Historical Social Research, Journal of Eurasian Studies, and Problems of Post-Communism, with her forthcoming book manuscript 'Aspirations, Obligations, Linked Lives: Care and Women's Life Courses in Tajikistan' representing a major contribution to the field. Her research combines long-term ethnography with attention to how Soviet legacies continue to shape contemporary social practices, particularly regarding political discourse on women that she characterizes as 'Tajik in Content—Soviet in Form'. As an engaged scholar, Dr. Torno contributes to public discourse through interviews like her 2025 NAR seminar participation and blog posts reflecting on ageing in rural Tajikistan. Her work challenges simplistic narratives about family breakdown under migration pressures, instead documenting how families creatively adapt care practices while maintaining core values of respect for elders—a principle reinforced by both social pressure and religious obligations in Tajik society.

Steffen Winterمشاهده پروفایل

مدرس

• Fractal Geometry
• Geometric Measure Theory
• Stochastic Geometry
• +۱ مورد دیگر

Steffen Winter is a Lecturer (PD Dr.) at the Institute of Stochastics, Karlsruhe Institute of Technology (KIT). His research specializes in Fractal Geometry, Geometric Measure Theory, Stochastic Geometry, and Dynamical Systems. He leads the DFG-funded project Scaling of curvature measures and the modified Weyl-Berry conjecture and serves as Principal Investigator for project 12 ( Morphometric Roughness of Nanostructured Surfaces ) within the DFG Priority Programme 2265 (Random Geometric Systems). Winter's work explores the mathematical foundations of fractals, stochastic processes, and geometric measurements. Key themes include Minkowski content, curvature measures, self-similar sets, percolation models, and applications to materials science and geoscience. Recent publications emphasize fractal dimensionality, surface roughness quantification, and stochastic convergence in complex systems. He teaches advanced courses including Stochastic Geometry , Fractal Geometry , and Markov Chains , and mentors students through seminars and proseminars. No awards or research grants besides DFG projects are documented.

In Young Minمشاهده پروفایل

مدرس

• International Relations
• Security Studies
• East Asian Politics
• +۳ مورد دیگر

In Young Min is a Lecturer in Korean studies at the Centre for East Asian Studies, Heidelberg University. He holds a B.A. and M.A. in Political Science from Yonsei University (South Korea), and a Ph.D. in Political Science and International Relations from the University of Southern California. His research focuses on international relations and security in East Asia, particularly the dynamics of power asymmetry and smaller states' agency in shaping these dynamics, with a regional focus on Korea. Recent work examines historical and contemporary issues surrounding the Korean Peninsula, including nuclear policy and unification treaties. His interdisciplinary contributions span political theory and historical analysis. Education History: B.A. and M.A. in Political Science, Yonsei University, South Korea Ph.D. in Political Science and International Relations, University of Southern California Research Interests: Power asymmetry dynamics in international relations Ontological security and identity in hierarchical systems Korean Peninsula security and unification South Korea's nuclear policy and non-proliferation challenges Publications Trends: His work bridges historical and contemporary analyses, with contributions to journals like the International Relations of the Asia-Pacific and Journal of Asian Security and International Affairs . Earlier technical articles in mathematics and computational methods reflect interdisciplinary engagement, though recent focus is on political science and international relations.

• Statistical Relational Artificial Intelligence
• Human-aware AI
• Explainable AI
• +۱۲ مورد دیگر

Tanya Braun is a Junior Professor in the Institute of Computer Science at the University of Münster, Department of Mathematics and Computer Science. She leads the Data Science research group, focusing on statistical-relational AI, human-aware AI, and text understanding. Her work bridges formal AI methods with real-world applications in healthcare, digital humanities, and public sector systems. Education: Bachelor's and Master's in Computational Informatics, Hamburg University of Technology Doctorate in Computer Science, University of Lübeck (2020), thesis: 'Rescued from a Sea of Queries - Exact Inference in Probabilistic Relational Models' Her research centers on probabilistic inference in relational domains , with a focus on lifted inference techniques that exploit symmetries to scale reasoning. She investigates human-aware AI , particularly how AI systems can reconcile learned models with human expectations to improve explainability and trust. Her work on text understanding addresses challenges in data-scarce settings such as digital humanities, where traditional large language models fail. She has developed methods for identifying and enriching subjective content descriptions, topic modeling in specialized domains, and feedback-driven model improvement. The 15 most recent publications highlight a strong trajectory in lifted inference, model compression, privacy-preserving AI, and explainability . Her work integrates formal AI foundations with practical concerns in high-stakes domains like healthcare. She frequently publishes in top venues such as AAAI, IJCAI, ECAI, and Artificial Intelligence, often in collaboration with Ralf Möller, Marcel Gehrke, and Jan Speller. Scientific Awards: No specific awards listed in the provided text. Tanya Braun actively advises students and leads the HAPPI project, which focuses on human-AI model reconciliation using lifted probabilistic inference. She has supervised multiple theses and mentored researchers including Jan Speller (PostDoc), Nazlı Nur Karabulut, and Sagad Hamid. She has secured funding from the Ministry of Culture and Science of North Rhine-Westphalia for her research. She is deeply involved in academic service: serving as program co-chair for KI 2025, guest-editing special issues in journals like Künstliche Intelligenz and Annals of Mathematics and Artificial Intelligence , and organizing major conferences including ICCS and KR. Labs and Teams: She leads the Data Science Group at the University of Münster, which conducts research in AI, probabilistic modeling, and data science. The group is actively involved in teaching and mentoring students in advanced AI topics.

Tamara Gravaمشاهده پروفایل

دانشیار

• Integrable systems
• Nonlinear waves
• Random matrix theory
• +۵ مورد دیگر

Tamara Grava is an Associate Professor at the International School for Advanced Studies (SISSA) in Trieste, Italy, and a Professor at the University of Bristol, UK. Her research focuses on mathematical physics, particularly integrable systems, nonlinear waves, and random matrix theory. She maintains active collaborations between these two prestigious institutions, contributing significantly to both theoretical developments and interdisciplinary applications. Her educational background includes a PhD in Mathematical Physics from SISSA, completed on October 5, 1998, with a thesis titled "On the Cauchy problem for the Whitham equations" under the supervision of Boris Dubrovin. Professor Grava's research spans several interconnected areas in mathematical physics. She investigates integrable systems with random initial data, developing probabilistic Riemann-Hilbert methods to analyze soliton gases and their connections to statistical mechanics. Her work on dispersive nonlinear partial differential equations examines long-time and small-dispersion asymptotics, with particular attention to dispersive shock waves and rogue waves. She also makes significant contributions to random matrix theory, studying special functions, orthogonal polynomials, and their connections to Painlevé equations. Her research often bridges pure mathematics with applications in physics, revealing deep connections between seemingly disparate fields. Analysis of Professor Grava's recent publications (2021-2024) reveals a strong focus on the intersection of integrable systems, random matrix theory, and nonlinear wave phenomena. Her work increasingly explores soliton gases and their statistical properties, connecting microscopic soliton dynamics to macroscopic hydrodynamic descriptions. There's a clear progression toward more complex systems involving random initial conditions and the development of rigorous mathematical frameworks to handle these problems. Her research shows strong interdisciplinary connections between mathematical physics, statistical mechanics, and quantum field theory. Professor Grava actively supervises PhD students including Sacha Grover (Bristol), Dmitrii Rachenkov (SISSA), Xiao-Fan Zhang, Xiaodong Zhu, and Zechuan Zhang. Her editorial work includes service on the boards of Nonlinearity (since 2012), SIAM Journal of Mathematical Analysis (since 2022), Constructive Approximation (since 2023), and the Bulletin and Journal of the London Mathematical Society (starting 2025). She participates in numerous international conferences and workshops, with upcoming engagements in 2025 including events on enumerative combinatorics, integrable systems, and statistical physics at institutions including CIRM, Harvard University, and the MATRIX Institute.