جست‌وجوی استاد و پژوهشگر

Yifei Zhaoمشاهده پروفایل

پژوهشگر

• Arithmetic Geometry
• Langlands Program
• Cohomology Theories
• +۶ مورد دیگر

Dr. Yifei Zhao is an academic researcher at the Mathematical Institute , University of Münster , Germany, within the Department of Mathematics and Computer Science. His work bridges arithmetic geometry, algebraic topology, and representation theory through advanced cohomology theories and geometric Langlands program research. Position: Fixed-term Academic Councilor (Akademischer Rat auf Zeit) Contact: yifei.zhao@uni-muenster.de , +49 251 83-35172, Room 100,008 Research focuses on: Langlands Correspondences : Extending to p-adic coefficients, derived categories, and geometric unification via motivic methods Moduli Spaces : Geometry of local shtukas, étale sheaves, and their cohomological properties Topological Recursion : Connections to free probability and Baker–Akhiezer kernels Cohomology Theories : Unifying étale, crystalline, and de Rham cohomology in mixed characteristics His current projects include CRC 1442 A05/D03 and EXC 2044 A1 , with publications in journals like Compositio Mathematica and Journal of the European Mathematical Society . Collaborators include James Tao and Luozi Shi. Detailed lecture notes on scheme theory and geometric Langlands are available from his courses and winter school contributions.

• Quantum Information and Computation
• Quantum Many-Body Systems
• Tensor Networks
• +۷ مورد دیگر

Professor Norbert Schuch is a full Professor of Physics and Mathematics at the University of Vienna, where he leads the Research Group "Quantum Information and Quantum Many-Body Physics" at both the Faculty of Physics and Faculty of Mathematics. He joined the University of Vienna in October 2020 after serving as a tenured Research Group Leader at the Max-Planck-Institute of Quantum Optics in Garching, Germany and as a Lecturer at the Technical University Munich. Prior to that, he held a Tenure-Track-Professor position at the Institute for Quantum Information at RWTH Aachen University. Professor Schuch's research focuses at the intersection of Quantum Information and Computation with the Physics of Complex Quantum Many-Body Systems. His work combines mathematical, physical, and computational approaches to understand quantum correlations in many-body systems. Key research areas include tensor networks (such as Matrix Product States and Projected Entangled Pair States), topological order, entanglement theory, quantum algorithms, and quantum complexity theory. His interdisciplinary approach integrates methods from physics, mathematics, and theoretical computer science to address fundamental questions about quantum systems. His recent publications show a continued focus on tensor network theory and applications, with particular emphasis on topological phases, entanglement structure, quantum algorithms, and computational aspects of quantum many-body systems. His work spans mathematical foundations, physical applications, and computational implementations, demonstrating the cross-disciplinary nature of his research program. As an educator, Professor Schuch teaches courses on Quantum Information, Quantum Computing, and Quantum Algorithms, as well as specialized topics like Entanglement in Quantum Many-Body Systems. He actively supervises PhD students, postdocs, and master's students in his research group, which maintains strong connections with the international quantum information community.

Antoine Tilloyمشاهده پروفایل

پژوهشگر

• Quantum Field Theory
• Tensor Networks
• Quantum Foundations
• +۴ مورد دیگر

Antoine Tilloy is a researcher at Mines Paris – PSL 's Centre Automatique et Systèmes , affiliated with the Quantic group (a joint venture with Inria Paris, ENS Paris, and Mines Paris). He focuses on the intersection of quantum field theory and tensor networks , particularly relativistic continuous matrix product states (RCMPS) for solving non-perturbative QFT problems. His work emphasizes rigorous numerical methods and their competitiveness with lattice gauge theory approaches. His research includes: ERC-funded projects on tensor networks in quantum field theory Collaborative work with Clément Delcamp on tensor renormalization Comparative studies of quantum computing, tensor networks, and Monte-Carlo methods for QCD He actively participates in academic outreach through blog posts, teaching assistant roles, and postdoc/PhD recruitment. His technical advancements aim to improve error scaling in variational optimization algorithms while addressing the limitations of structured versus unstructured approaches in theoretical physics.

Erez Zoharمشاهده پروفایل

دانشیار

• Quantum Many-Body Theories
• Quantum Information
• Quantum Optics
• +۴ مورد دیگر

Dr. Erez Zohar is an Associate Professor at the Racah Institute of Physics, Hebrew University of Jerusalem, Israel. His research focuses on the intersection of quantum many-body theories, quantum information, and quantum optics, particularly addressing challenges in strongly correlated systems and their applications to particle physics. In 2025, he will transition to the School of Physics and Astronomy at Tel Aviv University. Education: BSc in Physics and Mathematics, Tel Aviv University (2009) Doctoral research at Tel Aviv University under Prof. Benni Reznik Dr. Zohar works on developing novel tools for quantum simulation of lattice gauge theories, combining tensor network states with Monte Carlo methods to tackle non-perturbative problems in high energy physics. His research includes constructing gauge-invariant tensor networks with fermionic matter fields and mapping high-energy physics models to laboratory-controllable systems. His recent publications focus on quantum simulation of non-Abelian gauge theories, truncation-free QED simulations with Josephson arrays, and advancements in fermionic PEPS for gauge theories. The work demonstrates expertise in tensor networks, quantum field theory, and quantum computing applications. Scientific Awards: ERC Consolidator Grant (2023) for the OverSign project Adams Fellowship (during PhD at Tel Aviv University) Dr. Zohar's research program aims to reconstruct physical theories from fundamental components, revealing new perspectives in quantum field theory and enabling experimental approaches to previously inaccessible systems. His group's methodology combines theoretical innovation with practical quantum simulation design.

• Psychometrics
• Event-Related Potentials
• Structural Equation Modeling
• +۳ مورد دیگر

Kim-Laura Speck is a Researcher (PhD student) in the Psychological Research Methods group at the University of Kassel, Germany, holding this position since April 2022. Her academic qualifications include: M.Sc. Psychology from the University of Leipzig (2018-2022) B.Sc. Psychology from the University of Potsdam (2014-2018) Her research centers on advanced quantitative methodologies in psychological data analysis, with emphasis on measurement invariance violations in structural equation modeling for event-related potentials (ERP), tensor decompositions for psychological datasets, and latency shift consequences in exploratory factor analyses. She investigates item-versus-composite prediction superiority and methodological refinements for ERP data interpretation. She operates within the Psychological Research Methods team at the University of Kassel under Prof. Dr. Florian Scharf's supervision, utilizing facilities at Dutch Street 36-38, Room 1203 in Kassel.

• Quantum Computing
• Quantum Foundations
• Diagrammatic Reasoning
• +۳ مورد دیگر

John van de Wetering is an Assistant Professor at the Theoretical Computer Science group of the Informatics Institute at the University of Amsterdam . He works with the QuSoft research center and co-develops the PyZX open-source quantum compiler. His research spans quantum computation, diagrammatic reasoning, and quantum foundations. Education: PhD in Computer Science (2022, Radboud University) Research: Focuses on ZX-calculus for quantum circuit optimization, verification, and simulation. Explores quantum foundations through algebraic and compositional methods. Recent work includes quantum circuit optimization with AlphaTensor, completeness proofs for ZH-calculus, and scalable spider nets for transversal non-Clifford gates. He directs the new Master's program in Quantum Computer Science at UvA and co-authored the book Picturing Quantum Software . Notable collaborations include PyZX development and EU Gender Equality Working Group participation. Supervision includes current PhD students Lia Yeh (Oxford), Sarah Li (UvA), and Marc Farreras (Leiden). Former students include Boldizsár Poór (Quantinuum), Julien Codsi (Princeton), and Yanbin Chen (TUM). Tools & Outreach: Maintains the ZX-calculus Wikipedia page, co-lectured courses like Quantum Processes and Computation , and develops the ZX-calculus educational website. Organized QPL2026 conference and contributed to open-access journal Quantum .

Bernhard Burgethمشاهده پروفایل

دانشیار

• Image Processing
• Processing and Visualization of Tensor Fields
• Matrix Analysis
• +۳ مورد دیگر

Bernhard Burgeth is an Associate Professor of Mathematics at Saarland University since 2009. He joined the Department of Mathematics in 2002 and has held positions at the University of Erlangen-Nürnberg, McGill University, the Karlsruhe Institute of Technology (KIT), and the Technical University Eindhoven. His research spans mathematical image processing, tensor field analysis, and numerical methods for PDEs. Education : BSc, MSc (Diplom), and PhD in Mathematics from the University of Erlangen-Nürnberg; Habilitation at Saarland University. Research Interests : Focus on model-theoretic aspects of image processing, visualization of multivalued images (e.g., tensor fields), mathematical morphology, matrix analysis, and numerical simulations for hydrogen combustion. His work bridges theoretical mathematics with computational applications. Grants : Includes a Ph.D. grant from the Bavarian State Government (1990-1992), a DFG research grant at McGill University (1997/98), and a research grant from the Saarland Ministry of Economy and Science (2012/13) for the TensorVis project. Scientific Awards : Recipient of the Landespreis Hochschullehre (2010) and the Department Teaching Award (WiSe 2016/17). Teaching Responsibilities : Courses on mathematical morphology, image processing, probabilistic methods, integral equations, calculus, linear algebra, geometry, and probability/statistics. Recent lectures include Lineare Algebra: Theorie und Anwendungen (4+2), Geometrie(n) (4+2), and Wahrscheinlichkeit und Statistik (4+2).

Pascal Heiterمشاهده پروفایل

مدرس

• Numerical Optimization
• Numerical Methods for Manifold-Based Model Reduction
• Nonlinear Optimization Problems with Ordinary Differential Equation Constraints
• +۶ مورد دیگر

Dr. Pascal Heiter is a former Lecturer in Mathematics and Statistics at Neu-Ulm University of Applied Sciences (2012-2015) and holds a PhD in Numerical Mathematics from Ulm University (2017). His research focuses on numerical methods for manifold-based model reduction in nonlinear optimization problems with ordinary differential equation constraints, including chemical kinetics in combustion mechanisms, thermodynamics, and differential geometry applications. Developed AMMSoCK, a software for manifold-based model reduction in chemical kinetics Investigated Riemannian curvature tensor calculations and sectional curvatures He has supervised multiple theses at Ulm University and taught courses ranging from numerical linear algebra to optimal control theory. Scientific contributions include participation in international workshops on model reduction in reacting flows and numerical optimal control.

• Uncertainty Quantification
• Stochastic Partial Differential Equations
• Optimal Control with Random Inputs
• +۳ مورد دیگر

Dr. Akwum Onwunta is a researcher affiliated with the Max Planck Institute for Dynamics of Complex Technical Systems and holds a Ph.D. in Applied Mathematics from Otto von Guericke University, Magdeburg, Germany . His work bridges computational mathematics and quantitative finance. Research Focus: Uncertainty Quantification, Stochastic PDEs, Optimal Control, Numerical Linear Algebra, Tensor-based Algorithms, and Credit Risk Modeling. Onwunta's publications emphasize low-rank methods for solving high-dimensional problems in fluid dynamics and financial risk assessment. His expertise includes stochastic Galerkin systems and preconditioning techniques for unsteady PDEs with random inputs. Notable collaborations include work with Peter Benner and Martin Stoll on computational frameworks for uncertainty propagation in fluid mechanics. His academic output spans both theoretical and applied domains.

• Theoretical Physics
• Quantum Many-Body Systems
• Computational Physics
• +۲ مورد دیگر

Prof. Dr. Ulrich Schollwöck holds a chaired professorship at the Faculty of Physics, Ludwig Maximilian University of Munich (LMU), based at Theresienstr. 37, Room A409, 80333 Munich, Germany. His contact details include phone: +49 (0) 89 / 2180-4117, fax: +49 (0) 89 / 2180-994117, and email: schollwoeck@lmu.de . His research specializes in theoretical approaches to quantum many-body systems, with emphasis on computational physics and condensed matter theory. Key methodologies include tensor network states and numerical simulations for strongly correlated quantum matter, advancing understanding of quantum phase transitions and entanglement properties in low-dimensional systems. Prof. Schollwöck contributes to LMU's academic mission through teaching and research supervision, maintaining active collaboration within the university's physics ecosystem as evidenced by institutional group structures (e.g., Halimeh, Pollet, and Schilling groups). His work is further detailed on his personal website .

Bin Gaoمشاهده پروفایل

دانشیار

• Riemannian Optimization
• Tensor Computation
• Parallel/Distributed Computing
• +۵ مورد دیگر

Bin Gao is an Associate Professor at the Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences. He holds a Ph.D. in Applied Mathematics (2019, University of Chinese Academy of Sciences) and a B.Sc. in Mathematics (2014, Sichuan University). His postdoctoral experience includes positions at UCLouvain (2019-2021) and the University of Münster (2021-2022). Research Interests: Riemannian optimization, tensor computation, parallel/distributed algorithms for orthogonality constraints, machine learning applications. Key Contributions: Development of retraction-free methods on Stiefel manifolds, preconditioned Riemannian algorithms, and geometric frameworks for symplectic eigenvalue problems. Article Trends: Recent work focuses on overcoming the curse of dimensionality via manifold-based optimization, including distributed algorithms for Stiefel manifolds, graph-regularized tensor completion, and second-order methods for symplectic structures. Keywords span numerical analysis, quantum information, and machine learning. Scientific Awards: 2021 Zhong Jiaqing Mathematics Award 2018 Best Student Paper Award (CSIAM) 2018 CAS Special President Scholarship 2017 National Scholarship for Doctoral Students (China) 2016 Honor Student Award (International Workshop on Modern Optimization and Application) Advising & Collaborations: Collaborates with researchers from UCLouvain, University of Münster, and AMSS. Mentors students in Riemannian optimization and tensor computation. Leads the popman research group.

Clélia de Mulatierمشاهده پروفایل

استادیار

• Statistical Physics
• Information Theory
• Computer Science
• +۵ مورد دیگر

Clélia de Mulatier is an Assistant Professor at the University of Amsterdam , affiliated with both the Institute for Theoretical Physics and the Informatics Institute . She leads research at the intersection of statistical physics, information theory, and computer science , focusing on theoretical and numerical methods for complex systems . Her work spans collaborations with experimentalists in neuroscience and biology , and she actively participates in educational programs across multiple Dutch universities. Research Labs : Computational Soft Matter Lab, Computational Science Lab Affiliations : Dutch Institute for Emergent Phenomena (DIEP), Netherlands Platform Complex Systems (NPCS) Her research develops minimally complex spin models for high-order data analysis , applying exact Bayesian model selection to uncover hidden variable communities in binary datasets. This work has produced open-source tools like MinCompSpin and MinCompSpin_Greedy for different system sizes. Publications demonstrate expertise in tensor networks for dimensional reduction , epidemic modeling , and branching random walks in confined environments . Teaching includes Python programming , complex systems theory , and statistical inference for physics students across multiple institutions. She serves as program committee member for International Conference on Computational Science and organizes academic discussions through initiatives like Behind the CV: story from a Physicist .

• Database Systems
• In-Database Machine Learning
• GPU Acceleration for Databases
• +۳ مورد دیگر

Maximilian Schüle serves as Assistant Professor in the Department of Data Engineering at the University of Bamberg's Faculty of Information Systems and Applied Computer Sciences since October 2022. Previously, he held research positions at Technical University of Munich (2017-2022). His research bridges database systems and machine learning through compiler-based approaches. His research focuses on in-database machine learning , GPU-accelerated query processing , and recursive SQL extensions . Key contributions include: Developing MLIR-based compilers for automatic differentiation in SQL (DuoLingo-AutoDiff) Creating GPU code generators for database kernels using NVRTC Designing higher-order lambda functions for expressive query languages Implementing end-to-end neural network training within database engines His recent publications (2023-2025) demonstrate consistent output in top venues including ICDE, VLDB workshops, and BTW conferences, with growing emphasis on hardware-aware optimization and compiler techniques for analytical workloads. He currently leads a DFG-funded project on elastic memory hierarchies for memory-intensive applications (2025-2028), supporting multiple PhD researchers. His supervision emphasizes open-source contributions to database systems like Umbra and practical implementation skills alongside theoretical foundations. As an active member of the database community, he serves as workshop chair for BTW 2025 and regularly reviews for ACM TODS, VLDB Journal, and Information Systems. His work on public transport analytics demonstrates real-world impact through collaborations with urban mobility initiatives in Bamberg.

Dominik Stögerمشاهده پروفایل

استادیار

• Mathematical Foundations of Data Science
• Non-convex Optimization
• Machine Learning Theory
• +۴ مورد دیگر

Dominik Stöger is an Assistant Professor (tenure-track) in the Department of Mathematics at KU Eichstätt-Ingolstadt since 2021, affiliated with the Mathematical Institute for Data Science and Machine Learning (MIDS). His research bridges mathematical theory and data science applications. His educational background includes: B.Sc. in Mathematics, Technical University of Munich (2013) M.Sc. in Mathematics, Technical University of Munich (2015) Ph.D. in Mathematics, Technical University of Munich (2019) Stöger's research centers on mathematical foundations of data science, with emphasis on non-convex optimization in machine learning, theoretical analysis of overparameterized models, and low-rank matrix recovery. He combines optimization theory and high-dimensional probability to develop rigorous guarantees for modern algorithms, addressing critical challenges in deep learning theory. His recent publications (2020-2025) demonstrate consistent output in top venues including COLT, NeurIPS, and ICLR, with particular focus on implicit regularization phenomena and non-convex recovery guarantees. The 2025 pipeline shows active work extending theoretical boundaries in matrix sensing and neural network analysis. Stöger has received significant recognition: NeurIPS 2021 Spotlight Paper (top 3% of submissions) COLT 2025 paper presentation As a tenure-track faculty member, he maintains active collaborations across institutions (USC, TUM) and likely advises graduate students. His research program shows strong momentum with multiple concurrent projects advancing theoretical machine learning. He contributes to the research ecosystem through affiliation with MIDS, fostering interdisciplinary work in mathematical data science at KU Eichstätt-Ingolstadt.

• Nuclear structure physics
• Exotic nuclei
• Nuclear radii measurements
• +۵ مورد دیگر

Dr. Kanungo R. is a prominent researcher at GSI Helmholtzzentrum für Schwerionenforschung GmbH in Darmstadt, Germany, actively contributing to the field of nuclear structure physics through the NUSTAR (Nuclear Structure, Astrophysics and Reactions) collaboration at FAIR. His research program focuses on experimental investigations of exotic nuclei, particularly neutron-rich isotopes, using advanced accelerator facilities and detection systems. Dr. Kanungo's research interests center on nuclear structure far from stability, with particular emphasis on measuring proton and neutron distribution radii in exotic nuclei. His work examines neutron skin phenomena, nuclear shell evolution in exotic systems, and halo nuclei structures. By analyzing charge-changing cross sections of neutron-rich isotopes, he has made significant contributions to understanding how nuclear structure changes with extreme neutron-to-proton ratios. The publication record shows a consistent output of high-impact research in leading nuclear physics journals, with recent work focusing on oxygen, nitrogen, and fluorine isotopes. His research has revealed unexpected phenomena like thick neutron skin in doubly magic oxygen isotopes and provided evidence for tensor interactions influencing nuclear structure through precise proton radius measurements. Active contributor to the NUSTAR collaboration at FAIR Specializes in charge-changing cross section measurements Focuses on proton distribution radii in exotic nuclei Studies neutron skin and halo nuclei phenomena Investigates nuclear shell evolution far from stability Dr. Kanungo's experimental work provides critical data for testing and refining nuclear models under extreme conditions. His findings on shell closures at N=14 and 16 in oxygen isotopes and the two-neutron halo structure in 29F have advanced our understanding of nuclear structure in regions far from stability. His ongoing research continues to address fundamental questions about nuclear forces and the limits of nuclear existence.