جست‌وجوی استاد و پژوهشگر

Patricia Römerمشاهده پروفایل

پژوهشگر

• Phase Retrieval
• Inverse Problems
• Imaging Science
• +۳ مورد دیگر

Patricia Römer is a doctoral student and scientific staff member at the Department of Mathematics, Technical University of Munich (TUM), School of Computation, Information and Technology, with dual affiliation at the Helmholtz Center Munich. Her research focuses on developing algorithms for phase retrieval in imaging applications with Poisson noise. Her key research interests include: Phase retrieval and inverse problems Computational imaging under Poisson noise Optimization algorithms for low-dose imaging Mathematical recovery guarantees Ptychography and background removal techniques Recent publications (2021–2024) demonstrate consistent advancement in phase retrieval methodologies, particularly for real-world imaging scenarios involving quantization and noise constraints, bridging theoretical mathematics with practical computational solutions. Scientific awards: No awards documented As a doctoral student, she does not advise students. No grants are referenced. She operates within TUM's Data Science research group and maintains active collaboration with the Helmholtz Center Munich on imaging projects.

• Functional Analysis
• Differential Geometry
• Mathematical Physics
• +۴ مورد دیگر

Christian Fleischhack is a Professor of Analysis at the Institute of Mathematics within the Faculty of Electrical Engineering, Computer Science and Mathematics at Paderborn University, Germany, a position he has held since October 2009. His research bridges mathematical rigor with theoretical physics, focusing on foundational aspects of quantum gravity and geometric structures. His educational background includes: Diploma in Physics (1998): Funktionalintegralzugang zu Eichtheorien und Gravitation im Rahmen des Ashtekarprogramms (Leipzig) Diploma in Mathematics (1999): Stratifizierung des verallgemeinerten Eichorbitraums im Ashtekarprogramm (Leipzig) PhD (2001): Mathematische und physikalische Aspekte verallgemeinerter Eichfeldtheorien im Ashtekarprogramm (Leipzig) Fleischhack's research centers on Functional Analysis (measures on topological spaces, operator algebras), Differential Geometry (stratifications, diffeomorphisms), and Mathematical Physics (quantum geometry, quantum gravity). His work explores quantization methods—particularly loop quantization versus symmetry reduction—with emphasis on mathematical consistency in quantum gravity frameworks. He investigates how algebraic structures and geometric constraints shape physical theories, often addressing foundational questions in gauge theories and cosmology. His publication record reveals a sustained focus on loop quantum gravity's mathematical underpinnings, evolving from early work on generalized connections (2003-2006) to cosmological applications (2016-2019). Key themes include representation theory of algebras in quantum geometry, spectral properties of operators, and the interplay between symmetry and quantization. Recent articles demonstrate increasing sophistication in handling non-unital algebras and cosmological models. His scientific recognition includes: Emmy Noether Fellowship from the Deutsche Forschungsgemeinschaft (funding an independent junior research group) Alumnus status in the prestigious Young Academy (Junge Akademie) Fleischhack actively shapes his field through academic service: serving on Paderborn's PhD Board (Promotionsausschuß) and Examination Board (Prüfungsausschuß), and securing DFG funding for his Emmy Noether group. He co-organizes the annual Tux Workshops on Quantum Gravity (since 2016) and LQP Workshops on local quantum physics, fostering international collaboration. His editorial contributions include co-editing the compendium Heureka – Evidenzkriterien in den Wissenschaften (2010) and reviewing for journals like Mathematische Semesterberichte . He leads a research environment centered around the Mathematical Physics group at Paderborn, with strong ties to the Max Planck Institute network. His workshop series in Tux, Austria, and northern Germany serve as critical hubs for the loop quantum gravity community, attracting leading researchers to advance theoretical frontiers.

Michel T. Ivrlacمشاهده پروفایل

پژوهشگر ارشد

• Physically consistent modeling of communication systems
• Compact MIMO systems
• Electromagnetic principles of information technology
• +۷ مورد دیگر

Michel T. Ivrlac is a Senior Researcher at the Chair of Signal Processing Methods within the School of Computation, Information and Technology at the Technical University of Munich (TUM). His research focuses on: Physically consistent modeling of communication systems Compact MIMO systems Electromagnetic principles of information technology Space/time coding with coarse quantization of the received signal Interference in cellular mobile communications Dr. Ivrlac teaches several key courses at TUM including: Adaptive and Array Signal Processing (winter semester) Circuit Theory and Communications (winter semester) Electrical Engineering I and II for Teacher Training Physical Principles of Electromagnetic Fields and Antenna Systems Systems and Circuit Technology Practical Course His research connects theoretical signal processing with practical applications in communications technology, particularly focusing on physical layer aspects of wireless communications. His work spans from fundamental electromagnetic principles to advanced signal processing techniques for next-generation communication systems, aligning with TUM's research in Machine Learning for Physical Layer Wireless Communications and Intelligent Reflecting Surface Systems. Dr. Ivrlac maintains regular office hours by appointment and is based in Room N1115 at Theresienstrasse 90, Building N1, 1st Floor at the Technical University of Munich.

• Stochastic Partial Differential Equations
• Fluid Mechanics
• Compressible Fluid Dynamics
• +۳ مورد دیگر

Prof. Dr. Martina Hofmanová is a Professor at the Faculty of Mathematics, Bielefeld University , specializing in Stochastic Partial Differential Equations (SPDEs) and Fluid Mechanics . She has been the principal investigator of the ERC Starting Grant 'Mathematical analysis of fluid flows: the challenge of randomness' (2021–2025) and leads projects like CRC 1283 'Taming uncertainty and benefiting from randomness' . Her work bridges stochastic analysis, nonlinear PDEs, and mathematical physics. Education : Doctorate (2013) from École Normale Supérieure de Cachan (France) and Charles University (Czech Republic), supervised by Arnaud Debussche and Jan Seidler. Academic Positions : W2/W3 Professor at Bielefeld University (2017–present), Junior Professor at TU Berlin (2016–2017), Postdoc at MPIMS Leipzig (2013–2014). Research Focus : Mathematical analysis of fluid flows under randomness, including Navier-Stokes , Euler , and non-Newtonian fluid equations. She employs probabilistic methods, convex integration, and rough path theory to address existence, uniqueness, and ergodicity in stochastic systems. Recent work explores supercritical SPDEs , compressible fluids , and quantum field theory via stochastic quantization. Scientific Contributions : Awards : 2022 Minkowski Medal (German Mathematical Society). Grants : ERC Starting Grant (2021), CRC 1283 Subproject Leader (2019–present), DFG-funded 'Stochastic Partial Differential Equations' (2022).

Clark Barrettمشاهده پروفایل

استاد

• Formal Methods
• Automated Reasoning
• Verification
• +۷ مورد دیگر

Clark Barrett is a Professor in the Department of Computer Science at Stanford University, where he conducts research in formal methods, automated reasoning, and verification. He is affiliated with several research centers including the Stanford Center for Automated Reasoning, Stanford Center for AI Safety, Stanford Agile Hardware Project, and Stanford Center for Blockchain Research. His research focuses on developing formal methods and tools for verifying complex systems, with particular emphasis on satisfiability modulo theories (SMT), verification of neural networks, hardware design verification, and security. His work bridges theoretical foundations with practical applications across multiple domains. Over the past decade, Barrett's research has evolved from foundational work in SMT solving to increasingly diverse applications including neural network verification, hardware verification, and AI safety. His recent publications demonstrate a strong focus on practical verification techniques for real-world systems, particularly in the areas of hardware design, neural networks, and programming languages. The trend shows an expansion from core verification techniques to broader applications in AI safety and secure systems design. 2021 CAV (Computer Aided Verification) Award Barrett leads several major research initiatives and collaborates extensively with industry partners. His work on the Marabou neural network verification framework, SMT-LIB standard, and Symbolic QED verification methodology have had significant impact in both academic and industrial settings. He has supervised numerous PhD students and postdoctoral researchers who have gone on to successful careers in academia and industry. He is a key member of the Stanford Center for Automated Reasoning, which develops foundational technologies for automated reasoning, and the Stanford Center for AI Safety, where he focuses on formal methods for ensuring the safety and reliability of AI systems. His work on the Stanford Agile Hardware Project aims to revolutionize hardware design through formal methods and verification techniques.

• Enumerative Geometry
• Quantum Algebra
• Quantum Topology
• +۷ مورد دیگر

Professor Gaëtan Borot is a faculty member at the Institute of Mathematics, Faculty of Mathematics and Natural Sciences, Humboldt-Universität zu Berlin. He leads a research group in Mathematical Physics with connections to quantum field theory, string theory, and geometric analysis. His work is supported by multiple Research Training Groups including Rethinking QFT (2019-2029), From geometry to numbers (2024-2029), and the College of Mathematics and Physics Berlin (2020-2029). Professor Borot's research centers around topological recursion and its applications across mathematical physics. His work connects enumerative geometry, quantum algebra, moduli spaces, and random matrix theory through a unifying framework that reveals deep connections between seemingly disparate fields. He investigates how topological recursion provides methods to study quantization of geometric objects and field theories, with applications ranging from Gromov-Witten theory to statistical physics models on random surfaces. Analysis of his recent publications (2021-2024) shows a strong focus on the mathematical structures underlying conformal field theories, particularly Liouville CFT, where he explores Virasoro representations, scattering matrices, and equations of motion. His work on topological recursion continues to expand into new domains including cohomological field theories, Hurwitz theory, and spectral curves, demonstrating the versatility of this algebraic structure across mathematical physics. Professor Borot actively supervises PhD students including Giacomo Umer (who successfully defended in May 2025), Davide Scazzuso, and Niklas Martensen, along with numerous master's and bachelor's students. He organizes the Mathematical Physics Seminar held weekly in Adlershof and has taught courses on integrable systems, random matrix theory, and differential geometry. Despite currently being on leave until September 2025, he continues to supervise thesis projects with availability starting October 2025.

Lea Boßmannمشاهده پروفایل

استاد

• Mathematical Physics
• Quantum Many-Body Systems
• Interacting Bose Gases
• +۷ مورد دیگر

Lea Boßmann is Professor of Analysis at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), appointed in 2024. Previously she held a Junior Professorship at Johannes Gutenberg University Mainz and post-doctoral positions at LMU Munich and IST Austria. Education 2016–2019: Dr. rer. nat., University of Tübingen (PhD thesis: Effective dynamics of interacting bosons ) 2010–2016: B.Sc. & M.Sc. in Physics and Theoretical-Mathematical Physics, LMU Munich Research Interests Her research lies in mathematical physics, concentrating on the rigorous analysis of quantum many-body systems. She is particularly interested in deriving effective evolution equations for complex bosonic systems in the mean-field and large-particle limits, handling singular interactions, dimension reduction, and higher-order perturbative corrections beyond the classical Bogoliubov approximation. Key themes include: Effective descriptions of interacting Bose gases Mean-field limits and nonlinear Schrödinger equations Asymptotic analysis and Edgeworth expansions Dimensional reduction for strongly confined systems Stochastic perspectives on quantum many-body dynamics Scientific Contributions Across more than a dozen peer-reviewed articles since 2018, Boßmann has systematically refined the mathematical understanding of weakly interacting Bose gases, providing rigorous justification of effective equations such as the Gross–Pitaevskii and one-dimensional nonlinear Schrödinger equations, quantifying higher-order corrections, and analyzing spectral and dynamical properties of low-energy excitations. Teaching & Supervision At FAU she lectures in Analysis and runs advanced seminars on function theory and mathematical physics. During the academic year 2025 she will offer: Summer 2025: Function theory, Real Functions seminar, Mathematical Physics seminar Winter 2024/25: Analysis for teaching degree students, Mathematical Physics seminar Contact & Location Room 02.385, Cauerstraße 11, 91058 Erlangen, Germany Phone: +49 9131 85-67120 E-mail: lea.bossmann@fau.de

• Theoretical Chemistry
• Quantum Dynamics
• Molecular Reaction Dynamics
• +۴ مورد دیگر

Uwe Manthe is a Professor of Theoretical Chemistry at Bielefeld University, Faculty of Chemistry. He holds multiple administrative positions including Chairman of the Doctoral Committee, Deputy Chairman of the Society of German Chemists - Bielefeld Chapter, and member of various committees including the Faculty Conference and Financial Affairs and Resources Commission. Faculty of Chemistry / Theoretical Chemistry Faculty of Chemistry / Bodies, Commissions and Committees / Faculty Conference Faculty of Chemistry / Committees, Commissions and Boards / Examination Boards / Doctoral Committee (Chairman) Faculty of Chemistry / Associated Organizations / Society of German Chemists - Bielefeld Chapter (Deputy Chairman) Professor Manthe's research focuses on theoretical and computational chemistry, particularly quantum dynamics calculations for chemical reactions. His work centers on the multi-configurational time-dependent Hartree (MCTDH) approach, potential energy surfaces, reaction dynamics, and quantum scattering theory. He has made significant contributions to understanding hydrogen abstraction reactions, particularly those involving methane and its isotopologues. His recent publications demonstrate a strong focus on advancing computational methodologies for quantum dynamics, including tree tensor networks, correlation discrete variable representations, and non-hierarchical multi-layer MCTDH approaches. These methods enable accurate calculations of reaction rates and state-specific dynamics for complex polyatomic systems. His work bridges theoretical developments with practical applications in chemical kinetics and reaction mechanisms. As an educator, Professor Manthe is responsible for numerous courses including Theoretical Chemistry, Advanced Theoretical Chemistry, Quantum Chemistry, and Numerical Methods in Chemistry at both undergraduate and graduate levels. His teaching spans foundational mathematics through advanced specialization in theoretical chemistry.

• Probability Theory
• Machine Learning
• Stochastic Optimization
• +۴ مورد دیگر

Stephan Eckstein is a junior professor in the Department of Mathematics at the University of Tübingen and a member of the university's machine learning cluster. His research bridges probability theory and machine learning with particular focus on stochastic optimization and numerical approximation. Research interests include: Optimal transport theory and its computational aspects Regularization techniques for high-dimensional problems Causal models and probabilistic structures Graphical models in machine learning Graph neural networks Recent publications analyze dimensional stability in optimal transport, exponential convergence rates for Sinkhorn algorithms, and causal modeling in financial time series generation. Contact: stephan.eckstein@uni-tuebingen.de

• Machine Learning
• Neural Networks
• FPGA Optimization
• +۳ مورد دیگر

Vladimir Loncar is a researcher specializing in machine learning, FPGA optimization, and high-energy physics computing. His work focuses on accelerating neural networks and scientific algorithms using hardware-aware techniques. Notably, he contributes to the hls4ml framework for FPGA deployment of machine learning models, and has applied these methods to particle physics experiments like LHCb and the HL-LHC. His research spans symbolic regression, recurrent neural networks, and real-time data processing for large-scale physics detectors. Key projects include developing resource-efficient inference systems (e.g., Tailor for CNN optimization), benchmarking frameworks for GNN-based surrogate models, and latency-critical implementations for collider experiments. Loncar's work bridges theoretical physics and computational engineering, emphasizing practical applications in experimental particle physics, quantum simulations, and autonomous detector control. He collaborates extensively with institutions like CERN and the sPHENIX collaboration.

• Machine Learning
• Signal Processing
• Remote Sensing
• +۴ مورد دیگر

Wei Xue is an active academic researcher affiliated with Tsinghua University's Department of Computer Science and Technology. Their work spans multiple disciplines, including Machine Learning , Signal Processing , Medical Imaging , and Natural Language Processing . Key research areas include adversarial robustness in DNNs for remote sensing, hierarchical speaker representation learning for speech extraction, and multi-view fuzzy classification for brain network analysis. Recent publications focus on imbalanced data classification, spectrum sensing in cognitive radio, and innovative applications in soft robotics and medical diagnostics. Collaborations include institutions like Tsinghua University, Jiangnan University, and Hong Kong Baptist University, with frequent contributions to journals such as IEEE Transactions on Geoscience and Remote Sensing and Neural Networks .

Carlos I. Perez-Sanchezمشاهده پروفایل

پژوهشگر

• Mathematical Physics
• Noncommutative Geometry
• Random Matrices
• +۷ مورد دیگر

Carlos I. Perez-Sanchez is a postdoctoral researcher at the Institute for Theoretical Physics , University of Heidelberg, working under Răzvan Gurău . He previously held postdoctoral positions at the University of Warsaw (2021) and completed his PhD in mathematics at the University of Münster under Raimar Wulkenhaar. His research spans mathematical physics , focusing on random noncommutative geometry , tensor field theory , and their intersections with quantum gravity , functional renormalization , and bootstrap methods . His work on noncommutative geometry involves quantizing spectral triples via random matrices and unitary matrix ensembles to model gauge-Higgs theories and quantum gravity. He has advanced tensor field theory through topological recursion and Ward-Takahashi identities , bridging combinatorial structures with physical partition functions. His recent focus on functional renormalization (Wetterich equation) explores the renormalization group flow in multi-trace matrix models and free algebra frameworks. Publications include 15 recent articles (2025–2018) on topics like loop equations , Borel summability , and quiver-based noncommutative geometries . He co-organized workshops such as The QFT Path (2024) and Random Geometry in Heidelberg (2022), and has delivered talks at institutions in Bordeaux, Vienna, Warsaw, and Okinawa. His teaching includes Theoretical Statistical Physics and Large-N Methods in Field Theory at Heidelberg.

Maurits W. Haverkortمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Many-Body Systems
• X-ray Spectroscopy
• +۴ مورد دیگر

Maurits W. Haverkort is a Professor at the Institute for Theoretical Physics of Heidelberg University, Germany. His research focuses on correlated electron systems, developing numerical methods such as the Quanty software package for quantum many-body simulations. He leads a group exploring spectroscopic techniques (XAS, RIXS) and dynamical properties of complex materials, with applications to transition metal compounds, topological insulators, and actinides. His work bridges theory and experiment, emphasizing predictive modeling of electronic, magnetic, and optical properties. Education details include postdoctoral research under Prof. Bernhard Keimer at the Max Planck Institute for Solid State Research. He has taught advanced courses on condensed matter theory and computational methods at Heidelberg University. Collaborations involve global institutions like the University of Saskatchewan and the SLAC National Accelerator Laboratory. Key research directions include: (1) Development of Quanty for solving many-body problems via second quantization; (2) Spectroscopic tools for bond covalency and 5f-electron counting in actinides; (3) Neutrino mass determination via electron capture studies in Ho-163; (4) Exploring spin-orbit coupling effects in topological materials. His group has pioneered femtometer-precision vibrational metrology and ultrafast laser-controlled quantum dynamics. Funding includes leadership roles in DFG Research Units FOR 2202 (ECHo experiment), FOR 1346 (LDA+DMFT methods), and EU projects like MetroMMC. His team manages computational resources on Heidelberg's bwForCluster, emphasizing high-performance computing for correlated systems.

Marc Marot-Lassauzaieمشاهده پروفایل

پژوهشگر

• HPC Software Engineering
• Algorithm Efficiency
• Large-Scale Simulations
• +۲ مورد دیگر

Marc Marot-Lassauzaie is a Research Associate at the Chair of Scientific Computing in Computer Science (SCCS), Technical University of Munich (TUM). He holds an M.Sc. in Computational Science and Engineering (2020) and a B.Sc. in Engineering Sciences (2018), both from TUM. His research focuses on HPC software engineering, algorithm efficiency optimization, and large-scale simulations. He currently contributes to the Exahype software project and explores mixed-precision algorithmics for high-order methods like the ADER-DG algorithm. His work emphasizes improving computational performance and numerical stability in scientific simulations. Teaching activities include leading the Master-Praktikum on Scientific Computing and High-Performance Computing in Winter 2021. He has presented research at conferences such as PASC24, focusing on the impact of numerical precision in high-order methods. His technical expertise includes software development for large-scale simulations and collaboration on exascale computing initiatives.

Joachim Rudolphمشاهده پروفایل

استاد

• Control Engineering
• Systems Theory
• Robotics
• +۷ مورد دیگر

Prof. Joachim Rudolph is a Professor at Saarland University's Department of Systems Theory and Automatic Control within the College of Engineering. He specializes in advanced control engineering, systems theory, and robotics, with a focus on nonlinear control, distributed parameter systems, and model-based approaches. He teaches courses such as Systemmodellierung und Simulation , Systems Theory and Control Engineering , and supervises student theses on topics like robotics, hydraulic systems, and control algorithms. His research emphasizes practical applications, including magnetic actuator control, mobile robotics, and fault-tolerant systems. He leads the Chair for Systems Theory and Automatic Control, offering student projects in areas like mechatronics and autonomous systems. Recent courses include Systemtheorie und Regelungstechnik 3/4 , with lectures and exercises held in buildings A5 1 and E2 5. His work often involves collaboration with international researchers and industry, as seen in his involvement with the InnoLecture Colloquium and student exchange programs. Key research interests include algebraic differentiators, control of PDE-ODE coupled systems, and experimental validation. His lab focuses on practical implementations, such as magnetic levitation systems and tricopter control. He advises numerous students on master’s and bachelor’s theses, covering topics from observer design to energy-efficient control. Education: Doctorate (Dr.-Ing.) and Habilitation in Engineering. Affiliations: Chair for Systems Theory and Automatic Control, Saarland University. Grants/Funding: Multiple projects on robotics, control systems, and mechatronics (details not explicitly mentioned). Labs/Teams: Active in experimental setups like magnetic bearing systems and autonomous vehicle control.