جستجوی استاد راهنمای دانشگاهی

• Control Systems
• Discrete Event and Hybrid Systems
• Max-Plus Algebra
• +۵ مورد دیگر

Jörg Raisch is a Professor of Control Systems at the Technische Universität Berlin , affiliated with the Faculty IV - Electrical Engineering and Computer Science and the Institute for Energy and Automation Technology . He holds the chair of "Fachgebiet Regelungssysteme" since March 2006. Raisch studied "Technische Kybernetik" (Engineering Cybernetics) at Stuttgart University, Germany, and Control Systems at UMIST, Manchester, UK. He earned his Ph.D. in Chemical Engineering from Stuttgart University, followed by postdoctoral work at the University of Toronto and a DFG fellowship for his habilitation (1998). He established a research group at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg and served as an External Scientific Member since 2002. His research spans control theory , discrete event systems , max-plus algebra , and applications in energy systems and robotics . Recent work focuses on clock drift effects in low-inertia power systems , iterative learning control , and distributed control for microgrids . His publications highlight methodologies for timed event graphs , probabilistic behavioral distances , and wind turbine optimization . From 2007–2013, he represented Germany in the European Control Association (EUCA). He served on editorial boards of journals like Automatica and IEEE Transactions on Control Systems Technology . He held leadership roles in IFAC Technical Committee TC1.3 as Vice-Chair (2014–2017, 2020–present) and Chair (2017–2020) .

Lukasz Grabowskiمشاهده پروفایل

استاد

• Group Theory
• Combinatorics
• Algorithms
• +۴ مورد دیگر

Lukasz Grabowski is Professor for Theoretical Mathematics at the Institute of Mathematics, Leipzig University, actively engaged in research, teaching, and academic outreach. His institutional affiliation places him within Germany's prominent research-focused university system. His research centers on advanced mathematical structures with three core emphases: Group Theory (discrete groups, group rings, l2-invariants, and finite approximations), Measured and Borel Combinatorics (expansion properties, Kazhdan property, Aldous-Lyons conjecture, and equidecompositions), and Algorithms/Complexity Theory for graphs and groups (including Lovasz Local Lemma applications). These interconnected fields address fundamental questions in theoretical mathematics with implications for computational theory. Professor Grabowski currently supervises PhD students Jardon Hector Sanchez (Aldous-Lyons conjecture and Kazhdan property in groupoids) and Onur Bilge (Borel and measurable combinatorics), building on mentorship of former postdocs Joan Claramunt and Tomasz Ciesla. He actively promotes mathematical talent through the Mathe-Zirkel program for secondary students and delivers specialized lectures internationally, as evidenced by his 2024 Bonn talk on unimodular random graphs and 2018 Madrid lecture notes on L2-invariants. He leads a dynamic research group within Leipzig University's Institute of Mathematics, fostering collaboration through seminar presentations and academic exchanges while maintaining strong institutional ties through departmental teaching responsibilities including Algebraic Topology courses.

• 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 .

Fred Hamprechtمشاهده پروفایل

استاد

• Machine Learning
• Image Analysis
• Quantum Chemistry
• +۴ مورد دیگر

Fred Hamprecht is a Professor whose work bridges machine learning algorithms and complex problems with spatial structure . He has spent two decades advancing image analysis before pivoting to quantum chemistry , focusing on learning kinetic energy functionals via density functional theory and geometric machine learning . His research is grounded in rigorous mathematical frameworks like combinatorial optimization and algebraic graph theory , with a commitment to practical applications. His lab comprises exceptionally talented individuals, and he takes pride in mentoring students who have transitioned into prominent roles, including: Anna Kreshuk - PI at EMBL Bernhard Renard - Professor at HPI Bjoern Andres - Professor at TU Dresden Bjoern Menze - Professor at Zurich University Melih Kandemir - Associate Professor at University of Southern Denmark

Yariv Aizenbudمشاهده پروفایل

استادیار

• Statistical Recovery
• Geometric Structures
• Latent Tree Models
• +۴ مورد دیگر

Dr. Yariv Aizenbud is an Assistant Professor in the Department of Applied Mathematics at Tel Aviv University's School of Mathematical Sciences. His academic journey includes a Ph.D. in Applied Mathematics from Tel Aviv University and a Gibbs assistant professorship at Yale University's Applied Math Program. Research Focus: Statistical recovery of geometric structures Applications: Latent tree variable models, Manifold Learning, Randomized Algorithms in Numerical Linear Algebra Academic Roles: Organizes the Applied Math Seminar at Tel Aviv University Contact: Office: 108 Schreiber Building, Department of Mathematics, Tel Aviv University, Israel, 69978.

Sören Kraußharمشاهده پروفایل

استاد

• Dirac and Laplace operator on manifolds
• Complex and hypercomplex analysis
• Slice monogenic functions
• +۸ مورد دیگر

Prof. Dr. Sören Kraußhar is a Professor in the Department of Mathematics and Mathematics Education at the Faculty of Educational Science, University of Erfurt. His office is located in Teaching Building 2, Room 109b. He is actively involved in research and teaching in advanced mathematical analysis, with particular expertise in hypercomplex function theory and its applications to physics and engineering problems. Prof. Kraußhar's research spans Dirac and Laplace operators on manifolds, complex and hypercomplex analysis, slice monogenic functions, harmonic and hypercomplex automorphic forms, parabolic partial differential equations, and non-commutative geometry. His work represents a sophisticated integration of pure mathematical theory with practical applications in physics, particularly in magnetohydrodynamics and quantum mechanics. He has developed significant theoretical frameworks for octonionic and quaternionic analysis that extend traditional complex analysis to more complex algebraic structures. His publication record demonstrates a consistent progression from classical complex analysis toward more advanced hypercomplex analysis, with notable contributions to octonionic Bergman and Szegö kernels, Cauchy formulas in discrete settings, and variational principles with applications to magnetohydrodynamic equations. His recent work shows increasing focus on fractional calculus applications within hypercomplex settings and eigenvalue problems for slice functions. Prof. Kraußhar maintains active collaborations with researchers including F. Colombo, D. Legatiuk, and I. Sabadini, resulting in publications in high-impact journals such as Complex Analysis and Operator Theory, Journal of Geometry and Physics, and Mathematical Methods in the Applied Sciences. His work continues to push theoretical boundaries while maintaining relevance to physical applications, particularly in differential equations and mathematical physics.

Kapil Ahujaمشاهده پروفایل

استاد

• Machine Learning
• Network Science
• Computational Optimization
• +۴ مورد دیگر

Prof. Kapil Ahuja is a Full Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Indore (IIT Indore), where he heads the Mathematics of Data Science and Simulation (MODSS) research lab. After completing dual Master's degrees and a Ph.D. from Virginia Tech (USA) followed by postdoctoral work at the Max Planck Institute in Germany, he has held visiting positions at UT Austin, IMT Atlantique, Sandia National Labs, TU Dresden, and TU Braunschweig. His administrative roles include founding Dean of International Affairs and former Head of Computer Science & Engineering at IIT Indore. Education: Ph.D. in Mathematics, Virginia Tech (2011) M.S. in Mathematics, Virginia Tech (2009) M.S. in Computer Science, Virginia Tech (2007) B.Tech. in Mechanical Engineering, IIT (BHU) Varanasi (2001) Research Focus: Prof. Ahuja's work bridges theoretical advances with real-world applications, emphasizing machine learning algorithms for plant/cancer studies, game-theoretic poverty reduction models, exascale climate modeling solvers, and drone trajectory optimization. His interdisciplinary approach integrates numerical linear algebra with network science to solve complex systems problems across healthcare, agriculture, and climate science, supported by 4.85 Crores INR in external funding. Publication Trends: Recent work demonstrates growing emphasis on AI-driven optimization for physical systems (drones, climate models) and biomedical applications (cancer classification). His publications increasingly feature cross-disciplinary collaborations between computer science, biology, and economics, with notable contributions in explainable AI for healthcare and resource allocation algorithms for social networks. Scientific Recognition: National Teacher's Award (2024) from the President of India Five-time recipient of IIT Indore's Best Teacher Award (2013-2023) Best Poster Award at International Workshop on Game Theory & Networks (2019) Steeneck Graduate Research Fellowship (Virginia Tech, 2011) Multiple SIAM travel awards for international conferences Mentorship & Service: Prof. Ahuja has graduated 5 Ph.D. and 4 M.S. (Research) students while mentoring 75 B.Tech. projects. He serves as Associate Editor for Applied Intelligence Journal (Springer Nature) and Knowledge and Information Systems, organizes international conferences, and reviews for 35+ academic sources. His administrative leadership significantly expanded IIT Indore's global partnerships through the Research Park initiative. Research Infrastructure: The MODSS lab maintains active collaborations with Oak Ridge National Lab, Sandia National Labs, and European institutions. Current projects include AI-optimized drone swarms for agricultural monitoring and game-theoretic models for poverty intervention, utilizing high-performance computing resources for large-scale simulations.

• Hamiltonian Systems
• Model Reduction
• Geometric Optimization
• +۴ مورد دیگر

Dr. Thomas Bendokat is a researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. He specializes in computational methods for systems and control theory, with a focus on geometric approaches to dynamical systems and manifold structures. Research Interests: Hamiltonian systems, symplectic geometry, Grassmann and Stiefel manifolds, model reduction, geometric optimization, and data-driven identification of nonlinear systems. Contact: Email: bendokat@mpi-magdeburg.mpg.de His work bridges theoretical mathematics with practical applications in gas network modeling, computer vision, and structure-preserving computational methods. He has contributed to open-source software like phgasnets for port-Hamiltonian system simulations.

• 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.

• Numerical Linear Algebra
• Preconditioning Technique
• Structured Matrix Computations
• +۳ مورد دیگر

Dr. Yue Qiu is a Postdoc researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany, specializing in computational methods for systems and control theory. His work focuses on advancing numerical techniques for large-scale dynamical systems, with applications in energy networks and uncertainty quantification. Education : PhD in Applied Mathematics and Systems & Control, Delft University of Technology (2011-2015) MSc in Control Theory and Control Engineering, Northeastern University, China (2009-2011) BSc in Automatic Control, Northeastern University, China (2005-2009) His research interests span Numerical Linear Algebra, Preconditioning Techniques, Structured Matrix Computations, and Energy Networks. He contributes to multidisciplinary projects bridging mathematics and systems & control theory. As part of the Computational Methods in Systems and Control Theory group, Dr. Qiu collaborates on projects related to dynamical systems, optimization, and uncertainty quantification. His work emphasizes efficient numerical algorithms for real-world applications in energy systems.

Yao Yueمشاهده پروفایل

پژوهشگر

• Model Order Reduction
• Design Optimization
• Krylov Methods
• +۷ مورد دیگر

Yao Yue is a postdoctoral researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. Their work focuses on computational methods in systems and control theory, including parametric model order reduction, design optimization, Krylov methods, and fast computation techniques for Simulated Moving Bed (SMB) models and vibration/structure simulations. Education : Bachelor of Electronic Science and Technology, Harbin Engineering University (2001–2005) Master of Integrated Circuit Design, Tsinghua University (2005–2008) PhD in Engineering (Applied Mathematics, Numerical Approximation, Linear Algebra) at KU Leuven, Belgium (2008–2012) Research Interests span both applied mathematics and philosophical foundations of cognition. In computational methods, they work on optimizing numerical algorithms and system modeling. In philosophy, they explore axiomatic frameworks for cognitive dispositions, negation tendencies, and the epistemological limits of logic and empirical observation. Additional Activities include maintaining a personal homepage where they develop philosophical works like Reconstruction of Philosophy , discussing topics such as multiverse theory, consciousness, and the role of negation in knowledge formation.

Rolf Drechslerمشاهده پروفایل

استاد

• Formal Verification
• Quantum Computing
• RISC-V Architecture
• +۴ مورد دیگر

Rolf Drechsler is a Full Professor and Head of the Group of Computer Architecture at the University of Bremen's Institute of Computer Science since 2001, and Director of the Cyber-Physical Systems Group at DFKI Bremen since 2011. He holds an adjunct professorship at the Indian Statistical Institute and has been affiliated with Duke University. Education: Diploma (1992) and Dr. phil. nat. (1995) in Computer Science from Goethe University Frankfurt Academic Leadership: Dean of Mathematics and Computer Science Faculty (2018-2025), Vice Rector for Research (2008-2013) His research focuses on formal verification , RISC-V architectures , and quantum/in-memory computing . Recent work explores LLM integration in hardware testing and polynomial-based verification techniques. Publications from 2024-2025 span IEEE Transactions , DATE , and DAC , emphasizing automated verification , quantum circuit mapping , and LLM-driven testbench generation . Scientific Awards IEEE/ACM Best Paper Awards (2013, 2018) Berninghausen-Preis for Innovative Teaching (2018) IEEE Fellow (2015) Founder Award for Solvertec (2013) He has served on program committees for DAC, ICCAD, DATE, and founded graduate schools in Embedded Systems and System Design under Germany's Excellence Initiative.

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.

• Computational Complexity
• Algorithmic Game Theory
• Mechanism Design
• +۳ مورد دیگر

Argyrios Deligkas is a Senior Lecturer (equivalent to Associate Professor) at the Royal Holloway University of London. He obtained his PhD from the University of Liverpool under the supervision of Rahul Savani and held postdoctoral positions at the University of Liverpool and the Technion (Industrial Engineering and Management department). His research focuses on computational aspects of game theory, optimization, and complexity. Key interests include: Algorithmic Game Theory and Mechanism Design Computational Complexity (PPAD/PPA-hardness) Fixed-parameter algorithms and combinatorial optimization Fair division and resource allocation Equilibrium computation in multi-agent systems Recent publications (2023-2025) demonstrate a strong emphasis on computational hardness in fair division (e.g., PPA-hardness proofs), mechanism design with real-world constraints, and parameterized algorithms for pathfinding/graph problems. Collaborative work with European researchers dominates his output, with frequent appearances at AAAI, IJCAI, and AAMAS. He actively presents at conferences (e.g., ALGA2025, WINE 2024) and collaborates internationally, including visits to universities in Vienna, Prague, Glasgow, and Edinburgh.

Mathieu Hoyrupمشاهده پروفایل

پژوهشگر

• Recursion Theory
• Computable Analysis
• Algorithmic Randomness
• +۴ مورد دیگر

Mathieu Hoyrup is a permanent researcher (Chargé de Recherche) at Inria , affiliated with the Mocqua team at the LORIA research center in Nancy, France. His research bridges mathematical logic, computability theory, and dynamical systems through the lens of computable analysis and algorithmic randomness. Research Interests : Recursion theory, computable analysis, algorithmic randomness, ergodic theory, and dynamical systems. Advising : Supervised PhD students Hugo Férée, Djamel Eddine Amir, Alexis Terrassin, and Rémi Pallen. Academic Service : Organized the Computability and Complexity in Analysis conferences (2013–2022) and the Continuity, Computability, Constructivity (CCC 2017). Education : PhD in Mathematics from Université Paris Diderot (2008); Habilitation à diriger des recherches (2021) on topological aspects of representations in computable analysis.