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Prof. Dr. Jens Lang is a Professor at the Numerical Analysis Group within the Department of Mathematics at Technische Universität Darmstadt . His work focuses on adaptive numerical methods for partial differential equations (PDEs), particularly in computational fluid dynamics, uncertainty quantification, and optimal control.
Prof. Alexander Mielke is a leading mathematician affiliated with the Weierstrass Institute (WIAS) in Berlin, Germany. His work focuses on partial differential equations , gradient systems , and thermodynamic modeling with applications in material science, quantum mechanics, and multiscale systems. Institution: Weierstrass Institute (WIAS), Berlin Research Interests: Gradient flows, reaction-diffusion systems, optimal transport, variational analysis, and nonlinear mechanics Research Highlights: Mielke’s research explores the interplay between entropy decay , non-equilibrium steady states , and EDP convergence in gradient systems. His recent work includes self-similar profiles in diffusion equations and GENERIC formalism for thermodynamical models. Publications: He has authored over 50 peer-reviewed works, including studies on Hellinger–Kantorovich spaces , stochastic homogenization , and quantum-classical coupling . His articles appear in journals like Arch. Ration. Mech. Anal. , SIAM J. Math. Anal. , and J. Nonlinear Sci.
Dr. Stefanie Winkelmann is a leading researcher at the Zuse Institute Berlin (ZIB) , heading the Computational Systems Biology group within the Modeling and Simulation of Complex Processes school. Her work bridges mathematical theory with biological applications. Current affiliations: ZIB, DFG Cluster of Excellence MATH+, CRC 1114 Research Interests include: Stochastic reaction-diffusion processes Hybrid and multiscale modeling approaches Markov state models for metastable dynamics Agent-based modeling of social and biochemical systems Applications to neurotransmission, epidemics, and opinion dynamics Publication Trends show a focus on combining stochastic processes with computational biology. Her recent work explores collective variables in network dynamics, synchronization in biochemical oscillators, and data-driven approaches to drug design. Grants and Projects include leadership roles in DFG-funded initiatives such as: Modeling Synaptic Plasticity (2025-2028) Collective Variables for Spreading Processes (2025-2026) Math-Powered Drug Design (2022-2025) Contact : winkelmann@zib.de
Mirjam Dür is a Full Professor (W3) at the Department of Discrete Mathematics, Optimization and Operations Research within the Faculty of Mathematics, Natural Sciences and Technology at the University of Augsburg (since 2017). Previously, she held Full Professor positions at the University of Trier (2011-2017) and other academic roles in Groningen, Darmstadt, and Vienna. Her research focuses on mathematical optimization, particularly copositive programming, quadratic optimization, matrix theory, and conic optimization. Born in Vienna, Austria M.Sc. in Mathematics (1996) and PhD in Applied Mathematics (1999) from University of Trier Positive Habilitation evaluation at TU Darmstadt (2005) Research Interests : Global optimization, quadratic and combinatorial optimization, conic optimization and matrix theory, copositive programming, and applications to graph theory and discrete problems. She has pioneered methods like factorization-based approaches for completely positive matrices and cutting plane techniques in copositive programming. Scientific Awards : 2013 Optimization Letters Best Paper Award 2010 VICI Grant (NWO) 2012 GIF Research Grant (German-Israeli Foundation) Key Contributions : Development of algorithms for copositive optimization, theoretical advances in matrix cones, and novel applications to problems like graph stability and discrete optimization. She serves as Senior Editor for Optimization Methods and Software and editorial board member for multiple optimization journals.
Elisabeth Gaar serves as Professor of Optimization within the Chair of Discrete Mathematics, Optimization and Operations Research at the Institute of Mathematics, Faculty of Mathematics, Natural Sciences and Technology, University of Augsburg. She has held this position since May 2024, following a prior appointment from March 2023 to April 2024. Previously, she conducted postdoctoral research at Alpen-Adria-University Klagenfurt and worked at Johannes Kepler University Linz's Institute for Production and Logistics Management from October 2020 to February 2023. Her academic credentials include Bachelor's and Master's degrees in Technical Mathematics with specialization in Operations Research from Graz University of Technology, culminating in a doctorate from Alpen-Adria-University Klagenfurt's Institute of Mathematics in 2018. Dr. Gaar's research focuses on combinatorial optimization and nonlinear programming , with significant contributions to graph theory and algorithmic development. Her work bridges theoretical mathematics with practical applications in logistics and decision systems, emphasizing efficient solution methods for complex optimization problems. Her distinguished recognition includes: ÖGOR award for master's thesis ÖGOR award for doctoral dissertation GOR Young Researchers Award 2022 She collaborates within a specialized research team comprising Prof. Dr. Mirjam Dür, Prof. Dr. Dirk Hachenberger, and administrative support staff including Thomas Hirschmüller, Sara Joosten, and Regina Koller, advancing collective work in discrete mathematics and optimization theory.
Prof. Dr. Bernd Schmidt is a Chair holder in Nonlinear Analysis at the University of Augsburg , Faculty of Mathematics, Natural Sciences and Technology. His research focuses on multiscale methods, elasticity theory, and calculus of variations, with applications to materials science and continuum mechanics. Diploma in Mathematics, Free University of Berlin PhD, Max Planck Institute for Mathematics in the Sciences (2003-2006) Postdoc, California Institute of Technology (2006-2007) Assistant Professor, Technical University of Munich (2007-2011) Full Professor, University of Augsburg (2011-present) Schmidt's work bridges atomistic models with continuum theories, particularly in deriving nonlinear elasticity models for thin structures like plates and rods. His research addresses problems in fracture mechanics, pattern formation, and material stability through rigorous mathematical analysis and Γ-convergence techniques. Recent publications highlight his focus on von Kármán equations, Winterbottom shapes, and NLS approximations for lattice systems. He has contributed to understanding brittle fracture in nanowires, geometric linearization of incompressible materials, and energy minimization in multi-layered structures. Scientific Awards : Max Planck Society's Otto Hahn Medal (2006) GAMM's Richard von Mises Prize (2009) Schmidt leads a research team including David Santiago Correa-Cardeño, Federico Cianci, Johannes Rimmele, and Matthias Ruf. His work has been supported by grants from German and international research foundations.
Professor Malte A. Peter is a distinguished faculty member at the University of Augsburg, holding a professorship in Applied Analysis within the Faculty of Mathematics, Natural Sciences, and Materials Engineering. He serves as Vice-director of the Centre for Advanced Analytics and Predictive Sciences and is a member of the board of directors of the AI Production Network at the University of Augsburg. His leadership extends to international collaborations as a Local representative of the Association of Applied Mathematics and Mechanics (GAMM) and as an Associate editor of Nature Scientific Reports. His research spans mathematical modeling of wave phenomena, homogenization theory, and multiscale analysis. Key areas include water wave scattering, periodic homogenisation, physico-chemical mechanisms in multiscale media (porous media, biological cells), microfluidics, and materials science. His work bridges theoretical mathematics with practical applications in engineering and physics, particularly in understanding wave propagation through complex media and developing mathematical frameworks for evolving microstructures. Peter's publication record demonstrates consistent advancement in wave scattering theory, with recent work focusing on multiple wave scattering in locally resonant materials, homogenization of evolving microstructures, and computational methods for complex material behavior. His research shows increasing interdisciplinary collaboration, particularly with physicists and engineers working on metamaterials, wave energy applications, and material characterization. The trajectory indicates growing emphasis on computational implementations of theoretical frameworks. Life membership at Clare Hall, University of Cambridge (2023) Visiting fellowship at Clare Hall, University of Cambridge (2023) Gavin Brown Best Paper Prize of the Australian Mathematical Society (2021) Bremer Studienpreis 2007 (Rotary Club Bremen–Roland Prize) (2008) Admission to the German National Academic Foundation (2001) As leader of the Modelling and Simulation workgroup, Peter directs research on mathematical approaches to complex physical phenomena. His current externally funded projects include 'Novel approaches for the multidimensional convexification of inelastic variational models for fracture' (DFG-SPP 2256) and 'Effective factorisation techniques for matrix functions' (H2020-EU.1.3.). His previous projects have addressed carbon fiber reinforced concrete, lipid membrane dynamics, and electromagnetic emissions from crack propagation. His research program maintains strong international connections, particularly with Australian institutions and the Isaac Newton Institute. Peter leads the 'Workgroup Prof. Dr. M. A. Peter - Modelling and simulation' at the University of Augsburg, which includes research associates Dr. Tanja Lochner, Dr. Sophie Thery, and Lucas Fix, along with computational mathematics specialists Dr. Loïc Balazi and Timo Neumeier. The group collaborates extensively with international partners, particularly through the Isaac Newton Institute programmes and Australian research institutions. Current projects focus on mathematical frameworks for wave scattering, homogenization of evolving microstructures, and computational methods for material failure analysis.
Shaimaa Monem is a PhD student at the Computational Methods in Systems and Control Theory group, Max Planck Institute for Dynamics of Complex Technical Systems , Germany, and a Lecturer at the National Institute of Laser Enhanced Science, Cairo University , Egypt. She holds a MSc in Laser Physics (Cairo University, 2014), a Post-Graduate Diploma in Mathematical Science and Physics (Cape Town University, 2012), and a Diploma in Laser Physics (Cairo University, 2009). Research Focus: Accelerating 3D physics-based simulations of deformables using snapshots-based and neural networks reduced subspaces for computer graphics applications. Academic Experience: Assistant Lecturer (2014–present) and Teaching Assistant (2007–2014) at Cairo University. Key Contributions: Co-authored a 2020 publication on sustainable syngas production optimization, leveraging mathematical models for industrial applications. Her work integrates computational methods, control theory, and interdisciplinary projects like fluid-structure interaction and energy systems.
Prof. Dr. Sergey Chuiko serves as a Professor at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany, where he leads research within the Computational Methods in Systems and Control Theory group. His research spans interdisciplinary domains at the intersection of mathematics and engineering, with core expertise in: Mathematical modeling of complex technical systems Numerical methods for control theory applications Algorithm development for dynamical system analysis Computational optimization in control engineering His work focuses on translating theoretical control frameworks into practical computational solutions for industrial-scale systems. He maintains active collaboration with engineering departments across European technical universities while operating from his office (S3.05) at the Max Planck campus. Prof. Chuiko's research group specializes in developing high-performance computational tools for real-time control system design, with particular emphasis on stability analysis and robust controller synthesis for nonlinear dynamical systems.
پژوهشگر ارشد
Dr. Pavel Dvurechensky is a Research Fellow at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) since 2015 and a member of Math+, the Berlin cluster of excellence. His research focuses on theoretical and applied aspects of optimization algorithms, particularly first- and second-order methods for convex and non-convex large-scale problems. 2023: Habilitation in mathematics at Humboldt University Berlin 2014-2015: Research assistant at Institute for Information Transmission Problems, Moscow 2009-2015: Junior researcher at Moscow Institute of Physics and Technology His work addresses stochastic optimization, optimal transport, distributed computing, and applications in machine learning, energy systems, and traffic modeling. He has contributed to complexity analysis of mirror descent variants, barrier methods for non-convex problems, and high-probability bounds in heavy-tailed noise scenarios. Recent publications appear in top venues like ICML, NeurIPS, and Mathematical Programming. Selected Scientific Awards: Habilitation in mathematics (2023) He has taught courses on modern optimization at Humboldt University and Higher School of Economics, covering gradient methods, mirror descent, and optimal transport. Collaborations include projects with Math+ cluster on energy system equilibria and brain signal analysis.
پژوهشگر ارشد
Harshit Jitendra Motwani is a Postdoctoral Researcher at the Max Planck Institute for Software Systems (MPI-SWS) , Germany. Previously, he was a Postdoctoral Fellow at the Hong Kong University of Science and Technology (HKUST) (2023-2024), following doctoral research at Ghent University (2021-2023) and earlier engagements at HKUST, Ghent University, and the University of Bristol . Education : PhD in Mathematics: Algebra and Geometry from Ghent University (2021-2023), Thesis on Algebro-Geometric Algorithms for Program Synthesis; Integrated BSc and MSc in Mathematics and Computing from IIT Kharagpur (2015-2020). Research Focus : Integrates mathematics into computational domains, particularly Computational Algebraic Geometry , Formal Verification , and Tensors . His work spans program synthesis , tensor networks , conditional independence models , and control theory applications . Publications : Recent contributions include algorithmic advancements in formal methods (FM, AAAI, LAGOS), algebraic statistics (IMRN), and quantum computing (SIGMA). His research combines symbolic computation with practical software engineering challenges. Awards & Honors : IEEE Computer Society Larson Best Paper Award (2023) ACM SIGPLAN Distinguished Paper Award (2023) Young Researcher of the Heidelberg Laureate Forum (2023) INSPIRE Scholarship (2015-2020) Teaching : Guest Lecturer at HKUST, Teaching Assistant at RPTU Kaiserslautern-Landau and IIT Kharagpur. Mentored multiple bachelor's projects at Ghent University and IIT Kharagpur.
Professor Jens Limpert serves as Head of Fiber & Waveguide Lasers at Friedrich-Schiller University Jena, where he leads cutting-edge research in advanced laser systems. His work spans both fundamental optical physics and practical industrial applications, with particular emphasis on pushing the boundaries of power, efficiency, and precision in fiber laser technology. Professor Limpert's primary research interests lie in high-power fiber laser systems, with significant contributions to multicore fiber technology, ultrafast pulse generation, and coherent beam combination. His work addresses critical challenges in transverse mode instability, nonlinear optics, and extreme ultraviolet generation, bridging the gap between theoretical understanding and practical implementation in industrial laser systems. His research has enabled significant advancements in laser power scaling while maintaining beam quality and stability. Analysis of Professor Limpert's recent publications reveals a strong focus on power scaling of fiber laser systems through multicore architectures, with increasing emphasis on industrial applications. His work demonstrates consistent innovation in overcoming fundamental limitations of single-core fiber lasers, particularly through coherent and incoherent beam combination techniques. The research spans from fundamental physics of mode instabilities to practical manufacturing of specialty fibers and complete laser systems for scientific and industrial use. Professor Limpert actively collaborates with numerous researchers across multiple institutions, as evidenced by his extensive co-authorship network. While specific grant information isn't provided in the source text, his prolific publication record suggests substantial research funding supporting his laboratory's activities. His work appears to have significant industrial relevance, particularly in laser manufacturing and materials processing applications. Professor Limpert leads the Fiber & Waveguide Lasers group at Friedrich-Schiller University Jena, which appears to be a well-established research team with expertise spanning fiber design, laser physics, nonlinear optics, and ultrafast laser applications. The group maintains strong industry connections while pursuing fundamental research advances in laser technology.
Thorsten Hohage is a Professor at the Institute of Numerical and Applied Mathematics, Georg-August-Universität Göttingen, and a Max Planck Fellow at the Max Planck Institute for Solar System Research. His work bridges inverse problems, numerical analysis, and wave equation modeling. Research interests focus on computational methods for inverse problems in helioseismology, aeroacoustics, and imaging. Recent projects include iterative holography for solar differential rotation, phase retrieval in X-ray and EUV imaging, and regularization techniques in Banach spaces. Collaborations span institutions like Zuse Institute Berlin and Johannes-Kepler University Linz. Key publications since 2022 address viscous-inertial solar waves, phaseless scattering, and learned boundary conditions. His work employs advanced numerical algorithms for heterogeneous materials and dispersive media, with applications in astrophysics and biomedical imaging.
دانشیار
Jiaqi Liu is an Associate Professor in the Department of Computer Science and Engineering at Southern University of Science and Technology in Shenzhen, China. His research spans multiple domains within artificial intelligence, with a particular focus on autonomous systems, multimodal learning, and computer vision. He maintains active collaborations with researchers across China and internationally, particularly with Jian Sun and Peng Hang on autonomous driving projects. Dr. Liu's research interests encompass a broad spectrum of AI and computer science topics. His work in autonomous driving involves developing sophisticated decision-making frameworks for cooperative vehicle systems. In multimodal learning, he has pioneered approaches for handling missing modalities and creating adaptive fusion networks. His signal processing research includes innovative methods for sleep staging and EEG analysis using dynamic mode decomposition techniques. Additional research areas include photonic computing accelerators, graph neural networks, and quantum neural networks. The publication trend shows significant growth in output quality and quantity, with numerous papers in top-tier venues including IEEE Transactions, CVPR, AAAI, and IJCAI. His work demonstrates a strong interdisciplinary approach, bridging computer science with applications in healthcare, robotics, and telecommunications. Recent publications indicate increasing focus on the integration of large language models with reinforcement learning for autonomous systems. Dr. Liu has received recognition through publications in high-impact journals and conferences including: IEEE Transactions on Intelligent Transportation Systems IEEE Robotics and Automation Letters Expert Systems with Applications CVPR (Computer Vision and Pattern Recognition) AAAI Conference on Artificial Intelligence His research program involves collaborations across multiple domains, with current projects focusing on language-guided autonomous driving, multimodal sentiment analysis, and advanced signal processing techniques. He leads research efforts in developing novel deep learning architectures for complex real-world problems, particularly in the domains of autonomous systems and healthcare applications.
Tiago Pereira da Silva is a full Professor at the University of São Paulo (USP) specializing in dynamics on complex networks. His research spans theoretical and applied mathematics, with significant contributions to dynamical systems and random matrix theory. Education PhD in Applied Mathematics, University of Potsdam, Germany Research Focus : Professor Pereira investigates collective behavior in complex networks, ergodic theory, and Fermi acceleration. His work integrates mathematical rigor with real-world applications in network science and physical systems. Publication Trends : Recent works demonstrate interdisciplinary impact, combining mathematical modeling with public health (COVID-19 vaccine dosing optimization) and theoretical physics (heterogeneously coupled maps). His methodological expertise in dynamical systems and differential equations underpins diverse applications.
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