Professor Stephan Theobald is a leading academic in Hydraulic Engineering and Water Resources Management at the University of Kassel , where he has served as Head of Department since 2005. His work focuses on numerical modeling of fluid dynamics , automated reservoir control systems , and flood risk management . Key Research Areas : Numerical Methods for Fluid Dynamics Hydropower Optimization Climate Change Adaptation in Water Management 3D Morphodynamic Simulations Academic Recognition : Prize for Water Management (2000) Science Prize for Hydraulic Engineering (1999) Recent Publications : 2024 papers on sediment transport in river bifurcations 2023 studies on hybrid hydropower plant analysis 2022-2023 works on predictive flood control systems
Sarah Neuwirth is a tenured Professor for Computer Science at Johannes Gutenberg University Mainz (JGU) and a Visiting Researcher at the Jülich Supercomputing Centre. She manages JGU's High Performance Computing (HPC) division, coordinates regional/national HPC activities, and represents JGU in NHR, Gauss-Allianz, and HPC committees. Education : PhD (Dr. rer. nat.) in Computer Science (2018), Heidelberg University Diplom in Computer Science (2012), University of Mannheim Bachelor of Science in Computer Science (2010), University of Mannheim Research Interests : Parallel File and Storage Systems Modular Supercomputing (resource disaggregation/virtualization) Performance Engineering High Performance Computing Networking Reproducible Benchmarking Parallel I/O Publications Trends : Her work focuses on HPC performance modeling, parallel I/O optimization, modular supercomputing, network characterization, and reproducible benchmarks. Key themes include resource disaggregation, automated workflows, and data-intensive distributed applications. Scientific Awards : 2023 PRACE Ada Lovelace Award for HPC ZONTA Science Award 2019 Grants & Leadership : She leads the High Performance Computing division at JGU, participated in European DEEP projects, and serves on SC conference committees.
Professor Hendrik Dietz holds the Chair of Biomolecular Nanotechnology at the Technical University of Munich (TUM) , affiliated with the TUM School of Natural Sciences and the Munich Institute of Robotics and Machine Intelligence . His research focuses on constructing synthetic molecular devices and machines through DNA origami and self-assembly principles. Research Themes DNA origami for programmable nanodevices Self-assembly inspired by natural molecular systems Molecular visualization with cryo-EM Applications in medicine and synthetic biology Key Article Trends : Dietz's work explores DNA-based rotary motors, virus-trapping shells, and bio-inspired vesicle production. His recent articles highlight integrations of DNA origami with electrochemical sensing, deep learning, and transmembrane transport systems. Scientific Awards ERC Consolidator Grant (2016) Gottfried Wilhelm Leibniz Prize (2015) Hoechst Lecturer Scholarship (2012) Arnold Sommerfeld Award (2010) ERC Starting Grant (2010) Collaborations and Grants : He receives funding from the Deutsche Forschungsgemeinschaft (DFG) via the Excellence Clusters CIPSM and NIM, SFB863, and the Leibniz Prize program, as well as the European Research Council. Dietz collaborates with institutions like Harvard Medical School and the Max Planck School Matter to Life.
Kamyar Sarshar is a Professor of Business Informatics at the Hamburg School of Business Administration (HSBA) since January 2014, serving as Academic Director of the Bachelor's program in Business Informatics within the Department of Technology & Markets. His educational background includes: Computer Science degree from the University of Hamburg MBA from Cardiff University, United Kingdom PhD from the Institute of Business Informatics in Saarbrücken Prior to HSBA, he worked as a Managing Consultant at Logica (now CGI), leading cross-industry process management projects. Research interests focus on: Business Process Management E-Business IT in Healthcare His work emphasizes empirical evaluation of modeling techniques like Event-driven Process Chains and Petri nets, particularly in healthcare applications and end-user usability. Publications from 2004-2008 reveal consistent contributions to business process modeling methodology, with strong empirical validation across healthcare, energy, and construction sectors, highlighting practical applicability and user-centered design principles. No scientific awards are documented in the provided materials. Information regarding student supervision, research grants, laboratories, or collaborative teams is not specified in the source text.
Dr. Marika Karbstein is a Researcher at the Zuse Institute Berlin (ZIB), where she has been employed since April 2006. Affiliated with the DFG Research Center Matheon "Mathematics for key technologies" from 2006-2014, she earned her doctoral degree in Mathematics from Technische Universität Berlin in 2013. Her work bridges theoretical optimization and practical public transport applications. Her academic background includes: 1999-2005: Studies of Applied Mathematics (Wirtschaftsmathematik) at Technische Universität Berlin 2003-2006: Student assistant at Konrad-Zuse-Zentrum Berlin 2013: Doctoral degree in Mathematics (Dr. rer. nat), Technische Universität Berlin Dr. Karbstein specializes in mathematical optimization for public transport systems, focusing on strategic planning, service design, and passenger behavior modeling. Her research integrates timetabling, line planning, and passenger routing through advanced integer programming and network optimization techniques. She develops practical solutions for infrastructure design, crew scheduling, and fare planning, emphasizing real-world applicability in urban transport networks. Her methodology combines theoretical rigor with implementation-focused approaches to improve system efficiency and user experience. Her publication record shows consistent innovation in periodic timetable optimization and integrated transport modeling. Early work established foundations in Steiner tree problems for transport networks, evolving into sophisticated frameworks for passenger routing and line planning. Recent contributions emphasize direct connections and transfer minimization, reflecting industry needs for seamless passenger journeys. The research demonstrates strong interdisciplinary connections between operations research, computer science, and transportation engineering. Her scientific recognition includes: Diploma Thesis Award of the German Operations Research Society (2006) Runner-Up for Richard-Rado-Prize (2014) Dissertation Award of German Operations Research Society (2014) VBKI Wissenschaftspreis (2014) Tucker Prize Finalist (2015) Best Paper Award at ATMOS 2013 As a core member of the DFG Research Center Matheon, Dr. Karbstein contributed to major collaborative projects funded by the German Research Foundation. Her work with Ralf Borndörfer at ZIB has led to practical implementations including Potsdam's 2010 line plan optimization. While specific grants aren't detailed, her research has been sustained through institutional support at ZIB and Matheon's interdisciplinary framework. She actively collaborates with transport operators to translate theoretical advances into operational improvements. Dr. Karbstein operates within ZIB's renowned applied mathematics environment, leveraging its high-performance computing resources. Her work extends through Matheon's consortium connecting Berlin's mathematics community. Current research focuses on integrating passenger behavior models with real-time scheduling systems, advancing the frontier of data-driven transport optimization.
Christina Büsing is a Professor in Combinatorial Optimization at RWTH Aachen University. She leads the Teaching and Research Group on Combinatorial Optimization and is a principal investigator in the UnRAVeL Graduate College. Her research focuses on optimization under uncertainty , robust optimization , and combinatorial optimization , with applications to healthcare , energy systems , and transportation logistics . Alumni of TU Berlin, WWU Münster, and Universidad Complutense de Madrid Junior Professor for Robust Planning in Medical Care at RWTH Aachen (2016-2021) Her methodological expertise spans exact algorithms , heuristics , and complexity theory , with recent publications addressing network flows, facility location, and healthcare scheduling. She has received awards for teaching excellence and gender equality advocacy. 2022 Brigitte Gilles Award for women in science 2019 FAMOS Award for family-friendly leadership 2018 Best Teaching Award at RWTH Aachen Her work combines theoretical rigor with practical applications in urban railway traffic management , solar power systems , and agent-based pandemic response modeling .
Niklas von der Aßen is a Professor and Head of the Institute at the Chair and Institute of Technical Thermodynamics, RWTH Aachen University. His research focuses on energy systems, sustainable technology, and carbon capture. University: RWTH Aachen University Institute: Chair and Institute of Technical Thermodynamics Email: niklas.vonderassen@ltt.rwth-aachen.de His recent work includes nationwide heat pump deployment analysis, stochastic energy system optimization, and green chemistry metrics. Publications highlight interdisciplinary approaches to sustainability and thermodynamics. Current affiliations and responsibilities include leading the institute and advancing research in energy and environmental technologies.
Professor Patrick Rinke leads the Chair of AI-based Materials Science at the Technical University of Munich (TUM), within the TUM School of Natural Sciences and Department of Physics. His research group develops advanced electronic structure and machine learning methods to address critical challenges in materials science, surface science, physics, chemistry, and nanoscience. Professor Rinke's research spans multiple cutting-edge domains including electronic structure theory development, machine learning applications for materials science, data-driven materials discovery, biomaterials engineering, atmospheric science applications, clean energy materials, and hybrid materials systems. His work integrates advanced computational methods with practical applications across diverse scientific fields, particularly focusing on how artificial intelligence can transform traditional materials research. Analyzing his recent publications reveals strong trends in applying machine learning techniques to materials discovery, with particular emphasis on Bayesian optimization methods, active learning approaches for molecular data, and efficient dataset generation strategies. His research spans from fundamental electronic structure theory to practical applications in biomaterials, atmospheric science, and renewable energy technologies. Professor Rinke has received several prestigious awards including the August-Wilhelm Scheer visiting professorship (2017), a German Science Foundation research scholarship (2007), the Outstanding Postdoctoral Research Achievement Award from UC Santa Barbara (2009), recognition as an Outstanding Referee for Physical Review journals (2014), and the Institute of Physics Computational Physics Group Thesis Prize (2003). Professor Rinke actively contributes to the academic community through teaching and supervision. For the Winter term 2025/26, he is teaching courses including Academic Writing Skills, Introduction to Machine Learning for Materials Science, Current Topics in AI-Based Materials Science, and Machine Learning for Natural Sciences. His research group includes several team members working on diverse projects spanning the intersection of AI and materials science.
Sandrine Blazy is a Professor in the Computer Science Department at the University of Rennes, France. She is a member of CELTIQUE (also referred to as Epicure), a joint project-team with Inria Rennes Bretagne Atlantique and the IRISA laboratory. Since 2021, she has served as deputy director of the IRISA CNRS UMR 6074 laboratory and will be the general chair for POPL 2026, which will be held in Rennes. She is also a member of the editorial board of the LMCS journal. Dr. Blazy completed her PhD at CNAM (Conservatoire National des Arts et Métiers) in 1993 with a thesis titled "La spécialisation de programmes pour l'aide à la maintenance du logiciel" (Program Specialization for Software Maintenance Assistance). She later completed her Habilitation à diriger des recherches (HDR) in 2008 at the University of Évry Val d'Essonne with a thesis titled "Sémantiques formelles" (Formal Semantics). Her research focuses on the formal verification of program transformations and semantic properties of programming languages, particularly in the context of the CompCert compiler and Verasco static analyzer. She develops mechanized semantics using the Coq (or Rocq) proof assistant to ensure software correctness and security. A prime application domain of her work is software security, including constant-time programming for cryptographic applications and software obfuscation techniques. Her teaching includes mechanized semantics (in Coq), functional programming (in OCaml), formal methods (using Why3), and software vulnerabilities. Dr. Blazy's publication record from 2019-2025 shows a sustained focus on verified compilation techniques, particularly in preserving security properties during compilation. Her work bridges theoretical formal methods with practical compiler implementation, resulting in tools that have real-world impact in safety-critical systems. She has made significant contributions to the CompCert formally verified compiler project, with particular attention to constant-time preservation for cryptographic applications and JIT compilation verification. Her scientific achievements have been recognized with several major awards: CNRS Silver Medal (2023) Lucas Award from Formal Methods Europe (2023) ACM SIGPLAN Programming Languages Software Award for CompCert (2022) ACM Software System Award for CompCert (2021) Dr. Blazy has been actively involved in the programming languages research community, serving on numerous program committees for major conferences including POPL, ICFP, PLDI, and CPP. She has mentored students and contributed to education through teaching mechanized semantics and formal methods. Her work with the CompCert compiler has led to practical applications in safety-critical systems, with industry collaborations documented in publications like "CompCert: Practical experience on integrating and qualifying a formally verified optimizing compiler" (ERTS 2018). She leads research within the CELTIQUE project team, which focuses on developing trustworthy software using deductive verification. Her team works on advancing the state of the art in formal verification of compilers and static analyzers, with applications in security-critical domains including cryptographic implementations and safety-critical embedded systems.
Professor Hoang Xuan Phu is a renowned mathematician affiliated with the Institute of Mathematics , Vietnam Academy of Science and Technology , where he has served since 1984 (Researcher), 1992 (Associate Professor), and 1996 (Professor). He is an elected member of multiple prestigious academies: the Heidelberg Academy of Sciences and Humanities (2004), Bavarian Academy of Sciences and Humanities (2010), TWAS - The World Academy of Sciences (2013), and acatech - National Academy of Science and Engineering, Germany (2019). His email contact is hxphu@math.ac.vn and phu@iwr.uni-heidelberg.de . Education : University of Leipzig (Diploma 1979, PhD 1983, Habilitation 1987) Research Areas : Optimization, Optimal Control, Functional Analysis, Numerical Analysis, Rough Analysis Applications : Inventory Problems, Hydroelectric Power Plant Control, Robotics, Open Channel Hydraulics Editorial Roles : Editor-in-Chief of Vietnam Journal of Mathematics (2011-2022), Honorary Editor-in-Chief (2023-present), Associate Editor for multiple journals His recent publications focus on convex hull algorithms, optimal path planning, and function perturbation analysis, reflecting his expertise in mathematical optimization and computational methods. He has organized numerous international conferences on High Performance Scientific Computing in Hanoi (2000-2024) and Optimization & Scientific Computing (2003-2024).
Quim Peña is a postdoctoral researcher at the Department of Experimental Molecular Imaging (RWTH Aachen University). He obtained his PhD in Chemistry from Universitat Autònoma de Barcelona (Spain) and Aix-Marseille Université (France) in 2019, focusing on metal-based chemotherapeutics. Current research focuses on nanomedicine for enhanced drug delivery in cancer therapies Specializes in polymeric micelles and prodrug synthesis Recent work involves RGD-coated microbubbles and ultrasound-mediated delivery Contributed to 89Zr-radiolabeled micelle development for personalized breast cancer treatment His publications (2021-2025) emphasize polymer-drug conjugates , multidrug delivery systems , and theranostic applications . Collaborative projects include collaborations with Twan Lammers, Fabian Kiessling, and Josbert Metselaar. 2025: Hydrophobic ion pairing for micelle drug co-loading 2025: Multidrug micelles for brain tumor treatment 2024: RGD-coated microbubbles for blood-brain barrier delivery 2023: Transformative materials for interfacial drug delivery Scientific recognition includes the 2025 CRS Award for best short talk . His work targets cancer nanomedicine with emphasis on side-effect reduction through advanced delivery systems.
Dr. André Artelt is a researcher at the University of Bielefeld within the Faculty of Engineering and affiliated with the Machine Learning Group at the Center for Cognitive Interaction Technology (CITEC). His work focuses on Explainable AI (XAI), particularly counterfactual explanations, and their applications in critical infrastructure like water distribution networks. Current Research: Explainable AI Counterfactual explanations Water network monitoring Physics-informed graph neural networks Scientific Contributions: His recent publications explore reinforcement learning for water pump scheduling, scalable graph neural networks for water systems, and benchmark frameworks like EPyT-Flow. He investigates how training data affects explanation quality and develops tools for robust counterfactual reasoning. Awards: Project Lamarr Fellowship
Oliver G. Ernst is a Professor of Numerical Analysis at Technische Universität Chemnitz . His research focuses on Numerical Analysis , Uncertainty Quantification , and Inverse Problems , with applications in Thermo-Hydro-Mechanical (THM) processes , Electromagnetics , and Stochastic Partial Differential Equations . He is associated with the Numerical Analysis group at TU Chemnitz. Key Research Areas : Efficient numerical methods for PDEs Krylov subspace techniques Stochastic finite element methods Multi-physics modeling Geoscientific applications Recent Publications (2025-2010): THM simulations under uncertainty Neural network PDE solvers Bayesian inversion frameworks Rational Krylov algorithms Deflated restarting strategies Collaborations : TU Bergakademie Freiberg University of Manchester Technical University of Munich University of Maryland University of Geneva Software Development : Contributor to OpenGeoSys platform Developer of FEMALY MATLAB library Academic Recognition : h-index 32, i10-index 66, with over 4423 citations since 2020.
Prof. Dr. rer. nat. Fritz E. Kühn is a Professor of Molecular Catalysis at the Department of Chemistry within the TUM School of Natural Sciences at Technische Universität München (TUM). His research spans organometallic chemistry, medicinal chemistry, and molecular catalysis, focusing on carbene ligated metal precursors for task-specific applications in catalysis and biomedical fields. Current research emphasizes oxidation/hydrogenation catalysis with transition metals Active collaborations with industrial partners for small molecule activation Dean of Studies at TUM School of Chemistry since 2016 Spokesperson for TUM Graduate School (Chemistry department) Recent publications highlight advancements in gold(I) NHC complexes for cancer therapy , single-atom rhenium catalysts , and asymmetric epoxidation systems . His work aligns with UN SDGs through sustainable catalytic processes. Scientific recognition includes the Otto Roelen Medal and Hans Fischer Prize . Key research tools include N-heterocyclic carbenes, computational modeling, and industrial process optimization.
Paul Kotyczka is a Professor at the Technical University of Munich (TUM) in the School of Engineering and Design , Department of Automatic Control Engineering. He leads the Energy-based Modeling and Control Working Group and focuses on modeling, geometric discretization, and control of multi-physical systems, with expertise in nonlinear and passivity-based control. His work spans applications in robotics, mechatronics, and process engineering. Education : Dipl.-Ing. in Electrical Engineering (TUM, 2005), Dr.-Ing. (TUM, 2010), Habilitation (Dr.-Ing. habil., TUM, 2019). Research : Core areas include port-Hamiltonian systems, predictive control of active chassis, structural mechanics modeling, and numerical methods for control. His projects address autonomous driving, distributed parametric systems, and passivity-based control of switching nonlinear systems. Awards : Held a Marie Sklodowska-Curie Fellowship (2015–2017). Grants : Leads DFG projects (e.g., HermInE, INFIDHEM), MSCA-IF, and Franco-German Doctoral Program on port-Hamiltonian systems. Labs : Head of the Energy-based Modeling and Control group at TUM, collaborating internationally (e.g., IIT Bombay, Grenoble INP, LCIS France).
