Find Academic Supervisors

• Fluid Power Engineering
• Hydraulic Systems
• Tribology
• +4 more

Prof. Dr.-Ing. Katharina Schmitz serves as Institute Director and Vice Dean at the Institute for Fluid Power Drives and Systems, RWTH Aachen University. Her leadership within the Production Technology Cluster and extensive contributions to fluid power engineering establish her as a leading authority in mechanical engineering research and education. Her research spans fluid power systems, hydraulic component design, tribology, and physics-informed machine learning applications. She pioneers sustainable propulsion solutions through bio-hybrid fuels research while addressing fundamental challenges in polymer material behavior under hydraulic stresses. Current work focuses on carbon-neutral heavy-duty transportation, physics-based neural networks for lubrication modeling, and advanced control systems for electro-hydraulic actuators. Analysis of her 15 most recent publications reveals a dominant trend toward integrating physics-based modeling with deep learning to solve complex engineering problems. Her team consistently develops novel frameworks for cavitation prediction, flow rate determination, and material compatibility assessment - significantly advancing fluid power system reliability, efficiency, and digitalization. Scientific recognition includes: GfT Förderpreis 2023 for experimental and simulative investigation of partially hydrostatic relieved contacts in variable speed axial piston machines As head of the Institute for Fluid Power Drives and Systems, she leads cutting-edge research in sustainable fluid power technologies. The institute maintains strong industry partnerships while driving innovation in hydraulic component design, digital twins for condition monitoring, and next-generation propulsion systems through its position within RWTH Aachen's Production Technology Cluster.

Christina RothView profile

Professor

• Materials Science
• Electrochemical Engineering
• Energy Systems
• +5 more

Christina Roth is a Professor and Chair of Materials Process Engineering at the University of Bayreuth's Faculty of Engineering. Her research focuses on materials science and electrochemical energy systems, including fuel cells, redox flow batteries, CO₂ electro-reduction, and advanced materials synthesis via templating and electrospinning. She leads projects on operando methods to study catalytic processes and material degradation mechanisms. Her work bridges fundamental electrochemistry with applied energy technologies. Key research areas include developing high-performance electrocatalysts, optimizing electrode structures, and understanding reaction mechanisms under industrial conditions. Recent studies emphasize operando techniques to monitor catalyst behavior during operation, enhancing reliability in high-current-density electrolysis systems. Collaborations span academia and industry, addressing challenges in sustainable energy storage and conversion. Dr. Roth's expertise is reflected in over 150 publications across top journals like Nature Materials , ACS Catalysis , and Journal of the Electrochemical Society . She actively contributes to conferences such as the livMatS Colloquium series and serves on the Scientific Advisory Board. Her lab focuses on innovative materials for next-generation energy systems, emphasizing scalability and environmental impact.

• Numerical Analysis
• Uncertainty Quantification
• Inverse Problems
• +3 more

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.

• Hydrogeology
• Environmental Geosciences
• Subsurface Hydrology
• +6 more

Olaf A. Cirpka is a Full Professor of Hydrogeology at the University of Tübingen, Germany, within the Faculty of Science's Department of Geosciences. He holds a Diploma in Geoecology (University of Karlsruhe, 1992) and a Doctor of Engineering in Civil Engineering (University of Stuttgart, 1997). His career includes postdoctoral research at Stanford University (1998–2000), adjunct roles there until 2009, and leadership roles such as Head of the Emmy-Noether Junior Research Group (2000–2004) and Subsurface Hydrology Workgroup at Eawag (2004–2008). He is a Fellow of the American Geophysical Union (2015) and served as Spokesperson for the Research Training Group 1829 (2012–2021). Research Interests: His work focuses on subsurface hydrology, reactive transport modeling, biogeochemical processes in aquifers, and climate impacts on groundwater systems. He integrates numerical modeling, field experiments, and geophysical methods to address challenges in contaminant fate, hyporheic zone dynamics, and sustainable groundwater management. Articles Trends: Recent publications emphasize innovative methods for quantifying subsurface processes (e.g., VTraFlux, electrical conductivity tracers), climate-driven groundwater changes, and microbial-driven biogeochemical reactions. His work bridges experimental hydrology with computational tools to advance understanding of complex environmental systems. Awards & Grants: AGU Fellowship (2015) highlights his scientific contributions. He has led numerous research initiatives, including the Advect As project on arsenic dynamics and the Research Training Group on integrated hydrosystem modeling. Grants and collaborations span interdisciplinary environmental research. Labs & Teams: Directs the Hydrogeology group at Tübingen and collaborates with international institutions like Stanford, ETH Zürich, and Eawag. His research integrates field campaigns, lab experiments, and numerical simulations to address real-world hydrogeological challenges.

Rayna DimitrovaView profile

Assistant Professor

• Verification
• Reactive Systems Synthesis
• Control and Robotics
• +3 more

Rayna Dimitrova is a Tenure-track faculty member at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Previously, she held positions as Lecturer (Assistant Professor) at the University of Sheffield and University of Leicester, and postdoctoral roles at the University of Texas at Austin and the Max Planck Institute for Software Systems. She earned her PhD from Saarland University. Her research focuses on formal methods, including verification and synthesis of reactive systems, applications to control and robotics, quantitative analysis of probabilistic systems, and information-flow security. Key interests include strategic synthesis under partial observability, probabilistic uncertainty, and continuous dynamics, with applications to autonomous systems. She has served in numerous prestigious roles, including PC co-chair for VMCAI 2024, HYPER 2023, and SMT 2018. Her awards include the RS3 Best Paper Award (VMCAI 2012) and nominations for ETAPS (TACAS 2015) and EMSOFT (2014) Best Paper Awards. Her research group includes PhD students Rafael Dewes, Philippe Heim, and Saleh Soudijani. She has taught courses on reactive synthesis, program analysis, and decision procedures at multiple institutions, including the University of Sheffield and TU Kaiserslautern.

• Power Systems
• Smart Grids
• Synchronized Measurement Technology
• +6 more

Vladimir V. Terzija is a prominent researcher specializing in power systems engineering with a focus on smart grid technologies, synchronized measurement systems, and power system protection. His extensive publication record spans over two decades, demonstrating continuous contributions to the field of electrical power engineering across numerous IEEE journals and conferences. Terzija's research primarily centers on advanced power system monitoring, protection, and control methodologies. His work has significantly contributed to the development of synchronized measurement technology applications, fault analysis algorithms, and state estimation techniques for modern power systems. He has pioneered approaches for wide-area monitoring systems, transmission line fault analysis, and integrating renewable energy resources into power grids while maintaining stability and reliability. His research spans from fundamental power system theory to practical implementations addressing contemporary challenges in grid operation. Analysis of his recent publications reveals a strong focus on integrating artificial intelligence and machine learning techniques into power system applications, particularly for condition monitoring, anomaly detection, and predictive maintenance. His work increasingly addresses challenges posed by the energy transition, including grid stability with high renewable penetration, multi-energy system integration, and advanced control strategies for low-inertia power systems. The interdisciplinary nature of his research connects power engineering with data science, optimization theory, and cybersecurity. Throughout his career, Terzija has collaborated extensively with researchers across Europe and internationally, as evidenced by his numerous co-authored publications with institutions worldwide. His work appears consistently in top-tier IEEE publications, indicating recognition by the power engineering community. While specific awards aren't documented in the available publication records, his sustained research productivity and influence in the field suggest significant professional recognition. Terzija has supervised numerous research projects focused on power system monitoring and control, with particular emphasis on practical implementations that bridge theoretical developments with real-world grid applications. His work on WAMS (Wide Area Monitoring Systems), fault location algorithms, and state estimation techniques has contributed to advancing grid operational capabilities. The research trajectory shows increasing focus on addressing challenges associated with renewable energy integration, grid digitalization, and maintaining stability in modern power systems. His research group appears to focus on developing advanced monitoring and control systems for power networks, with particular expertise in synchrophasor technology applications. The collaborative nature of his work suggests involvement in international research consortia addressing contemporary power system challenges, particularly those related to grid stability in systems with high renewable penetration and the development of intelligent monitoring solutions for power infrastructure.

Wolfgang RheinheimerView profile

Professor

• Ceramic materials
• Sintering technologies
• Grain boundary engineering
• +7 more

Prof. Wolfgang Rheinheimer is a Professor and Institute Director at the Institute for Ceramic Materials and Technologies , University of Stuttgart, since 2023. Previously, he held academic positions at RWTH Aachen (2022-2023), Forschungszentrum Jülich (Emmy Noether Group Leader, 2020-2022), TU Darmstadt (2020), and Karlsruhe Institute of Technology (2010-2017). Academic Rank: Full Professor Research Focus: Advanced sintering technologies, grain boundary engineering, defect chemistry, conductivity in ceramics, and microstructure evolution His research spans experimental and computational approaches to ceramic materials, with emphasis on field-assisted processing (electric/magnetic), grain boundary properties , and solid-state electrolytes . He has pioneered studies on flash sintering , cold sintering , and blacklight sintering mechanisms. Scientific Awards : Emmy Noether Fellowship (2020-2022) for establishing his independent research group His work integrates phase-field modeling with experimental characterization to optimize ceramic properties for energy applications (solid-state batteries, fuel cells) and structural uses. Collaborations include Robert Bosch GmbH and Purdue University (2018-2019 Visiting Professorship).

Severin ReizView profile

Researcher

• Mechanical Engineering
• Reactive Flow Modelling
• Parallel Computing
• +9 more

Severin Reiz is a Researcher at the School of Informatics, Technische Universität München, affiliated with the Chair of Scientific Computing (SCCS). His work spans interdisciplinary domains, combining computational methods with mechanical engineering and machine learning. Research focus: Reactive flow modeling, hierarchical matrices, and optimization in neural networks. Teaching involvement: Tutorials for Modeling and Simulation, Quantum Computing, and Parallel Computing courses. Project roles: Main Developer of ExaNIML (2018-2020), Program Manager of SPPEXA (2017-2019). He has conducted research stays at institutions like the University of Texas at Austin (2018). Additional activities include organizing the SCCS Colloquium, leading a soccer department, and volunteering with the Münchener Flüchtlingsrat.

• Network Protocols Engineering
• Cybersecurity
• Distributed Systems
• +3 more

Klaus Wehrle is a Professor of Computer Science and Head of the Communication and Distributed Systems Group (Informatik 4) at RWTH Aachen University. He holds a diploma (1999) and doctorate (2002) from the University of Karlsruhe (now KIT). His research focuses on network protocols, cybersecurity, and distributed systems, funded by DFG, ERC, EU, and industry. He leads the DFG Priority Program on Cyber-Physical Networking and holds ERC grants. Awards include Südwestmetall and FZI Dissertation Prizes. He serves on IEEE, ACM, and DFG committees. His work spans protocol engineering, network simulation, and reliable communication software. He advises the Department of Computer Science at RWTH and collaborates on projects like In-Network Computing and Industrial IoT security. His research addresses industrial systems, smart grids, and privacy-preserving data sharing.

• Biomedical Engineering
• Medical Statistics
• Ophthalmology
• +3 more

Prof. Konstantin Kotliar is a Professor at Aachen University of Applied Sciences, specializing in Biomedical Engineering and Medical Statistics. He teaches courses in Mathematics, Advanced Medical Statistics, and Space Physiology. His research focuses on retinal vessel analysis to study microvascular dysfunction in diseases such as Fabry disease, diabetes, and Alzheimer’s. Kotliar’s work bridges ophthalmology, neuroscience, and cardiovascular science, with a particular interest in developing non-invasive diagnostic tools for early disease detection. His studies often involve collaborations with global health initiatives and clinical trials, such as the EndoAfrica-NWU Study. He has contributed to understanding neurovascular coupling mechanisms and their implications for neurological disorders. Research interests include retinal vessel dynamics, cardiovascular risk stratification, and the application of statistical methods in medical diagnostics. Kotliar’s methodologies span from biomechanical modeling to machine learning-driven image analysis, emphasizing translational research with clinical relevance. His work has implications for improving therapies and preventive measures in chronic diseases.

Bernard HaasdonkView profile

Professor

• Model Reduction
• Parametrized Partial Differential Equations (PDEs)
• Kernel Methods
• +7 more

Bernard Haasdonk is a Professor at the University of Stuttgart, affiliated with the Institute of Applied Analysis and Numerical Simulation (IANS), part of the Faculty of Mathematics and Computer Science. His research focuses on model reduction techniques for parametrized partial differential equations (PDEs), kernel-based methods, numerical analysis, and machine learning applications in scientific computing. He leads a research group in numerical mathematics and has contributed to software tools like RBMatlab and KerMor. Affiliations: Institute of Applied Analysis and Numerical Simulation, University of Stuttgart Roles: Academic Researcher, Software Developer, Grant Principal Investigator His work bridges numerical simulation, machine learning, and reduced basis methods, addressing challenges in optimal control, fluid dynamics, and biomechanics. Haasdonk has held multiple funded projects, including those on kernel methods for model reduction and certified RB-ML-ROM surrogate models. Research Interests: Model reduction for PDEs, kernel methods, greedy algorithms, numerical analysis, optimal control, and applications in fluid dynamics and porous media. He emphasizes structure-preserving methods for Hamiltonian systems and data-driven approaches for surrogate modeling. Publications: Over 200 articles in journals like SIAM, BIT Numerical Mathematics, and Physica D, focusing on convergence analysis, kernel-based approximation, and reduced-order modeling. Recent trends include adaptive greedy algorithms, symplectic model reduction, and energy-conserving surrogates. Awards: IEEE PerCom 2017 Best Paper Award, Teaching Excellence Awards (2012-2017), and early-career research grants. Grants: DFG-funded projects on model reduction, SimTech Cluster contributions, and collaborations on fuel cells and biomechanics. Teams: Leads the Numerical Mathematics Research Group at IANS, collaborating with interdisciplinary teams on projects like MORCOS (Model Order Reduction of Coupled Systems) and KerMor (Kernel Methods for Model Reduction).

Felix SchindlerView profile

Researcher

• Numerical Analysis
• Machine Learning
• Scientific Computing
• +3 more

Felix Schindler is a Researcher at the Institute for Analysis and Numerical Analysis , part of the Department of Mathematics and Computer Science at the University of Münster . His work bridges numerical analysis, machine learning, and scientific computing, with a focus on model reduction for partial differential equations (PDEs), adaptive algorithms, and computational efficiency. Research Interests include: Numerical analysis of parametric and multiscale PDEs Localized reduced basis methods (LRBM) and adaptive enrichment Integration of model order reduction (MOR) with machine learning (ML) Conservative flux reconstruction techniques Development of software libraries like dune-xt and pyMOR Recent Publications highlight trends in applying deep kernel models for surrogate modeling, localized training strategies for PDE-constrained optimization, and hybrid full/reduced-order pipelines for reactive flow prediction. His work emphasizes certified error control, hierarchical adaptivity, and cross-disciplinary computational frameworks. Collaborations span institutions such as AIMS Senegal, Springer Nature, and DUNE project teams. He actively contributes to conferences like GAMM, ENUMATH, and Algoritmy.

Dirk PeschkaView profile

Researcher

• Partial Differential Equations
• Fluid Dynamics
• Materials Science
• +7 more

Dr. Dirk Peschka is a researcher at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, Germany, where he contributes to the Partial Differential Equations Research Group (FG1) . He is affiliated with the Berlin Mathematics Research Center MATH+ , the Society for Applied Mathematics and Mechanics (GAMM) , and the German Physical Society (DPG) . Research Interests Mathematical modeling of fluid dynamics and materials science using partial differential equations (PDEs). Applications in thin film dynamics, semiconductor devices, and reactive multiphase flows. Development of gradient flow frameworks and thermomechanical models via GENERIC formalism. Analysis of contact line behavior, dewetting processes, and fluid-structure interaction. Numerical methods for semiconductor simulations and geoscience applications. Publications Trends His recent work (2022–2025) emphasizes energy-based modeling of thin films, reactive flows, and semiconductor degradation. Key themes include contact line dynamics, gradient flows, and multiscale analysis of materials and fluid systems. Memberships Weierstrass Institute for Applied Analysis and Stochastics (WIAS) Berlin Mathematics Research Center MATH+ Society for Applied Mathematics and Mechanics (GAMM) German Physical Society (DPG)

Anja DrewsView profile

Professor

• Process Engineering
• Membrane Processes
• Bioprocess Engineering
• +6 more

Prof. Dr.-Ing. habil. Anja Drews is a Professor for Process Engineering in Life Science Engineering at HTW Berlin - University of Applied Sciences. She specializes in membrane processes , bioprocess engineering , and interfacial catalysis within liquid multiphase systems. Education: Dipl.-Ing. (1997), Dr.-Ing. (2004) in Process Engineering from TU Berlin Academic Career: Research Assistant at TU Berlin (2004-2008), Departmental Lecturer at University of Oxford (2009), Habilitation in Process Engineering (2010) Her research focuses on: Multiphase Reaction Engineering - Pickering emulsions Mechanistic Modeling - Filtration kinetics Membrane Bioreactors - Fouling mitigation Fluid Dynamics - Bubble-induced shear stress Biocatalytic Process Design - Enzymatic membrane reactors Carbon Capture - Direct air capture technologies Recent publications highlight trends in: Interfacial enzyme catalysis within Pickering emulsions Quantitative analysis of multiphase systems Membrane fouling mechanisms in bioreactors Process intensification through colloidal stabilization Temperature effects on nanofiltration performance Integration of reaction and separation processes

Hendrik LensView profile

Professor

• Power Systems
• Grid Stability
• Renewable Energy Integration
• +4 more

Hendrik Lens is a **Professor for Power Plant and Grid Systems** and **Director of the Institute** at the University of Stuttgart's **Institute of Combustion and Power Plant Technology (IFK)**. He leads the **Power Generation and Automatic Control (SuA) department**, focusing on advanced grid technologies and energy system optimization. His research emphasizes **grid stability**, **renewable energy integration**, and **converter control strategies**. Key contributions include studies on grid-forming converters, inertia-aware generation planning, and dynamic network equivalents. He collaborates internationally on projects like the *VerbundnetzStabil initiative* analyzing interconnected power systems. Publications span **18 journals/conferences in 2024 alone**, with a focus on smart grid technologies and decarbonization strategies. His work addresses challenges such as frequency containment reserves, distributed generation impacts, and stochastic unit commitment tools. Operates within the Institute of Combustion and Power Plant Technology, contributing to both academic and applied research in sustainable energy systems.