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Tianbai XiaoView profile

Researcher

• Numerical Analysis
• Applied Mathematics
• Kinetic Theory
• +7 more

Tianbai Xiao is a Researcher at the Karlsruhe Institute of Technology (KIT) within the Department of Mathematics and Steinbuch Centre for Computing. His work spans mesoscopic science , uncertainty quantification , and scientific machine learning , focusing on multi-scale, multi-physics problems in flow transport. His research in kinetic theory addresses nonlinear partial differential equations, hyperbolic conservation laws, and the unified modeling of continuum/rarefied flows. He develops high-performance numerical algorithms like the Unified Gas-Kinetic Scheme (UGKS) and Kinetic.jl (a finite volume toolbox for scientific computing). Current projects include mesoscopic science , stochastic data science , and physics-informed neural networks . He contributes to open-source tools including FluxReconstruction.jl for advection-diffusion methods and Langevin.jl for stochastic kinetic modeling. Publications cover Journal of Computational Physics , Engineering Fracture Mechanics , and Entropy , with preprints on arXiv in 2025 addressing force-driven flows and hybrid peridynamics. Teaching activities include the Introduction to Kinetic Theory lecture at KIT, and mentoring in the CAMMP (Computational and Mathematical Modeling Program) to develop problem-solving skills through real-world modeling tasks. He advocates for problem-based learning where students translate non-mathematical problems into mathematical language.

• Internet of Things (IoT)
• Fog Computing
• Digital Twins
• +3 more

Dimitrios Georgakopoulos is a researcher at Swinburne University of Technology and National Measurement Institute, focusing on Internet of Things (IoT), digital twins, fog computing, and smart manufacturing. His work bridges theoretical advancements with real-world applications in urban infrastructure, precision agriculture, and industrial IoT. Research Areas: IoT, Digital Twins, Fog Computing, Smart Cities, Precision Agriculture Key Contributions: Sensor sharing marketplaces, 5G-enabled smart city frameworks, metadata-assisted IoT data classification Recent Articles (2023-2025): Explore topics like digital manufacturing consistency, AI-powered roadside asset management, and deep learning for heterogeneous IoT data. Trends emphasize autonomic systems, sensor integration, and contextual data analysis. Collaborations: Frequently works with Prem Prakash Jayaraman, Ali Yavari, Abhik Banerjee, and Anas Dawod on IoT security, sensor networks, and time-sensitive applications.

• Distributed Systems
• Peer-to-Peer Networks
• Cloud Computing
• +4 more

Peter G. Kropf is a Professor in the Department of Computer Science at the University of Neuchâtel, Switzerland, with a distinguished research career spanning over three decades. His academic journey reflects significant contributions to distributed systems, peer-to-peer networks, and cloud computing, with recent focus on IoT analytics and scientific computing applications. Dr. Kropf's research interests center on Distributed Systems , Peer-to-Peer Networks , Cloud Computing , Wireless Mesh Networks , and Scientific Workflows . His work demonstrates a clear evolution from foundational distributed systems research to practical applications in environmental monitoring, IoT analytics, and large-scale scientific computing. He has maintained consistent research productivity throughout his career, with publications appearing regularly from 1990 through 2024. Analysis of his recent publications reveals a strong trend toward real-time data processing for environmental applications, IoT analytics , and cloud-based scientific workflows . His work often bridges theoretical distributed systems concepts with practical implementations, particularly in environmental monitoring and resource management contexts. The interdisciplinary nature of his research connects computer science with environmental science and hydrology. Dr. Kropf has established long-term collaborations with researchers including Gilbert Babin (15 joint publications), Pascal Felber (14 publications), and Sabina Serbu (7 publications), forming a productive research network focused on distributed systems challenges. His work has appeared in prestigious venues including IEEE Internet Computing, Future Generation Computer Systems, and Middleware conference proceedings.

Christian MendlView profile

Assistant Professor

• Quantum Computing
• Computational Physics
• Statistical Physics
• +2 more

Christian Mendl is a Rudolf Mößbauer Tenure Track Assistant Professor at the Technical University of Munich (TUM) , affiliated with the School of Computation, Information and Technology and the Institute for Advanced Study (TUM-IAS) . His career includes a postdoctoral position at Stanford University (2015-2017) under a Feodor Lynen Fellowship from the Alexander von Humboldt Foundation, a Junior Professorship at TU Dresden (2017-2019), and a PhD in Physics from LMU Munich (2012). Education : Physics and Mathematics (TUM) Appointments : Rudolf Mößbauer Assistant Professor (TUM, 2019), Junior Professor (TU Dresden, 2017), Postdoc (Stanford, 2015-2017) Research Focus : Mendl specializes in Quantum Computing , Computational Physics (tensor networks, quantum Monte Carlo, neural-network quantum states), Statistical and Non-Equilibrium Physics , and Numerical Simulation . His work bridges quantum information theory with condensed matter physics, emphasizing efficient quantum algorithms and simulators for complex systems. Scientific Contributions : Recent publications highlight advancements in quantum circuit optimization , tree tensor network simulations , block encoding of operators , and quantum-assisted optimization for problems like the capacitated vehicle routing and Toda lattice dynamics. His methods often integrate machine learning with quantum information to address challenges in Hamiltonian simulation and quantum error analysis . Awards : Alexander von Humboldt Feodor Lynen Fellowship, Boehringer Ingelheim Fonds PhD Fellowship, TopMath Graduate Program, Studienstiftung des deutschen Volkes Grants : Rudolf Mößbauer Tenure Track Fellowship (TUM-IAS), Dieter Schwarz Fellowship

Friedrich BoeingView profile

Researcher

• Hydrology
• Climate Change Impact Assessment
• Drought Monitoring
• +3 more

Friedrich Boeing is a Researcher at the Department of Hydrosystem Modeling in the Computational Hydrosystems unit of the Helmholtz Centre for Environmental Research − UFZ in Leipzig, Germany. He is simultaneously pursuing his PhD at the University of Potsdam under the supervision of Prof. Dr. Sabine Attinger, Prof. Dr. Thorsten Wagener, and Dr. Andreas Marx. PhD Candidate: University of Potsdam University: Helmholtz Centre for Environmental Research − UFZ Department: Hydrosystem Modeling His research focuses on drought quantification , water resource monitoring , and climate change impact assessment for Germany. He develops high-resolution drought indicators and leads knowledge transfer through the WIS-D project , collaborating with stakeholders across water sectors. Recent publications highlight his expertise in soil moisture dynamics , hydrological modeling , and climate-water interactions . His work appears in journals like Environmental Research Letters and Hydrology and Earth System Sciences . Key Projects: WIS-D, CLIMALERT, HOKLIM Collaborations: University of Potsdam, ICOS network, Zenodo data repository

Klaus MelchersView profile

Professor

• Personnel Selection
• Applicant Reactions
• Personality Assessment in Work Context
• +7 more

Klaus Melchers is a Professor of Work and Organizational Psychology at Ulm University, where he has held a W3 professorship since October 2012. Previously, he served as an Assistant and Senior Assistant at the Department of Psychology, University of Zurich, from 2003 to 2012. He completed his psychology studies at Philipps-University of Marburg and University College, followed by a dissertation in 2003 on stimulus processing in human learning. His research focuses on key areas in personnel selection, including applicant reactions, personality assessment in work contexts, impression management, and the effectiveness of training. He investigates how candidates respond to various selection procedures, particularly focusing on fairness, transparency, and the impact of digital tools such as video interviews and gamified assessments. The recent publication trends reveal a strong emphasis on technology-mediated interviews, applicant faking, fairness in hiring, and the validity of assessment methods. His work increasingly explores digital transformations in recruitment, including asynchronous video interviews, game-based assessments, and algorithmic bias. Themes such as psychological reattachment to work, mobile device use, and sleep also reflect a growing interest in daily work experiences and well-being. Klaus Melchers frequently collaborates with researchers such as Janine Basch, Benjamin Bill, Nina Merkl, and Martin Kleinmann. His publications appear in top journals like Personnel Psychology , Journal of Business and Psychology , and International Journal of Selection and Assessment . While there is no explicit mention of advising students or receiving awards, his extensive publication record and book chapters suggest active mentorship and leadership in the field. He leads the Department of Work and Organizational Psychology at Ulm University, contributing to both academic research and practical applications in HR diagnostics. His work bridges theory and practice, often addressing real-world challenges in personnel selection and organizational psychology.

Maud NordsternView profile

Professor

• Child Protection
• Youth Welfare
• Early Childhood Education
• +9 more

Prof. Dr. Maud Nordstern is a Professor of Youth Welfare and Child Protection at the Frankfurt University of Applied Sciences , College of Social Work & Health. Her work focuses on integrating child protection into academic curricula, emphasizing interdisciplinary collaboration and digital teaching innovations. Education: Diplom-Pädagogik (1992-1996), Promotion in Erziehungswissenschaften (Goethe-Universität Frankfurt). Research: Child rights, procedural representation for minors, professional qualification in child protection, digital learning tools, and early childhood education. Notable Projects: FallbeiSpiel Thomas (multimedia learning platform), Kinderschutz in der Lehre (digital education development). Awards: Hessian University Prize for Excellence in Teaching (2013), Hanse Merkur Child Protection Award (2018), Stifterverband University Pearl (2024). Publications: Over 20 years, she has authored/edited 15+ works on child protection, including handbooks on Verfahrensbeistandschaft , trauma pedagogy, and interdisciplinary training frameworks. Her FallbeiSpiel Thomas project (2024) exemplifies her commitment to gamified learning. Scientific Awards: Hessian University Prize for Excellence in Teaching (2013) Hanse Merkur Child Protection Award (2018) Stifterverband University Pearl (2024) Grants and Projects: Leads the Kinderschutz in der Lehre initiative (2024-2027) and SKILL - FallbeiSpiel Thomas phases 1&2, funded by the Stiftung Innovation in der Hochschullehre and Pflege-Adoptiv-Familien-Stiftung. Leadership & Collaborations: Vorsitzende des Kuratoriums der Stiftung zum Wohl des Pflegekindes (since 2013), member of AG IX Landespräventionsrat Hessen (since 2006), and expert advisor for the Hessisches Ministerium für Soziales und Integration (2023). Collaborates with institutions like Goethe-Universität Frankfurt, Deutsche Psychoanalytische Vereinigung, and BZgA.

• Computational Mechanics
• Numerical Simulation
• Shape Optimization
• +12 more

Stefanie Elgeti is Associate Professor and Private Lecturer at the Chair for Computational Analysis of Technical Systems (CATS), Faculty of Mechanical Engineering, RWTH Aachen University. She previously held a professorship in lightweight design at TU Vienna starting in 2019. Her research integrates computational mechanics with manufacturing process optimization, focusing on plastics extrusion, injection molding, and high-pressure die casting. Diploma in Mechanical Engineering, majoring in 'Manufacturing Techniques for Microsystems' PhD (2011): 'Free-Surface Flows in Shape Optimization of Extrusion Dies' Habilitation (2016): 'CAD-Conforming Finite Element Methods in Engineering Design' Her research centers on solving inverse problems in manufacturing through numerical simulation. She employs advanced techniques such as free-surface flow modeling, non-Newtonian material models, spline-based finite elements, and PDE-constrained shape optimization. Her group simulates entire process chains from filling to solidification and warpage prediction, enabling design optimization of cavities and cooling systems. The recent publications (2022–2024) reveal a strong trend toward integrating artificial intelligence—particularly physics-informed neural networks and Bayesian optimization—into traditional simulation workflows. There is increasing emphasis on warpage compensation, shape optimization of extrusion dies, and modeling of biomedical and environmental systems, showcasing a broadening scope from industrial manufacturing to interdisciplinary applications. She is actively involved in academic service, having served as vice-spokesperson of GAMM-Juniors (2013–2014) and currently co-chairing the ECCOMAS Young Investigator Group. While no formal awards are listed, her leadership roles and editorial contributions reflect significant recognition in the computational mechanics community. Prof. Elgeti advises students and leads multiple research initiatives at CATS, including work groups focused on production engineering, fluid-structure interaction, and INTERESST. Her team develops model hierarchies and digital twins for industrial processes, aiming to bridge simulation and real-world manufacturing through intelligent, adaptive systems.

• Quantum Computing
• Computer-Aided Engineering
• Gaussian Processes
• +6 more

Oliver Ahrend is a doctoral student and researcher at RWTH Aachen University, affiliated with the Chair of Methods for Model-based Development in Computational Engineering (MBD) and the Institute of General Mechanics (IAM). He holds an M.Sc. in Simulation Sciences from RWTH Aachen and a B.Eng. in Mechanical Engineering from Aalen University. His research focuses on bridging quantum computing and engineering applications, particularly in developing methods to apply quantum algorithms to real-world computational engineering problems. A key area of interest is the use of quantum computing in Gaussian processes and discrete-element simulations. Quantum Computing for Engineering Model-Based Development Simulation and Optimization Quantum Algorithms in Mechanics His recent work centers on quantum annealing techniques for particle matching in quasi-cyclic discrete-element simulations, presented at the 16th World Congress on Computational Mechanics in 2024. This reflects a growing trend in applying quantum computing to classical mechanical simulations. Oliver Ahrend has no listed scientific awards at this time. He has been actively involved in research and development projects, contributing to both academic and applied computational engineering. He has served as a research assistant at MBD and IAM from 2022 to 2024 before advancing to his current doctoral position. There is no mention of formal student advising or grant leadership. He is associated with the Chair of Methods for Model-based Development in Computational Engineering, where he contributes to advancing model-driven approaches in computational systems. His GitHub activity indicates engagement in symbolic quantum simulation, GPU computing, and educational quantum computing projects.

Florian SteinkeView profile

Professor

• Energy Management Systems
• Machine Learning Applications in Energy
• Distributed Control Systems
• +5 more

Prof. Dr. Florian Steinke is a Professor and Head of the Energy Information Networks and Systems Department at Technische Universität Darmstadt. His academic career spans roles at Siemens Corporate Technology (2009–2016) and a PhD in machine learning at the Max Planck Institute for Intelligent Systems (2006–2008). His research focuses on algorithmic energy management, distributed control systems, machine learning applications in energy grids, and resilient smart grid design. Education: PhD in Machine Learning (Max Planck Institute for Intelligent Systems, 2006–2008) Diplom in Computational Physics (University of Tübingen & University of Washington, 1999–2005) Research Interests: Development of cyber-physical systems for energy grids Optimization of thermal-electric systems using game theory and stochastic control Integration of social media data for demand forecasting Cybersecurity measures against adversarial attacks on grids Recent work emphasizes probabilistic grid modeling, resilient energy market design, and AI-driven control strategies for Fourth Generation district heating grids. His platform ecosystem research aims to support the energy transition through data-driven solutions. Labs/Teams: Leads the Energy Information Networks and Systems research group, focusing on interdisciplinary projects combining automation, data science, and energy systems engineering.

• Control Systems
• Automotive Engineering
• Fault Diagnosis
• +4 more

Prof. Rolf Isermann is a Professor at the Technical University of Darmstadt, leading the Research Group for Control Systems and Process Automation. His work focuses on model-based control, fault diagnosis in automotive systems, and real-time engine management. He has authored seminal works on combustion engine diagnostics, vehicle dynamics control, and collision avoidance systems like PRORETA. His research bridges theoretical control engineering with practical applications in automotive and industrial automation. Key contributions include advancements in state estimation for diesel engines, adaptive control methodologies for driving dynamics, and system identification techniques. He has published extensively on topics such as turbocharger modeling, emission control optimization, and fault-tolerant mechatronic systems. His work emphasizes integrating sensor data with physical models to enhance system reliability and performance. Prof. Isermann's research also explores mechatronic systems fundamentals, including sensor and actuator design, and has contributed to standards in industrial automation through his involvement with IFAC symposia. His publications span academic journals and conference proceedings, reflecting a commitment to both theoretical innovation and practical engineering solutions.

Jin-Song von StorchView profile

Professor

• Climate Physics
• Ocean Dynamics
• Climate Energetics
• +12 more

Prof. Jin-Song von Storch is Deputy Director of the Department of Climate Variability at the Max Planck Institute for Meteorology and a §17 Professor at the University of Hamburg. She leads the Energetics of Climate working group, focusing on ocean dynamics, climate energetics, and probabilistic climate prediction. Her research bridges oceanography and statistical physics to understand the inherent randomness in deterministic climate systems. PhD in Meteorology, University of Hamburg (1990) Diploma in Meteorology, University of Hamburg (1987) Vordiplom in Physics, University of Hamburg (1987) Her research interests include climate physics, ocean dynamics, climate energetics, statistical physics of climate, internal climate variability, and Earth system modeling. She investigates how mechanical energy from wind and tides supports diapycnal mixing and maintains overturning circulations, and how concepts from statistical physics can enhance probabilistic climate predictions. Her systems-oriented approach explores the randomness and irreversibility in deterministic climate models. Her recent publications span high-resolution climate modeling (ICON), ocean tides, Lorenz energy cycles, and wind-driven ocean dynamics. She contributes to advancing Earth system models and understanding energy transfers in the climate system. Heisenberg Program of the DFG (1999–2004) Scholarship from the Chinese government (1981–1987) She has advised PhD students such as Ssebandeke, J., and is involved in major modeling initiatives like ICON and MPI-ESM. She leads research on ocean energetics and contributes to international climate model intercomparisons. Her work integrates theoretical and modeling approaches to improve climate predictability. She is affiliated with the Max Planck Institute for Meteorology and the University of Hamburg, contributing to climate research through leadership, mentorship, and innovative modeling.

Jan BarowskiView profile

Senior Lecturer

• High Frequency Systems
• Millimeterwave Radar
• THz Sensing
• +5 more

Dr. Jan Barowski is a Senior Academic Councillor (Senior Lecturer) at the Department of High Frequency Systems within the Faculty of Electrical Engineering and Information Technology at Ruhr University Bochum. His research focuses on millimeterwave radar systems, THz sensing, and advanced material characterization techniques. He leads a team developing innovative solutions in high-frequency systems, including FMCW radar imaging, antenna design, and biosensor applications. Barowski's work integrates interdisciplinary approaches combining radar technology, signal processing, and electromagnetic engineering. Recent projects include fluidic THz time delay systems, ultrawideband robotic antenna measurements, and dielectric waveguide-based biosensors. His team collaborates extensively on industrial applications like non-destructive material testing and 3D imaging. He is actively involved in academic committees and has authored/co-authored numerous articles in top journals/conferences like IEEE Transactions on Microwave Theory and Techniques, European Microwave Conferences, and International Radar Symposia. His research emphasizes practical applications in fields such as biomedical sensing, industrial monitoring, and telecommunications.

• Microwave Engineering
• Terahertz Technology
• Antenna Measurement Systems
• +7 more

Jan Kristof Dausien is a Researcher at the Microwave Systems department within the Faculty of Electrical Engineering and Information Technology at Ruhr-University Bochum. His work focuses on advanced microwave and terahertz technologies, including sensor development, dielectric waveguide systems, and radar applications. He collaborates with Prof. Ilona Rolfes and other researchers in projects such as KI-ROJAL, PINK, and Terahertz-NRW. Research Interests: Design and characterization of dielectric waveguides for THz systems FMCW radar techniques for material imaging and ranging Integration of fluidic components into THz sensors Automated robotic antenna measurement systems Non-destructive testing using radar tomography Publications highlight his contributions to THz biosensors, environmental signal propagation studies, and innovative waveguide splitter designs. His work bridges theoretical simulations with practical applications in antenna systems and material characterization. Lab/Team: Part of the Microwave Systems team, contributing to projects like PluTO+, 6GEM, and Plaque-CharM. Collaborates with Fraunhofer Heinrich Hertz Institute (FHR) on sensor technologies.

• Microwave Engineering
• Radar Systems
• Electromagnetics
• +3 more

Prof. Dr.-Ing. Thomas Musch is a Professor in the Department of Electronic Circuit Technology at the Faculty of Electrical Engineering and Information Technology (ETIT), Ruhr University Bochum. His research focuses on advanced radar systems, microwave engineering, and sensor technology. He leads projects like MEDICI, addressing humanitarian applications such as landmine detection using microwave and radar technologies. His work intersects with electromagnetics, signal processing, and semiconductor devices. Education: Academic qualifications not explicitly listed but inferred from his position as a professor. Research Interests: Prof. Musch’s areas include radar system design, millimeter-wave sensors, phase noise analysis in circuits, and applications in industrial automation, plasma diagnostics, and non-destructive testing. His group develops solutions for real-time monitoring of fluids, gases, and bulk materials using radar and electromagnetic techniques. Publications: Over 150 peer-reviewed articles since 2015, emphasizing radar imaging, microwave components, and sensor innovation. Recent work includes ultra-wideband frequency synthesizers, dielectric waveguide characterization, and AI-driven radar data synthesis. Grants & Collaborations: Involved in interdisciplinary projects, including EU-funded initiatives and international collaborations with institutions like Universidad Pontificia Bolivariana (Colombia). His lab focuses on practical applications like plasma state supervision and humanitarian demining. Labs/Teams: Electronic Circuit Technology Lab at ETIT, specializing in radar systems, microwave circuits, and sensor development. Collaborates with industry partners for practical implementation of research.