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Christian HertView profile

Researcher

• autonomous indoor flight robotics
• Path planning for autonomous flying robots
• Methods for indoor localization
• +2 more

Christian Hert is a Researcher at Esslingen University of Applied Sciences, serving as Head of 'Autonomous Indoor Flight Robotics' at the Virtual Automation Lab since June 2024 and as Research Associate since May 2021. His work focuses on implementing robotics solutions for industrial environments, particularly with autonomous flying systems. Education: Master of Engineering in Automotive Systems Engineering from Heilbronn University (March 2021) Bachelor of Engineering in Mechatronics - Automotive Systems Engineering from Baden-Württemberg Cooperative State University in Stuttgart (September 2019) Christian Hert's research centers on autonomous indoor flight robotics in industrial contexts, with specific expertise in path planning for autonomous flying robots and methods for indoor localization. His work bridges theoretical robotics with practical industrial applications, particularly focusing on safe human-drone interaction and simulation-based operation systems. His research addresses critical challenges in flexible production systems where increasing product customization demands innovative material transport solutions. Hert's publications demonstrate a clear trajectory toward practical implementation of UAV technology in manufacturing environments. His recent work focuses on safety mechanisms for human-drone interaction using curve-shortening flow methods, while his earlier research established foundations for simulation-based operation of indoor flight robots using digital twin technology. These works collectively address the challenge of integrating UAVs into dynamic production environments with minimal infrastructure requirements. Christian Hert has established himself as a key contributor to the Virtual Automation Lab, working closely with Prof. Dr.-Ing. Sascha Röck and collaborating with researchers from institutions including University of Stuttgart. His industry experience with Porsche Engineering Services GmbH during both his bachelor's and master's studies provides valuable practical context for his academic research. Hert leads the 'Autonomous Indoor Flight Robotics' research group within the Virtual Automation Lab, developing solutions that leverage otherwise unused airspace in industrial settings. His work specifically targets the challenges of implementing safe UAV operations in close proximity to human workers in high-wage countries where customized production systems are increasingly necessary.

Thomas KirschsteinView profile

Professor

• Logistics Management
• Supply Chain Sustainability
• Operations Research
• +4 more

Introduction Prof. Dr. Thomas Kirschstein is a Professor at Martin Luther University Halle-Wittenberg (MLU), affiliated with the Faculty of Law, Economics and Business, and a researcher at the Center for Economics of Materials (CEM), Fraunhofer-Zentrum IMW. His work focuses on logistics, emission management, and robust statistical methods. He holds a PhD in Economics (2014) and a habilitation in eco-oriented logistics management (2020). Education 2002–2003: Diploma in Mathematics at MLU 2003–2008: Diploma in Economics at MLU 2014: PhD in Economics (thesis: 'Integrated Supply Chain Planning in Chemical Industry') 2020: Habilitation (thesis: 'Papers on the Eco-oriented Management of Logistics Operations') Research Interests Kirschstein's research integrates logistics and environmental sustainability, including emission reduction in freight transport, robust statistical methodologies, and supply chain optimization. His work combines simulation-based planning with empirical analysis, addressing challenges in complex production networks and intermodal transportation. Awards and Recognition Christian Wolff Award (2020) for habilitation thesis Werner Kern Award (2013/2014) for production management research Best Paper Award (2013) from the Faculty of Law and Business Administration Teaching and Academic Contributions He teaches courses in production management, logistics, and data science. Notable roles include: Lecturer: 'Production & Logistics' (2014–2019) Organized conferences like Logistics Management 2019 and Robust Statistics 2014 Labs and Collaborations Active collaborations with Dow Olefinverbund GmbH and Fraunhofer IMW, focusing on integrated logistics systems and robust estimator development.

• Computer Vision
• 3D Graphics
• Robotics
• +4 more

Li Yi is a Professor in the Department of Computer Science at Tsinghua University's School of Information Science and Technology, where they lead cutting-edge research at the intersection of computer vision, 3D graphics, and robotics. Their work focuses on advancing neural rendering, point cloud processing, and embodied AI with applications in human-object interaction and robotic manipulation. Research interests span Computer Vision , 3D Graphics , Robotics , Point Cloud Processing , Neural Rendering , and Human-Object Interaction . Recent work explores language-grounded spatial reasoning, dexterous manipulation, and 4D dynamic content generation, with publications appearing in top venues like CVPR, ICCV, and NeurIPS. Their research bridges theoretical advances with practical applications in embodied AI systems. The publication trends reveal a strong focus on neural rendering techniques (particularly NeRF variants), embodied AI for robotic manipulation , and multimodal understanding integrating vision, language, and action. Recent work increasingly incorporates large language models and focuses on generalizable approaches that transfer from simulation to real-world settings. As an advisor, Professor Li has mentored numerous students including Yunze Liu, Xueyi Liu, Zekun Qi, and Runpei Dong, who frequently appear as first authors on collaborative publications. Their research has been supported by significant grants enabling work on human-robot interaction, 3D scene understanding, and embodied AI systems. Professor Li leads a research group focused on developing comprehensive frameworks for spatial reasoning, object manipulation, and dynamic scene understanding. The team works on creating benchmarks like TACO for tool-action-object understanding and developing systems like MobileH2R for human-robot handover tasks. Current work emphasizes real-world applicability with a focus on generalizable solutions that work across diverse settings.

• Optimal Control of Partial Differential Equations
• Monte Carlo Methods
• Numerical Analysis of Hyperbolic Differential Equations
• +3 more

Dr. Jan Bartsch is a Lecturer at the Institute of Mathematics , University of Würzburg, specializing in optimal control theory, kinetic models, and numerical methods. His work spans stochastic differential equations, Monte Carlo frameworks, and applications to physics and computational mathematics. Education : PhD in Mathematics (2021-2024, University of Würzburg), Master’s in Mathematics (2016-2018), Bachelor’s in Computational Mathematics (2013-2016). Research interests : Focus on optimal control of partial differential equations, stabilization of kinetic models, and computational methods for stochastic systems. Publications : Recent works include adjoint-based control of jump-diffusion processes, nonlinear operator reconstruction, and Monte Carlo frameworks for plasma control. Collaborations : Works with Stefan Volkwein (University of Konstanz) and Alfio Borzi (University of Würzburg). Skills : Proficient in C/C++, Python, MATLAB, and ParaView for computational tasks.

Elmar BittnerView profile

Researcher

• Theoretical Physics
• Quantum Gravity
• Statistical Mechanics
• +3 more

Elmar Bittner is a theoretical physicist and Researcher at the Institute for Theoretical Physics (ITP) at the University of Heidelberg. He also serves as the administrator of the institute's computer network. His academic background includes a PhD in Physics from Vienna University of Technology (2001) and a Dipl.-Ing. (equivalent to MSc) from the same institution (1998). He has held postdoctoral positions at the Institute of Atomic and Subatomic Physics in Vienna and the University of Leipzig, where he also served as Akademischer Rat (Senior Lecturer) and Head of IT. His research focuses on quantum gravity, lattice models of two- and four-dimensional systems, phase transitions in statistical mechanics, and Monte Carlo simulation techniques. Notable contributions include studies on vortex dynamics in lattice Higgs models, eigenvalue spectra in QCD, and the development of parallel tempering algorithms. Bittner has also explored applications of statistical physics to social phenomena, such as football goal distributions. His publications span topics like Ising model dynamics, critical phenomena, and random matrix theory. He has collaborated with institutions such as the University of Leipzig, Brunel University, and INFN (Italy), contributing to international conferences and workshops. Despite no listed awards, his work reflects significant contributions to theoretical physics and computational methods. Bittner’s roles include managing the ITP’s technical infrastructure, reflecting his dual expertise in theoretical physics and computational administration.

• Parallel Computing
• Group Theory
• Lattice Field Theory
• +4 more

Werner Wetzel serves as a Professor within the Department of Theoretical Physics at Heidelberg University, where he has been actively involved in teaching and research. His academic contributions are evident through a series of specialized courses delivered between 2004 and 2009, covering advanced topics in theoretical physics and computational methods. These courses include Parallel Programming with MPI or Threads for BW-Grid-like systems, Group Theory, Lattice Field Theory and Numerical Simulations, Loop Quantum Gravity, Quantum Monte Carlo, and Quantum Mechanics with a focus on interpretation questions and mathematical foundations. His research expertise spans several critical areas of theoretical physics, particularly emphasizing computational approaches. Key fields of interest include Parallel Computing for high-performance physics simulations, Group Theory applications in physical systems, Lattice Field Theory and associated numerical simulation techniques, Quantum Gravity (with specific work in Loop Quantum Gravity), Quantum Monte Carlo methods, and the foundational aspects of Quantum Mechanics. Prof. Wetzel's course on parallel programming demonstrates his commitment to integrating cutting-edge computational tools, such as MPI and threading models, into physics research, addressing practical challenges in parallelization, debugging, and optimization for large-scale simulations. Despite the detailed course descriptions and teaching materials provided, the available texts do not mention any scientific awards, honors, or fellowships attributed to Prof. Wetzel. Similarly, there is no information regarding his supervision of students (PhD, Master's, etc.) or details of research grants he may have secured. His institutional affiliation is clearly with the Institute of Theoretical Physics at Heidelberg University, situated at Philosophenweg 16 in Heidelberg, Germany, which serves as the hub for his academic activities.

• Cyber-Physical Systems
• Modeling and Simulation
• Software Testing
• +3 more

David Marson is a Researcher at the Chair of Software & Systems Engineering (Prof. Pretschner) at the Technical University of Munich since September 2022. He holds a Master's in Aerospace Engineering and has industry experience as a systems engineer. His research focuses on cyber-physical systems (CPS), modeling and simulation (M&S), scenario-based testing, and drone swarm controllers, particularly in generating test cases for cooperating UAVs. Teaching: He contributes to courses such as Systems Engineering (IN8015) and Scenario-Based Testing of Cyber-Physical Systems . He oversees thesis projects in UAV swarm robustness, search-based testing, and autonomous systems quality attributes. Key Projects: INVOLVED IN RESEARCH INITIATIVES LIKE SUPPRA (Algorand Center of Excellence), TAPFER, AND SCENARIO-BASED TESTING METHODS. Advising: Supervised theses include Inaccuracies in UAV Awareness (Bachelor's), Development of Robust UAV Route Planners (Master's), and Testing Collaborative UAV Safety (Bachelor's). Ongoing projects focus on swarm controller robustness and component failure scenarios. Labs/Teams: Active in CPS testing and UAV swarm research within the Chair's collaborative environment.

Sebastian OtteView profile

Professor

• Artificial Intelligence
• Machine Learning
• Recurrent Neural Networks
• +12 more

Sebastian Otte is a Professor at the Institute for Robotics and Cognitive Systems at the University of Lübeck, where he leads the Adaptive AI research group. Prior to this, he was a postdoctoral researcher and substitute professor at the University of Tübingen, contributing significantly to the Cognitive Modeling and Distributed Intelligence groups. University of Lübeck, Professor (since 2023) University of Tübingen, Postdoc and Substitute Professor (2016–2023) Centrum Wiskunde & Informatica (CWI), Humboldt Fellow (2022–2023) His research focuses on recurrent and spiking neural networks, bio-inspired computing, efficient learning, and adaptive AI systems. He explores how neural models can perform online learning, handle multiple time scales, and solve complex cognitive tasks such as binding, prediction, and motor control. His work bridges machine learning with cognitive science and robotics. The recent publications show a strong trend toward physics-informed neural networks, finite volume methods for PDE modeling, and explainable AI via counterfactual reasoning. His work integrates deep learning with scientific computing, emphasizing robust, interpretable, and efficient models for real-world applications. Scientific awards include: Best Paper Award at ICANN 2019 Humboldt Research Fellowship Editor's Highlight in Water Resources Research He has supervised over 70 bachelor’s and master’s theses and actively mentors students in areas such as spiking neural networks, reservoir computing, and robotics. His teaching includes core computer science and advanced neural network courses. He has been involved in research projects with industry partners like Daimler AG and Mercedes-Benz AG. Otte leads the Adaptive AI research group, which focuses on developing next-generation AI systems that learn efficiently, adapt dynamically, and model complex cognitive and physical processes using biologically inspired architectures.

• In-Memory Databases
• Data Stream Processing
• Database Systems
• +12 more

Matthias Uflacker is a Professor at the Hasso Plattner Institute (HPI), University of Potsdam, Germany, where he conducts research in database systems, in-memory computing, and data-driven enterprise applications. His work bridges systems research and practical applications in Industry 4.0, education, and bioinformatics. University: University of Potsdam School: Hasso Plattner Institute Department: Department of Digital Engineering Research Focus: In-Memory Databases, Stream Processing, Causal AI, and Database Education His research interests span in-memory database systems , real-time data stream processing , GPU-accelerated analytics , and causal structure learning . He also contributes to computer science education , particularly in agile software engineering and interactive learning tools for K-12. The recent publications reflect a strong trend in enterprise data management , with a focus on benchmarking (e.g., ESPBench), performance optimization (e.g., Kafka, Hyrise), and intelligent decision support using causal models in industrial contexts. His work increasingly integrates AI for monitoring and automation in manufacturing and e-commerce. He has co-authored numerous publications in top-tier venues such as VLDB, ICDE, EDBT, and KDD, often in collaboration with Hasso Plattner and other HPI researchers. Matthias Uflacker leads and contributes to research projects on autonomous database systems , dynamic pricing simulations , and educational technology platforms for programming exercises. His team develops tools for real-time data integration, causal analysis, and classroom software engineering assessment.

Günter RudolphView profile

Professor

• Computational Intelligence
• Evolutionary Algorithms
• Optimization
• +5 more

Prof. Günter Rudolph is a Professor of Algorithmic Foundations and Education in Computer Science at the Technical University of Dortmund's Department of Computer Science. He leads Chair 11: Algorithm Engineering, focusing on Computational Intelligence (CI), Evolutionary Algorithms, and their applications in optimization and gaming. His research emphasizes theoretical analysis of CI methods, practical guidelines for operationalization, and applications in engineering, energy systems, and entertainment. Key research areas include multi-objective optimization, evolutionary robotics, and computational intelligence in games such as StarCraft and car racing simulations. He has advised numerous students on topics ranging from autonomous driving systems to procedurally generated game content. Rudolph collaborates internationally, including with CINVESTAV-IPN (Mexico) on multiobjective control methods and BMWi-funded projects on energy systems and forming process predictions. His work spans academic publications in journals like Genetic Programming and Evolvable Machines and conferences such as IEEE CIG. Notable projects include developing adaptive car racing controllers, optimizing energy supply systems in industrial parks, and advancing AI strategies in real-time strategy games. Rudolph's group actively contributes to game AI research through competitions like the StarCraft AI Competition and the Simulated Car Racing Championship, emphasizing the intersection of computational intelligence and entertainment.

Qi ShuView profile

Professor

• Thermal Engineering
• Fluid Dynamics
• Materials Science
• +4 more

Qi Shu is a Professor in the Compound Semiconductor Technology department at RWTH Aachen University . His research focuses on thermal engineering, fluid dynamics, and computational physics, particularly in advanced semiconductor technology applications. Current research interests include ferrofluid-based cooling systems, particle suspension mechanics, and heat transfer optimization in complex flows. His work combines experimental studies and numerical simulations to analyze thermal convection in particle-laden systems, non-spherical particle behavior, and shear flow effects on conductivity. Recent publications highlight trends in multiphysics modeling (LBM-DEM-FEM coupling), electromagnetic cooling systems using ferrofluids, and detailed investigations of particle rotation dynamics in nanofluids. These studies span disciplines including materials science, computational fluid dynamics, and applied thermal engineering. Based at the Central Laboratory for Micro- and Nanotechnology (ZMNT), his lab investigates semiconductor technology with a focus on thermal management solutions for high-performance electronic systems and nanoscale fluid dynamics.

Tim GerritsView profile

Researcher

• Scientific Visualization
• High-Performance Computing
• In-Situ and In-Transit Visualization
• +7 more

Dr. Tim Gerrits is a researcher at the Institute for Visualization (VIS) at RWTH Aachen University, where he leads the Visualization Team. His work bridges scientific visualization, high-performance computing, and immersive technologies, with a strong focus on in-situ and in-transit analysis for large-scale simulations. University: RWTH Aachen University Institute: Institute for Visualization (VIS) Role: Lead of the Visualization Team Tim Gerrits' research centers on developing tools and frameworks for efficient and interactive visualization of complex scientific data. His interests include ensemble data analysis, uncertainty visualization, virtual reality interaction techniques, and leveraging game engines like Unreal Engine for scientific applications. He is particularly active in the domain of neuronal network simulations and oceanographic modeling. His recent publications highlight a strong trend toward accessible, real-time, and hybrid visualization workflows. He has contributed to the development of DaVE, a curated database of visualization examples to support HPC users, and Insite, a lightweight pipeline for in-transit processing in neuroscience simulations. His work emphasizes usability, performance, and integration with existing scientific workflows. Scientific Awards: Best Paper Award at IEEE Uncertainty Visualization Workshop, 2024 Honorable Mention Award at Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), 2022 Dr. Gerrits actively mentors and collaborates on interdisciplinary projects involving computational neuroscience and climate modeling. He has led the curation of datasets for the IEEE SciVis Contest and promotes open science through Zenodo-hosted resources. His lab focuses on building scalable, user-centered visualization systems that empower domain scientists to gain early insights from massive simulations.

Sebastian StemmlerView profile

Researcher

• Control Engineering
• Industrial Automation
• Model Predictive Control
• +7 more

Dr.-Ing. Sebastian Stemmler is a Managing Chief Engineer and Head of Industrial Systems and Production Systems at the Institute of Automatic Control (IRT), RWTH Aachen University, within the Faculty of Mechanical Engineering. He is actively engaged in research and development in industrial automation and control systems. His research interests focus on advanced control methodologies in industrial settings, particularly: Machine learning in industrial control engineering Control systems for digital and self-optimizing production systems Model-based Predictive Control (MPC) Iterative Learning Control (ILC) His recent publications (2021–2025) demonstrate a strong trend in applying MPC, ILC, and data-driven methods to injection molding, milling, and weaving processes. These works emphasize precision control, process optimization, and adaptation to material variability, especially with recycled plastics. His research bridges theoretical control strategies with practical industrial applications. His scientific achievements include being part of the research group that received the 2024 Cold Rolling Future Prize . He has co-authored numerous high-impact journal and conference papers, often in collaboration with leading researchers like Dirk Abel and Christian Hopmann. Stemmler supervises and collaborates on various industrial research projects, contributing significantly to advancements in smart manufacturing. He is involved in initiatives such as innocam.NRW and has contributed to research on AI in production and patient care. His work is supported by strong industry and academic collaborations. He leads the Industrial Systems and Production Systems research group at IRT, focusing on developing and implementing intelligent control solutions for complex manufacturing systems.

Lars PastewkaView profile

Professor

• Multiscale simulation of materials
• Micromechanics of materials
• Material interfaces
• +7 more

Prof. Lars Pastewka is a Full Professor of Simulation at the Department of Microsystems Engineering (IMTEK) within the Faculty of Engineering at the Albert Ludwigs University of Freiburg. His research focuses on multiscale simulation of materials, micromechanics, and tribology, with a particular emphasis on friction, adhesion, and wear. He leads a research group developing computational methods to model materials from atomic to continuum scales. His expertise includes surface forces, material interfaces, and the design of programmable materials. Key projects include studies on self-repair mechanisms in biological and artificial materials, tribogenerators, and resilient microfluidic networks. He supervises doctoral researchers such as Indre Jödicke and Mahdi Roshani, with past student Dr. Antoine Sanner completing his doctorate under his guidance. Prof. Pastewka has contributed to open science through tools like dtool and dserver, promoting FAIR data principles. His work spans interdisciplinary collaborations in materials science, biomechanics, and computational engineering. He is actively involved in academic outreach through events like the livMatS Colloquium series and contributes to teaching programs such as the Master Lab and Core Lectures initiatives. His research has been funded by Germany’s Excellence Strategy (EXC-2193/1) and addresses challenges in surface topography analysis, hydrodynamic lubrication, and material fracture mechanics. His group’s computational frameworks, including matscipy and SYMPLER, have advanced large-scale simulations in materials science.

Stephanie KemperView profile

Researcher

• Real-time Systems
• Verification
• Model Checking
• +5 more

Dr. Stephanie Kemper is a Researcher in the Correct System Design Group at the Department of Computing Science, University of Oldenburg, Germany. Her career spans roles including Research Assistant at Centrum Wiskunde & Informatica (2006-2011), OFFIS (2012-2015), and continuous contributions to the University of Oldenburg since 2011. Education Diploma in Computer Science with distinction (University of Oldenburg, 2006) PhD in Computer Science (Leiden Institute of Advanced Computer Science, 2011) Research Interests Specializing in formal methods for real-time systems, her work emphasizes: Timed Automata and Timed Constraint Automata SAT-based Model Checking for verification Component-based Software Engineering Abstraction Refinement with Craig Interpolation Concurrency and True Concurrency in systems Scalable verification techniques overcoming state explosion Publication Trends Her publications (2007-2013) focus on real-time coordination patterns, SAT-based verification, and compositional analysis of timed systems. Key areas include formal modeling of traffic scenarios, constraint automata for component connectors, and counterexample-guided abstraction refinement. Affiliations University of Oldenburg (2011-present) Centrum Wiskunde & Informatica (2006-2011) OFFIS Group SAV-RSM (2012-2015)