Matjaz Gams is a prominent researcher in the field of Artificial Intelligence and Ambient Intelligence. His work focuses on integrating AI into healthcare, wearable technologies, and smart environments. He has contributed significantly to activity recognition systems using sensor data, fall detection algorithms, and machine learning applications in medical diagnostics. Gams actively participates in international conferences such as IJCAI and UbiComp, often serving as an organizer and editorial board member. His research spans interdisciplinary domains including: AI ethics and responsible research practices Smart city frameworks and urban digital transformation Healthcare innovations like medical chatbots and heart sound analysis Wearable sensor systems for fall prediction and cognitive load monitoring Notable contributions include developing the Insieme platform for ambient intelligence applications and leading studies on cross-domain activity recognition challenges. Gams collaborates with multidisciplinary teams across academia and industry to advance real-world AI implementations.
Peter Moerters is a Professor of Applied Mathematics at the University of Cologne , specializing in probability theory and its applications. His research spans random graphs, large deviations, Brownian motion, stochastic processes in random media, and geometric measure theory. He has extensive collaborations and editorial service, including contributions to journals like Stochastic Processes and their Applications and Journal of Theoretical Probability . Research Interests : Probability theory, random graphs, large deviations, Brownian motion, stochastic processes in random media, and geometric measure theory. Notable Coauthors : Yuval Peres, Jochen Blath, Wolfgang König, and others. Publications : Recent works include studies on percolation phase transitions, competing growth processes, tangent graphs, and branching with selection and mutation. Editorial Service : Serves on the editorial boards of Journal of Theoretical Probability and Stochastic Processes and Applications .
Tim Quatmann is a researcher at RWTH Aachen University's Department of Computer Science, affiliated with the Faculty of Mathematics, Computer Science, and Natural Sciences. He focuses on probabilistic model checking, multi-objective optimization, and formal verification of parametric probabilistic systems. His work addresses challenges in systems with partial observability and parameter synthesis for Markov models. Quatmann is a core developer of the Storm probabilistic model checker, a widely used tool in formal verification. Education: He earned his Ph.D. in 2023 from RWTH Aachen University, with a dissertation titled Verification of multi-objective Markov models . Research Interests: Quatmann's research bridges theoretical foundations and practical tool development, emphasizing scalable algorithms for probabilistic systems. His work includes optimizing MDP model checking algorithms, parameter space exploration, and improving accuracy in computing probabilistic metrics like expected visiting times. He has contributed to the Storm project, QComp competitions, and tool benchmarking efforts. Teaching: He has taught courses such as Model Checking , Probabilistic Systems Verification , and Theoretical Foundations of UML , reflecting his expertise in formal methods and theoretical computer science. Labs/Teams: He collaborates with the MOVES group (Model-Based Software Verification and Self-Adaptive Systems) at RWTH Aachen, contributing to advancements in probabilistic verification and automated reasoning.
Marios C. Angelides is a prominent academic specializing in multimedia systems, artificial intelligence, and collaborative technologies. His work focuses on integrating machine learning, IoT, and game theory into applications such as autonomous systems, disaster response, and personalized gaming. He has authored over 90 publications, including influential papers on MPEG standards and AI-driven UAV coordination. His research bridges theoretical frameworks with practical implementations in telecommunications, emergency communications, and educational technologies. Angelides collaborates extensively with researchers like Faris A. Almalki and Harry W. Agius, advancing interdisciplinary solutions in intelligent tutoring systems and adaptive multimedia.
Professor Angela P. Schoellig holds the Alexander von Humboldt Professorship for Robotics and Artificial Intelligence at Technical University of Munich (TUM) and is an Associate Professor at the University of Toronto Institute for Aerospace Studies (UTIAS), affiliated with the Vector Institute. Her research focuses on integrating robotics, control systems, and machine learning to enhance autonomous systems' performance, safety, and adaptability. She leads projects in autonomous drones, self-driving vehicles, and safe learning algorithms. Schoellig is a recipient of prestigious awards including the Robotics: Science and Systems Early Career Spotlight Award (2019), Sloan Fellowship (2017), and recognition as an MIT Innovator Under 35 (2017). Educational Background: PhD in Robotics from ETH Zurich (2013), awarded ETH Medal and Chorafas Foundation Prize M.Sc. in Engineering Cybernetics from University of Stuttgart (2008) M.Sc. in Engineering Science and Mechanics from Georgia Institute of Technology (2007) Key Roles & Activities: Principal Investigator, NSERC Canadian Robotics Network Four-time winner (2018–21) of the SAE AutoDrive Challenge with the U of T team Associate Director, Centre for Aerial Robotics Research and Education (CARRE) Editor, International Journal of Robotics Research Research Themes: Her work emphasizes safe learning in dynamic environments, including delivery drones for remote regions, pollution monitoring, and medical AED delivery. She develops algorithms for robust control under uncertainty, with applications in mining, healthcare, and autonomous vehicles. Notable projects include winter-optimized autonomous driving (WinTOR initiative) and UWB-based localization systems. Awards & Honors: Mitigates risks in learning systems through safety filters and constraint-aware algorithms Pioneer in swarm robotics and language-driven choreography for drone coordination Advances reproducibility in robotics with benchmarks like safe-Control-Gym Grants & Collaborations: Infineon Stiftungslehrstuhl for "Safety, Performance and Reliability of Learning Systems" Industry partnerships with aerospace, transport, and energy sectors Labs & Teams: Leads the Dynamic Systems Lab at TUM and advises U of T’s SAE/GM AutoDrive Challenge team and UTAT Aerospace Team, fostering student innovation in autonomous systems.
Sebastian Wohner is a researcher at the Chair of Computer Graphics and Visualization (Prof. Westermann) at the Technical University of Munich. His work focuses on advanced visualization techniques, machine learning applications in graphics, and GPU-accelerated algorithms for 3D design and simulation. He actively contributes to projects such as the NVIDIA CUDA Research Center and ERC-funded initiatives like SaferVis and realFlow, emphasizing real-time liquids and safer visualization systems. His research interests span 3D Gaussian splatting, topology optimization, neural fields for statistical dependencies, and spatio-temporal flow visualization. He has pioneered methods for compressing meteorological ensembles and accelerating novel view synthesis in consumer devices. Wohner also explores GPU-based linear algebra optimizations and efficient rendering techniques for ribbons and twisted lines. In teaching, he leads courses on game physics, visual data analytics, deep learning in computer graphics, and topology optimization. Notable contributions include the development of the Particle Engine and Bunny Demo applications, as well as advancements in differentiable rendering and robotic perception systems. His work bridges theoretical foundations with practical implementations in both academia and industry.
Manfred Faldum is a researcher at the Institut für Geometrie und Praktische Mathematik, RWTH Aachen, Germany. He is actively involved in research on numerical methods for high-dimensional partial differential equations and has contributed to significant advancements in low-rank tensor methods. He also serves as a teaching assistant in numerical mathematics courses at RWTH Aachen and previously at Johannes Gutenberg University Mainz. Research Interests: His work centers on adaptive methods for PDEs, high-dimensional problems, low-rank tensor approximations, space-time discretization, and Fokker-Planck equations. These areas are critical in modern computational mathematics, especially for simulations in physics and engineering where dimensionality and accuracy are challenging. The sole available publication demonstrates a strong focus on developing efficient numerical solvers for parabolic PDEs using adaptive low-rank techniques, reflecting a trend toward scalable and memory-efficient algorithms for complex systems. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: There is no mention of students advised or research grants received. However, his role as a thesis supervisor during his studies and his active research participation suggest engagement in academic mentoring and collaborative projects. Labs and Teams: He is a member of the research team at the Institut für Geometrie und Praktische Mathematik, RWTH Aachen, and collaborates with Prof. Markus Bachmayr. He participates in research initiatives such as Drops and Multiwave , and is involved in workshops on sparsity, singular structures, and high-dimensional approximation.
Dr. Leonard Heilig is a Researcher at the Institute of Information Systems within the University of Hamburg Business School at the University of Hamburg. His work focuses on integrating advanced technologies such as digital twins, blockchain, and cloud computing into maritime logistics and port operations. He is affiliated with the Von-Melle-Park 5 office in Hamburg and can be reached at leonard.heilig@uni-hamburg.de . He holds a Ph.D., though specific educational details are not provided in the text. His research interests include optimizing automated container terminals, reducing environmental emissions in ports, and enhancing enterprise architecture management through agile methodologies. He has contributed to frameworks for port-centric information management and inter-terminal truck routing, emphasizing real-time data utilization and sustainability. His recent publications highlight trends in digital twin applications for port operations, blockchain integration in maritime logistics, and cloud-based optimization solutions. While no scientific awards are explicitly listed, his work demonstrates significant contributions to smart port systems and digital transformation in logistics. He collaborates within the Institute of Information Systems team and has been involved in projects like port-IO , a mobile cloud platform for truck routing optimization. Grants and advising roles are not detailed in the provided texts.
Yang Yang is a Researcher and PhD student at the University of Hamburg Business School's Maritime Economics Research Center since 2019. She holds a B.Sc. in Logistics Engineering from Changsha University of Science & Technology (2015) and an M.Eng in Logistics (focusing on port operations) from Shanghai Maritime University (2017). Her work includes roles as a logistics planning engineer in an automotive company (2015–2017). Her research focuses on maritime logistics optimization, carbon emissions reduction in transportation and port operations, and environmental science dynamics in river systems. Key areas include port connectivity, shipping networks, and sustainable infrastructure strategies. Recent studies analyze carbon emissions in river basins (e.g., Pearl River, Elbe River), the impact of land use on CO₂ outgassing, and optimization of container terminal operations. Her work bridges environmental sustainability with industrial logistics, addressing both natural and anthropogenic factors in global supply chains. Yang has no listed awards but contributes actively to interdisciplinary research at the intersection of maritime economics and environmental science. She collaborates with the Maritime Economics Research Center and engages in doctoral studies exploring sustainable port logistics.
Martin Eisemann is Professor of Computer Science and Director at the Computer Graphics Lab within the Computer Science Department of the College of Engineering at Technical University of Braunschweig. Previously, he served as full professor for Computer Graphics at TH Köln (2015-2020) where he co-founded and led the Advanced Media Institute. His academic journey includes a Diploma (2006) from University of Koblenz-Landau and PhD (2011) from TU Braunschweig, followed by post-graduate work at TU Delft. His research spans visual computing with emphasis on computer vision, image/video processing, computer graphics, ray tracing, Monte-Carlo simulations, information visualization, and visual analytics. Recent work demonstrates strong focus on neural rendering techniques including neural point clouds, Gaussian splatting, and holography applications, reflecting evolving trends toward AI-integrated graphics pipelines and immersive visualization systems. His publications consistently address real-time performance challenges while advancing visual quality metrics. VMV'16 Best Paper Award EGSR'16 Best Paper Award ACM Multimedia 2015 Best Student Paper Award Graphics Interface 2015 Best Student Paper Award SAP 2025 Best Student Paper Honorable Mention As Dean of Studies (2023-2027) and former Audit Committee member, he actively shapes academic policy. His community service includes program committee roles for SAP, WACV, and Computational Visual Media conferences. Current research includes a planned sabbatical (April-October 2025) focusing on visual computing challenges. The Computer Graphics Lab maintains active collaborations with DLR, Ford, and European institutions through projects spanning planetary visualization, video conferencing security, and ADHD cognitive support tools.
Gunnar Stevens is a Professor and Divisional Director of IT-Security and Consumer Computing at the University of Siegen's Faculty of Information Systems and New Media. His research focuses on consumer-oriented technologies, including privacy-enhancing systems, human-robot interaction, sustainable mobility solutions, and explainable AI. Dr. Stevens' work bridges technical security with human-centered design, investigating topics such as algorithmic accountability in dating apps, digital sovereignty, privacy norm formation through gamification, and sustainable transportation behavior. Recent projects examine the digitalization of household administrative labor and renewable energy preferences for EV charging. He has led numerous projects on usable security policies, smart home intelligibility, and trust in voice assistants. His methodological approach combines design studies, living lab implementations, and empirical evaluations of technology adoption.
Dr. Pascal Grittmann is a Research Fellow in Computer Graphics at Saarland University, specializing in efficient and robust rendering algorithms. His research advances Monte Carlo methods, importance sampling, and bidirectional rendering techniques for global illumination. Current DFG-funded project develops adaptive bidirectional rendering solutions requiring minimal user configuration. Research aims to create universal rendering algorithms balancing efficiency and robustness across diverse scenes. Publications demonstrate innovations in variance-aware sampling, path guiding optimizations, and caustic rendering. Served as Eurographics Symposium on Rendering conference co-chair (2021). Teaching includes practical implementation of rendering techniques using Vertex Connection and Merging methods. Maintains collaborations with international computer graphics researchers.
Dr. Stefan Endler is an Academic Councillor at the Institute of Computer Science, Johannes Gutenberg University Mainz, where he has held various roles including Research Associate and Academic Council member since 2006. His work bridges computer science and sports science, focusing on sports informatics, modeling/simulations for training impact analysis, and software engineering (design patterns). Educational Background: Bachelor of Science (2006): Model-based training planning with GPS data at Johannes Gutenberg University Mainz Bachelor of Science (2008): Attacker models and attack detection in mobile ad-hoc networks at TU Darmstadt Doctorate (2013): Adaptation of the PerPot metamodel for endurance-oriented running optimization at Mainz University Research Interests: Development of simulation models for athletic performance optimization Application of design patterns in software engineering for sports technology Integration of sensor data (e.g., smartwatches) for real-time training analysis Teaching Contributions: Extensive teaching experience across 15+ years, including courses on software development, design patterns, and computer engineering. Notable roles include lecture leadership for Design Patterns (2014–2021) and programming fundamentals. Awards: 2018 Teaching Award from Johannes Gutenberg University recognizing excellence in academic instruction. Advisory Work: Supervised 45+ theses (2014–2020) across computer science and sports science disciplines. Maintained active involvement in thesis supervision and academic council governance. Collaborative Efforts: Cross-disciplinary work with the Institute of Sports Science, contributing to biomechanical studies and training methodology research.
Prof. Hao Yan is a Professor at the 2nd Physics Institute of the University of Stuttgart, affiliated with Faculty 08. He has been honored with the Humboldt Research Award and is recognized as an International Partner by the Baden-Württemberg Stiftung. His research focuses on advanced control systems, including model predictive control (MPC), stochastic control, optimization, and DNA nanotechnology. Yan's work integrates machine learning and robust methodologies to address challenges in dynamic systems and power electronics. His research interests span control theory applications in electrical engineering, with a particular emphasis on grid-forming converters, frequency stability, and energy systems. He also explores the intersection of nanotechnology and control systems. Recent publications (2018–2025) highlight trends in stochastic MPC, distributionally robust optimization, and learning-based control strategies. Notable contributions include work on tube MPC, intermittent observation handling, and discounted probabilistic constraints in uncertain environments. His research bridges theoretical advancements with practical applications in smart grids and adaptive control systems. Prof. Yan has received prestigious awards including the Humboldt Research Award and international partnerships supporting his research in top-tier institutions. His work is disseminated through leading journals and conferences in control systems and electrical engineering.
Maria Matheou is a junior professor at the Institute for Lightweight Structures and Conceptual Design (University of Stuttgart), where she leads the A07 subproject within the DFG-funded SFB1244 initiative. Her research focuses on adaptive kinetic facades, aiming to enhance urban sustainability through dynamic building envelopes that improve daylight performance and mitigate urban heat islands. She teaches design studios emphasizing transformable architecture and interdisciplinary approaches. She holds a B.Sc. (2009), Diploma (2010), and Ph.D. (2014) in Architecture from the University of Cyprus, with postdoctoral research on kinetic hybrid structures. Her work integrates robotics, automation, and environmental engineering to create responsive architectural systems. Key Research Projects : SFB1244: Adaptive skins for future built environments ADDOPTML: Optimized 3D-printed structures using machine learning Teaching : Adaptive Façade Skins (B.Sc./M.Sc., University of Stuttgart) Building Technology (University of Cyprus) Awards : Lambros & Thalia David Award for Excellence in Architectural Design (2010) University of Cyprus Scholarship for Academic Excellence (2013) Her lab collaborates globally with institutions like McGill University and the National Technical University of Athens on daylight optimization and reconfigurable mechanisms.
