Björn Brandenburg is a researcher at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany. His work focuses on real-time systems, scheduling algorithms, and operating system design, with a particular emphasis on predictable resource allocation and performance guarantees in multiprocessor and cyber-physical environments. His research interests include real-time response-time analysis (e.g., PROSA ), locking protocols for multiprocessor systems, side-channel mitigation in cloud environments, and the verification of real-time scheduling policies. He has contributed to foundational studies on deadline failure probabilities, self-suspending tasks, and predictable real-time Linux implementations. Scientific awards include recognition for outstanding papers on TimerShield (2017) Offline Equivalence (2017) . His work intersects with practical systems like LITMUSRT and ROS 2, aiming to bridge theoretical guarantees with real-world applications in safety-critical and distributed real-time systems.
Sotirios Liaskos is an Associate Professor in the School of Information Technology at the Faculty of Science, York University. He is a leading researcher in requirements engineering and conceptual modeling, with a focus on goal models, empirical evaluation, and model-driven engineering. Research Interests: Requirements Engineering Goal and Conceptual Modeling Empirical Software Engineering Model-Driven Design and Automation Uncertainty and Decision-Theoretic Reasoning in Models Applications in Blockchain and Reinforcement Learning His recent work emphasizes the empirical validation of modeling constructs, the integration of decision theory into goal models, and the automated generation of secure workflows and AI training environments. He has led and co-authored numerous experimental studies on model comprehensibility and semantic quality. Publication Trends: His publications consistently appear in top venues like ER, RE, and iStar. The last five years show a strong trend toward empirical evaluation of modeling languages, decision-theoretic goal models, and applications of goal modeling in emerging domains such as blockchain and reinforcement learning simulation design. Scientific Contributions: Developed frameworks for empirical evaluation of modeling language ontologies (Peira framework). Advanced decision-theoretic approaches to goal modeling under uncertainty. Pioneered model-driven methods for generating blockchain simulators and reinforcement learning environments. Conducted foundational empirical studies on the comprehensibility of contribution links and visualization alternatives in goal models. Advising and Collaboration: He has advised several researchers including Ibrahim Jaouhar, Wisal Tambosi, Mehrnaz Zhian, and Saba Zarbaf. He maintains a highly collaborative research profile with frequent co-authorship with John Mylopoulos, Shakil M. Khan, and other international researchers. He has served as a co-editor for multiple iStar workshop proceedings, indicating leadership in the goal-oriented requirements engineering community. Labs and Teams: While no specific lab name is mentioned, his work is closely associated with research groups focused on requirements engineering and conceptual modeling, likely within York University’s software engineering research cluster. His collaborations span institutions in Canada, Europe, and beyond.
Ulrik Schroeder is a Universitätsprofessor (Full Professor) at RWTH Aachen University, leading the Chair of Learning Technologies within the Faculty of Computer Science. His research focuses on the intersection of educational technology, learning analytics, and immersive technologies with particular emphasis on practical implementations in higher education settings. Professor Schroeder's research spans multiple interconnected domains in educational technology. His primary interests include Learning Analytics implementation (particularly using xAPI standards), Virtual Reality applications for education, Open Educational Resources development and conversion, and gamification approaches for programming education. He has developed several notable tools including convOERter for OER conversion, WebWriter for creating explorable explanations, and various xAPI-based learning analytics infrastructures. His work consistently bridges theoretical frameworks with practical educational applications, often focusing on computer science education contexts. Analysis of his recent publications reveals a strong trend toward integrating Learning Analytics with immersive technologies, particularly Virtual Reality environments. His research demonstrates a systematic approach to educational technology development, with emphasis on scalability, interoperability through standards like xAPI, and practical implementation in real educational settings. The work increasingly focuses on personalized learning paths, quality assurance for educational resources, and privacy-conscious data collection. Co-editor of 21. Fachtagung Bildungstechnologien (DELFI) (2023) Co-editor of Hochschuldidaktik der Informatik HDI 2018 Co-editor of DeLFI 2018 conference proceedings Professor Schroeder has supervised numerous doctoral and postdoctoral researchers who frequently appear as co-authors on his publications, indicating an active research group. His projects often involve interdisciplinary collaborations across computer science, education, and psychology. Current major initiatives include the AIStudyBuddy project for study path analysis and the development of VR classroom simulations for teacher training. His research group, the Learning Technologies Innovation Lab, develops open research tools that support various aspects of educational technology research and implementation.
Dr. Maria Langhammer is a Researcher at the Department of Ecological Modelling, Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. Since April 2018, she has held a Research Associate position, and since July 2019, she has coordinated the Helmholtz Interdisciplinary Graduate School for Environmental Research (HIGRADE). Her work focuses on simulating biodiversity responses to land-use changes, particularly in agricultural landscapes, and evaluating policy instruments like the EU’s Common Agricultural Policy (CAP). She holds a PhD in Ecological Modelling from Universität Potsdam (2019), where her thesis explored biodiversity responses to land-use mosaics. Education: Biology studies (Diploma, 2009–2012) at University of Greifswald and Freie Universität Berlin. Her research integrates agent-based modelling, spatial analysis, and policy evaluation to address ecological and socio-economic challenges. Research interests include agricultural landscape simulation, bioenergy impacts on biodiversity, and computational tools for ecological forecasting. She has contributed to projects such as the German Centre for Integrative Biodiversity Research (iDiv) and the HIGRADE graduate school.
Prof. Gisela Detrell is a Professor of Human Spaceflight Technology at the TUM School of Engineering and Design, Technical University of Munich. She specializes in developing technologies for astronautical spaceflight, including life support systems (e.g., microalgae photobioreactors), mission simulations (e.g., Mars/Moon concepts), and virtual reality tools for astronaut training. Her work bridges engineering, biotechnology, and interdisciplinary collaboration. Education: Bachelor/Master in Aerospace Engineering at the Polytechnic University of Catalonia (UPC) PhD from the University of Stuttgart and UPC (2015), focusing on reliability analysis of life support systems for long-duration space missions Research Interests: Prof. Detrell’s research emphasizes sustainable life support systems for extraterrestrial habitats, VR-driven astronaut training, and interdisciplinary design approaches for space stations. Her photobioreactor studies explore algae-based solutions for oxygen and food production on lunar/mars bases, while simulations address mission realism and team performance under extreme conditions. Articles Overview: Her publications span VR docking simulators, ISS-based photobioreactor experiments, and biofiltration systems for closed-loop life support. These reflect a focus on practical, scalable technologies for long-term space habitation. Awards/Grants: No specific honors or grants listed in the text. Her academic contributions are highlighted through her professorship and research group leadership. Labs/Teams: She previously led the research group at the Institute of Space Systems in Stuttgart and currently heads the Human Spaceflight Technology group at TUM.
Fabian Fritz holds an M.Sc. degree and works at the Technical University of Munich (TUM) within the Chair of Aerodynamics and Fluid Mechanics . His research focuses on computational fluid dynamics (CFD) and numerical simulation of multiphase flows, particularly using Smoothed Particle Hydrodynamics (SPH) . He collaborates on projects like PBF-LB/M (additive manufacturing) and contributes to Lagrangian fluid mechanics benchmarking frameworks. Research Trends: His publications emphasize numerical methods (SPH, level-set, finite-volume), multiphase flow modeling , heat transfer , and thermoacoustic stability . Recent work includes hardware-agnostic code optimization and adaptive mesh refinement techniques. Education: Completed a master’s thesis on Diffusive-Interface Modeling of Multiphase Flows with Surface-Tension Effects , supervised by P.D. Dr.-Ing. habil. Stefan Adami.
Jihyun Lee is an Assistant Professor in the Department of Mechanical and Manufacturing Engineering at the Schulich School of Engineering, University of Calgary. She was awarded the Anna Boyksen Fellowship by the Technical University of Munich Institute for Advanced Study (TUM-IAS) in 2021, hosted by Prof. Michael Zäh. Doctorate in Mechanical Engineering from University of Michigan-Ann Arbor (2016) Prior post at Korea Institute of Machinery and Materials (2016-2019) Her research focuses on mechatronics, robotics, manufacturing automation, and control systems , with applications in machine tools, additive manufacturing, and precision measurement. She integrates artificial intelligence and optimization to enhance industrial automation. Recent publications highlight work on vibration control , sensor fusion , and flexible manufacturing systems . Her team explores dynamic modeling , nanocomposite sensors , and human-in-the-loop robotics for industrial and marine applications. 2020 Remote Teaching Award, Schulich Engineering 2020 Early Achievement Award, Association of Korean-Canadian Scientists and Engineers 2018 Best Achievement Award, KIMM She supervises doctoral and master’s students at the University of Calgary, emphasizing hands-on experience and MATLAB/Python simulation skills in her lab. Her work bridges quantum logic and industrial robotics through interdisciplinary collaborations.
Dr. Moritz Ziegler is a geomechanics researcher affiliated with the Technical University of Munich (TUM) and the Assistant Professorship of Geothermal Technologies . He previously worked at GFZ Potsdam (2017–2023) and earned his PhD in Geophysics from the University of Potsdam (2014–2017). His research focuses on geomechanical numerical modeling , uncertainty quantification , and 3D stress field analysis , with applications to geothermal energy, seismic hazard, and rock mechanics. Education: Bachelor of Science in Geosciences (2008–2011), Freie Universität Berlin Master of Science in Geophysics (2011–2014), University of Potsdam PhD in Geophysics (2014–2017), University of Potsdam & GFZ Potsdam His work integrates advanced computational methods ( Altair Hypermesh , Dassault Systèmes Abaqus , Python , Matlab ) to address complex geomechanical problems. Recent publications analyze stress gradients in the North Alpine Foreland Basin, fault-stress interactions, and physics-based machine learning in geomechanics. He has contributed to software development (DOuGLAS v1.0) and calibration tools (FAST Calibration v2.4). Scientific awards or honors are not explicitly mentioned in the provided text. However, his research has been published in leading journals such as Geophysical Journal International , Solid Earth , and Pure and Applied Geophysics .
Prof. Dr.-Ing. Werner Lang serves as Vice President for Sustainable Transformation and holds the Chair of Energy Efficient and Sustainable Design and Building (ENPB) at the Technical University of Munich (TUM), within the TUM School of Engineering and Design. Previously, he was Professor of Sustainable Building and Director of the Center for Sustainable Development at the University of Texas School of Architecture in Austin (2008-2010). Lang also directs the Oskar von Miller Forum and is a partner at Lang Hugger Rampp GmbH Architekten in Munich. Lang's research focuses on developing strategies for buildings with positive environmental footprints through regenerative energy systems, renewable materials, and closed material cycles. His work emphasizes comprehensive life cycle analysis considering ecological, economic, and social aspects. Current research areas include climate-resilient urban neighborhoods, circular economy in construction, and sustainable building materials. The ENPB institute conducts numerous research projects such as Building Climate-Municipal, CircularFTmehrRAUM, and Urban Green Infrastructure. Lang's publications reveal a strong trend toward life cycle assessment, multi-criteria decision-making, and computational approaches for sustainable building design. His recent work integrates machine learning with building performance analysis and focuses on practical implementation of circular economy principles in urban contexts, with increasing emphasis on quantifying environmental benefits of urban green infrastructure. TUM Sustainability Award 2022 Doce et Delecta (Second Prize for Best Teaching), 2019 Bayerischer Energiepreis 2014 International Building Skin Tech Award (2008) Promotionspreis der TUM (2000) Lang leads the Institute of Energy-Efficient and Sustainable Design and Building with numerous research grants including projects like Building.Lab+, NAWAREUM, and ECO+. His team includes researchers working on topics ranging from urban mining to life cycle assessment tools. The institute maintains several products and startups including MoMeBo, Bilanzlabor, and EnergyML that translate research into practical applications for the building industry.
Nils Ole Tippenhauer is a faculty member at the CISPA Helmholtz Center for Information Security , leading the SCy-Phy research group . His academic journey includes an Assistant Professorship at the Singapore University of Technology and Design (SUTD) (2014–2018), a PhD in Computer Science from ETH Zurich (2012), and a Diploma in Computer Engineering from Hamburg University of Technology (2007). He also holds an exchange study year at the University of Waterloo (2004–2005) supported by a DAAD scholarship. Research Interests focus on practical systems security , particularly Security of Cyber-Physical Systems Industrial Control Systems (ICS) and Industrial IoT (IIoT) Physical-Layer Security and Wireless Security Privacy-Preserving Technologies (e.g., DP3T project) Embedded Systems Security Threat Detection & Defenses His work integrates both theoretical and applied approaches, addressing vulnerabilities in critical infrastructures like water systems and power grids. Recent Publications highlight trends in Anomaly detection evasion in industrial networks Microarchitectural side-channel defenses Localization techniques in cellular networks Security analysis of ICS protocols Data-driven vulnerability assessments for robotics Cyber-physical simulation for infrastructure security Scientific Awards include Best paper at DIMVA'23 Distinguished Paper at ACSAC 2022 Best paper at CPSIOTSEC 2022 Best paper at CPSS 2017 K-H Ditze Award for diploma thesis (2007) SG Mark Institution award (2016) Runner-Up at smart energy hackathon (2013) Advising and Grants feature PhD defenses of Daniele Antonioli and Hamid Reza Ghaeini (2022), co-organizing conferences like WiSec and CPSS , and leading projects such as the National Science Experiment (NSE) with 50,000 mobile sensors in Singapore. He also contributed to the DP3T project for privacy-preserving contact tracing. Labs and Teams include the SCy-Phy research group at CISPA and the development of testbeds like SWaT (Secure Water Treatment), WADI (Water Distribution), and EPIC (Electric Power and Industrial Control) at SUTD. These platforms enable hands-on security research in realistic industrial environments.
Prof. Dr.-Ing. Lars Linsen is a full Professor of Computer Science at the Westfälische Wilhelms-Universität (WWU) Münster, leading the VISualization & graphIX (VISIX) group. His primary affiliation is the Institute of Computer Science within the Faculty of Mathematics and Computer Science. He holds adjunct professorships at Jacobs University, Bremen, and has held previous academic roles including Full Professor at Jacobs University (2012–2017) and Associate/Assistant Professor roles in Germany and the U.S. His research focuses on interactive visual analysis, medical visualization, and scientific visualization, with applications in life sciences and engineering. Education: PhD (Dr.-Ing.) in Computer Science from Universität Karlsruhe (2001), M.Sc. (Diplom) in Computer Science (1997), B.Sc. (Vordiplom) in Computer Science (1994). Awards: IEEE Visualization Design Contest Winner (2008, 2022, 2018), Preis des Fördervereins des Forschungszentrum Informatik (2002). Research Highlights: Develops visualization tools for medical imaging (e.g., mass spectrometry imaging, MRI data analysis) and physical simulations (e.g., wildfire spread analysis, asteroid impact modeling). Active in EU-funded projects like Pig-Pro-QuO (surface coatings) and cells-in-motion initiatives. Supervised over 20 PhD/MS advisees, including notable graduates in medical visualization and simulation ensemble analysis. Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions on Visualization and Computer Graphics, Computers & Graphics, and EuroVis. Key works include SciVis contest-winning wildfire analysis frameworks and medical visualization tools for stenosis detection. Teaching: Offers courses on visualization, computer graphics, and computational science. Actively involved in thesis supervision and curriculum development at both WWU Münster and Jacobs University. Grants & Collaborations: Principal investigator on DFG-funded projects (e.g., hemodynamics simulations, ensemble visualization) and industry collaborations (e.g., Tascon GmbH for coating quality analysis). Member of the Cells-in-Motion Interfaculty Centre and CDH board at WWU.
Jonathan Külz is a Researcher at the Technical University of Munich (TUM) , affiliated with the Department of Informatics 6 - Chair for Cyber Physical Systems under Prof. Matthias Althoff. His research focuses on Modular Robotics , Reinforcement Learning , Cyber-Physical Systems , and Control Systems . His work includes algorithmic synthesis of modular robot compositions, model-based manipulator co-design, and unifying benchmarks for robotics. He has supervised multiple Master’s theses Bachelor’s theses Practical courses on topics like Robot Workspace Representation and Dynamic Model Identification . Notable supervised projects include Autonomous Navigation of Reachbot and Task-Based Modular Robot Configuration Synthesis . His recent publications span Robotics , Benchmarking , and Computational Social Science . Key trends include Computationally efficient assessment of robot capabilities Deep reinforcement learning for robotics Analysis of political discourse polarization Jonathan emphasizes structured thesis supervision, requiring exposés, shared folders, and protocol-driven meetings. He advocates for LaTeX in scientific writing and tools like NotebookLM and Zettlr for research documentation.
Antonello Monti is a Professor and Director of the Institute for Automation of Complex Power Systems at RWTH Aachen University. His research focuses on modern power systems, including smart grid technologies, hybrid AC-DC grids, and quantum computing applications in energy systems. Recent publications demonstrate innovations in grid resilience, EV charging optimization, quantum-assisted power system planning, and advanced simulation techniques. His team develops open-source tools like JuliaGrid for power system analysis and validates concepts through real-time testing platforms. Research addresses energy transition challenges including renewable integration, grid modernization, cyber-physical security, and next-generation optimization methods combining quantum computing with traditional power engineering approaches.
Prof. Dr. Martin Burger is a leading scientist at DESY and a Full Professor in the Department of Mathematics at Universität Hamburg, where he leads the Computational Imaging Group. His research bridges applied mathematics, imaging sciences, and machine learning, with a focus on inverse problems, mathematical modeling, and partial differential equations. He has held professorial positions at Universität Münster and FAU Erlangen-Nürnberg prior to his current dual appointment. Full Professor, Universität Hamburg (2023–present) Leading Scientist, DESY, Hamburg (2023–present) Full Professor, FAU Erlangen-Nürnberg (2018–2023) Full Professor, Universität Münster (2006–2018) His research interests include inverse problems, variational regularization, optimal transport, kinetic models, and mathematical modeling in biology and social sciences. He has made significant contributions to imaging reconstruction, sparse neural networks, and the analysis of transformer architectures. His work often integrates theoretical analysis with computational methods, influencing both pure and applied mathematics. The most recent articles reflect a strong trend toward interdisciplinary applications, combining deep learning with PDE-based modeling, analyzing social and biological systems via kinetic and mean-field models, and advancing mathematical imaging through graph-based and optimal transport methods. His publications span high-impact venues in applied mathematics and computational science. Calderon Prize, Inverse Problems International Association (IPIA) ERC Consolidator Grant (2014) Invited speaker at ECM (2021), ICM (2022), and ICIAM (2023) Editor-in-Chief, European Journal of Applied Mathematics (since 2017) Prof. Burger has supervised numerous PhD students and postdoctoral researchers, many of whom appear as co-authors in his publications. His research is supported by major grants, including funding from the German Federal Ministry of Education and Research (BMBF). He is actively involved in collaborative projects across mathematics, physics, and engineering disciplines. He leads the Computational Imaging Group at DESY, fostering a collaborative environment for developing novel mathematical tools in imaging science. The group works on both theoretical foundations and practical implementations, contributing to advancements in tomography, machine learning, and data analysis.
Antonio Vairo is a full Professor at the Department of Physics, TUM School of Natural Sciences, Technical University of Munich, where he holds the Chair of Theoretical Physics - Applied Quantum Field Theory (T39) at the James-Franck-Str. 1/I campus in Garching bei München. His research focuses on the theoretical foundations of quantum chromodynamics with emphasis on heavy quark systems and non-perturbative phenomena. Professor Vairo's primary research interests include Quantum Chromodynamics (QCD), Heavy Quark Physics, Lattice Gauge Theory, Effective Field Theories, and Exotic Hadron Spectroscopy. His work bridges computational approaches with analytical frameworks to investigate quarkonium dynamics in extreme environments like the quark-gluon plasma, while developing novel applications of Born-Oppenheimer effective theory to multi-quark systems. Recent investigations extend into dark matter bound state formation in the early universe, demonstrating interdisciplinary reach across particle physics and cosmology. Analysis of his 2024-2025 publications reveals three dominant research thrusts: (1) quarkonium suppression mechanisms in heavy-ion collisions using open quantum systems approaches, (2) high-precision lattice QCD computations of static forces and chromoelectric correlators, and (3) systematic development of effective field theories for exotic hadrons and dark matter pairs. His work on pNRQCD (potential non-relativistic QCD) provides critical connections between lattice results and experimental observables in heavy-ion physics. Professor Vairo maintains active research leadership through collaborations with international groups including the Belle II experiment, as evidenced by his contributions to 'The Belle II Physics Book'. His methodological innovations in applying quantum trajectory methods to quarkonium evolution and developing FeynOnium computational tools for effective field theories demonstrate significant technical contributions to the field. Current research directions emphasize next-to-leading order corrections in heavy quark dynamics and Debye mass effects in dark matter bound state formation.
