Prof. Alois Christian Knoll is a full professor at the Technical University of Munich (TUM) in the School of Computation, Information and Technology. His academic career includes roles at Bielefeld University and leadership in major EU initiatives like the Human Brain Project and ECHORD++. He specializes in robotics, AI, and autonomous systems, with a focus on medical robotics, sensor-based systems, and neuromorphic engineering. Knoll has supervised over 100 doctoral theses and authored/co-authored over 1,000 publications. Education: Diploma in Electrical Engineering (University of Stuttgart, 1985); PhD in Computer Science (Technical University of Berlin, 1988); Habilitation (TU Berlin, 1993). He has been at TUM since 2001, leading the Robotics, AI, and Real-Time Systems department. Research interests span autonomous systems, neuro-IT integration, and traffic simulation. Key projects include fortiss (Bavarian State Institute for Computer Science) and TUM-CREATE (Singapore collaboration). Awards include IEEE Fellow, University of Tokyo Fellow, and the Carl-Ramsauer-Prize (1990). Current roles include editorships in robotics journals, leadership in EU flagship projects, and teaching across multiple programs. His work bridges computer science, neuroscience, and engineering, with applications in healthcare, automotive systems, and urban mobility.
Prof. Dr. Mirko Hornung is a Professor of Aircraft Design at the TUM School of Engineering and Design, Technische Universität München. His research focuses on conceptual aircraft design, integration of propulsion systems, and evaluation of aviation technologies in operational contexts. Education and Career: PhD in Aeronautical Engineering from the University of the Bundeswehr (2003), awarded a research prize for work on reusable space transport systems. 2003–2009: Worked at Airbus Group (EADS) on military air systems, propulsion integration, and program management. Executive Director of Research & Technology at Bauhaus Luftfahrt, a think tank for long-term aviation developments. Research Interests: Aircraft design optimization, including hybrid energy systems, electric propulsion, and UAV technologies. Environmental sustainability in aviation, such as hydrogen-powered aircraft and lifecycle assessment. Aerodynamic and structural analysis, including flutter suppression and composite materials. Key Publications Highlight Trends: Focus on hybrid-electric and hydrogen propulsion for reducing environmental impact. Advancements in UAV design, including morphing wings and autonomous systems. Integration of AI-driven tools for propulsion optimization and lifecycle analysis. Scientific Awards: EADS Promotion Award (1995) Research Prize for Thesis on Reusable Space Transport Systems (2003) Advising & Grants: Directs research at Bauhaus Luftfahrt, collaborating on future aviation concepts. Engaged in interdisciplinary projects like FLEXOP UAV demonstrator and Ce-Liner eMobility studies. Labs/Teams: Active in the Aircraft Design Professorship at TUM and leadership roles at Bauhaus Luftfahrt, focusing on next-generation aviation technologies.
Max Planck Institute for Dynamics of Complex Technical SystemsGermany
Peter Benner is a Professor and Director at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, where he leads the Computational Methods in Systems and Control Theory group. He also holds an Honorarprofessor position for Mathematics at Otto-von-Guericke Universität Magdeburg since 2011. Benner has previously served as Managing Director of the Max Planck Institute during multiple periods (2013-2014, 2021-2022, and 2025-2026), demonstrating his leadership in the field. Benner's research focuses on Scientific Machine Learning, Numerical Linear and Multilinear Algebra, Model Order Reduction and Reduced-order Modeling, Numerical Methods in Systems and Control Theory, PDE Constrained Optimization, High-performance and Power-aware Computing, and Mathematical Software development. His work bridges theoretical mathematics with practical engineering applications, particularly addressing challenges in large-scale dynamical systems. Analysis of his recent publications reveals a strong emphasis on developing efficient computational methods for complex systems. Benner has pioneered approaches combining model order reduction with tensor methods to tackle high-dimensional problems in uncertainty quantification and PDE-constrained optimization. His work shows a consistent trend toward integrating data-driven techniques with traditional model-based approaches, particularly for nonlinear and parametric systems. Throughout his career, Benner has actively mentored students and collaborated with researchers worldwide, delivering numerous invited talks at prestigious institutions and conferences across Europe, North America, and Asia. His research has received significant funding, supporting the development of mathematical software and computational methods for industrial applications. Benner leads the Computational Methods in Systems and Control Theory department at the Max Planck Institute, which focuses on developing and implementing advanced numerical methods for large-scale dynamical systems. The group maintains strong connections with both theoretical mathematics and practical engineering applications, particularly in fluid dynamics, energy systems, and control theory.
Prof. Dr. Christian Breitsamter is a Professor at the Technische Universität München (TUM), leading the Chair of Aerodynamics and Fluid Mechanics within the TUM School of Engineering and Design. He has held this position since 2007 and has been a member of key committees such as the ICAS Programme Committee and STAB-Programmleitung. His research focuses on aerodynamics of aircraft and rotorcraft configurations, including vortex dynamics, aeroelasticity, and fluid-structure interaction. Education: PhD in Aerodynamics (1997) Master’s in Aerospace Engineering (1989) Research Interests: Prof. Breitsamter’s work spans experimental and numerical studies of high-agility aircraft, helicopter aerodynamics, and advanced wing designs. Key areas include leading-edge vortices, gust load mitigation using flexible wings, and flow control techniques. His group investigates cutting-edge topics like deep learning for buffet prediction and hybrid neural networks for aerodynamic modeling. Awards: Willy Messerschmitt Preis (1999) AIAA Associate Fellow (2007) Advising & Grants: While specific student names are not listed, his research involves collaborative projects with industry partners (e.g., RACER Compound Helicopter) and EU initiatives like the FURADO program. His team contributes to the NFDI4ING infrastructure for engineering data. Labs/Teams: Active in the Aerodynamics Wind Tunnel facilities (Windkanäle A/B/C) and leads the SAGITTA flying wing demonstrator project. His group also explores membrane wings and elasto-flexible morphing technologies.
Marc Hodes is Professor in Mechanical Engineering and Mathematics at Tufts University. With a PhD from MIT, his research focuses on heat transfer phenomena with applications in electronics cooling, supercritical fluids, and thermoelectric systems. He directs the graduate program in Mechanical Engineering. Education: BS, University of Pittsburgh (1990) MS, University of Minnesota (1994) PhD, Massachusetts Institute of Technology (1998) Research Areas: Thermal management of electronics through microchannel cooling and liquid metal technologies; Apparent slip phenomena in microstructured surfaces; Mass transfer in supercritical CO 2 systems for aerogel processing; Thermoelectric module optimization for precision temperature control. Awards & Honors: NSF REU Fellowship (1989) E.T.S. Walton Visitorship Award Best Associate Editor, ASME Journal of Heat Transfer (2023) Research Leadership: Principal investigator on multiple NSF grants including projects on aerogel manufacturing, dropwise condensation, and analysis of convection in slip flows. Industry collaborations include Google, DARPA, and Bell Labs.
Professor Jia Chen is a Professor of Environmental Sensing and Modeling at the Technical University of Munich (TUM), holding positions in both the TUM School of Computation, Information and Technology (CIT) and the Department of Electrical and Computer Engineering, as well as the Department of Civil, Geo and Environmental Engineering. She also maintains an affiliation as an Associate at Harvard University. Her pioneering work focuses on developing novel optical sensors and atmospheric models to monitor and quantify greenhouse gas emissions in urban environments. Professor Chen's most significant contribution is the development of the differential column measurement method and the establishment of MUCCnet, the world's first permanent urban column sensor network. This groundbreaking work enables continuous, city-wide monitoring of greenhouse gases. Her research team has made notable discoveries, including quantifying methane emissions from events like the Munich Oktoberfest and identifying previously underestimated urban emission sources. Her research spans atmospheric science, environmental engineering, and climate change mitigation, with particular emphasis on: Urban greenhouse gas monitoring systems Advanced atmospheric modeling techniques Sensor network development for environmental monitoring Integration of machine learning with emission quantification Urban air quality assessment methodologies Professor Chen has received numerous prestigious awards including: Timothy Oke Award (2024) for original research in urban climatology ERC Consolidator Grant (2022) Arnold Sommerfeld-Award (2021) Germany's "Top 40 under 40" recognition by Capital Magazine (2020) Membership in the Global Young Academy (2021) She leads an extensive research group with numerous PhD students and postdoctoral researchers, and her work is supported by major funding from ERC, EU Horizon 2020, United Nations Environment Programme, NASA, ESA, German Federal Ministry of Education and Research, and German Research Foundation. Professor Chen has authored over 180 publications and 12 patents, with an h-index of 35.
Prof. Dr.-Ing. Elisabeth Clausen is a Professor and Director of the Chair and Institute for Advanced Mining Technologies at RWTH Aachen University. She holds key roles in the Specialist Group for Raw Materials and Disposal Technology, serves as a rectorate representative, and leads the Commission for EU Research Funding. Her research spans Underground mining automation Acoustic emission diagnostics Sustainable mining systems Space resource extraction Advanced sensor technologies Her recent publications focus on autonomous mining machinery, underground communication systems, and acoustic emission analysis across 15+ studies from 2013–2025, with particular emphasis on Ultra-wideband positioning Thermographic detection Crack monitoring in planetary gearboxes Explosive atmosphere safety Mineral processing diagnostics Digitalization trends Prof. Clausen contributes to mining education reform through initiatives like CDIO™ and has developed innovative learning spaces in underground mines. She coordinates international educational labs and integrates sustainability into mining engineering curricula, with publications on Adaptive ventilation systems Mining education frameworks Future-proof mineral extraction Entrepreneurial mindset in engineering
Prof. Chiara Manfletti is a Professor at the Technical University of Munich (TUM), leading the Chair of Space Propulsion and Mobility. She also serves as Director and COO of Neuraspace. Her academic journey includes a degree from Imperial College London (2001), a master's from the International Space University (2002), and a PhD from RWTH Aachen (2010). Previously, she worked at the German Aerospace Center, served as Programme Advisor to the European Space Agency Director General, and became the first President of Portugal's national space agency. Her research focuses on innovative propulsion systems, satellite autonomy, and AI-driven propulsion controls. She has received the National Defence Medal (2020) and Medal of Merit (2020) from Portugal. Research Interests: Democratization of space access via novel propulsion technologies Autonomous and sustainable satellite propulsion systems Data-driven propulsion control using AI and health monitoring Key Contributions: Her work bridges numerical/experimental expertise with space safety policy. Recent publications analyze water hammer phenomena in propulsion systems and propose frameworks for planetary protection in space activities. Awards: National Defence Medal 1st class (2020) Medal of Merit from Portuguese Ministry of Science (2020) Professional Roles: Combines academic leadership with industry roles, actively shaping space policy and innovation. No listed grants are detailed publicly in the provided text.
Ulrich Tallarek serves as Professor of Analytical Chemistry in the Faculty of Chemistry at Philipps University of Marburg, where he has held a W3 professorship since 2011. He also serves on the Board of Directors for the Materials Science Center at the university, a position he has held since 2007. His research group focuses on the fundamental understanding of transport phenomena in porous media with applications spanning chromatography, battery technology, and microfluidic systems. The group maintains strong collaborations with institutions worldwide and secures substantial research funding for advanced computational and experimental work. Professor Tallarek's research interests center on functional porous solids, with specific focus on morphology-transport-performance relationships. His work bridges multiple scales from molecular dynamics simulations of solute behavior in nanopores to macroscopic transport in chromatographic columns and battery electrodes. Key research areas include diffusion in hierarchical porous media, electrokinetic phenomena in microfluidic systems, molecular simulation of chromatographic processes, and advanced characterization of porous materials using tomography and other techniques. His group has pioneered multiscale simulation approaches that connect molecular-level surface chemistry to macroscopic transport properties. The research output demonstrates consistent focus on understanding fundamental transport mechanisms in porous systems, with recent publications emphasizing multiscale simulation techniques, molecular dynamics studies of solvent effects in chromatography, advanced characterization of mesoporous structures, and applications to separation science and energy storage. The work shows strong integration of computational modeling with experimental validation across multiple length scales. 2003: Desty Memorial Prize for Innovation in Separation Science, The Royal Institution of Great Britain, London 2006: Young Scientist Award from DECHEMA e.V. 2011: Named Discussion Leader at the 2011 Gordon Research Conference on Physics & Chemistry of Microfluidics 2011–2012: Chairman of the German Chemical Society (GDCh), Marburg 2013: Finalist, World Technology Awards, for category Environment 2013: Named as one of the 100 most influential analytical scientists in the world (The Analytical Scientist Power List) 2017: Recipient of the Silver Jubilee Medal 2017, The Chromatographic Society, UK Professor Tallarek's research has been supported by numerous grants enabling high-performance computing resources, advanced instrumentation, and international collaborations. His group maintains strong ties with industry partners in separation science and analytical instrumentation. The Tallarek Research Group includes postdoctoral researchers, PhD students, and technical staff working across experimental and computational domains. Current projects focus on molecular simulation of chromatographic processes, advanced characterization of porous battery electrodes, and development of novel separation methodologies. The Tallarek Research Group operates state-of-the-art facilities for computational modeling, including access to high-performance computing resources at Forschungszentrum Jülich. The group also maintains experimental capabilities for chromatographic analysis, materials characterization, and microfluidic device development. Their work on physically reconstructed porous media has established new standards for connecting microstructure to transport properties in complex materials systems.
Anna C. Balazs is Distinguished Professor and John A. Swanson Chair of Engineering in the Department of Chemical Engineering at the University of Pittsburgh, with an adjunct appointment in Chemistry and visiting professorships at Scripps Research Institute, UT-Austin and Oxford University. In 2025 she receives the €10,000 Gutenberg Research Award from Johannes Gutenberg University Mainz (JGU) for her pioneering theoretical work on smart soft materials. She earned an A.B. in Physics from Bryn Mawr College (1975) and a Ph.D. in Materials Science from MIT (1981), followed by post-doctoral research at Brandeis, MIT and UMass. Research interests span theoretical and computational soft-matter physics, focusing on: Statistical-mechanical modelling of polymer blends and composites Self-oscillating and chemo-responsive hydrogels Active matter, enzyme-powered swimmers and self-propelling sheets Self-healing, shape-morphing and bio-inspired materials Computer simulation of colloidal and interfacial phenomena Recent publications (2023-2025) demonstrate a clear trend toward integrating chemistry, fluid mechanics and elasticity to create life-like, autonomous soft machines. Key contributions include: Harnessing enzyme pumps to drive macroscopic sheet locomotion Designing chemically communicating micro-post arrays Creating dissipative materials with programmable, hierarchical 3-D architectures Scientific awards include: Gutenberg Research Award 2025 Polymer Physics Prize, American Physical Society SF Boys-A. Rahman Award, Royal Society of Chemistry Langmuir Lectureship Award, American Chemical Society Election to the U.S. National Academy of Sciences (2021) She serves on the Advisory Board of the DOE-BES Materials Council and on editorial boards for Langmuir , Soft Matter and Polymer Reviews . Her group collaborates closely with experimental teams world-wide, including the DFG-NSF “Confine” partnership with JGU and the CoM2Life Cluster of Excellence initiative.
Prof. Dr.-Ing. Harald Klein holds the Professorship of Plant and Process Engineering at the TUM School of Engineering and Design (Technical University of Munich). His research focuses on process engineering analysis and synthesis, particularly thermal/chemical unit operations applied to power plant technology. Develops thermodynamic substance models & simulation tools Expertise in industrial process design and optimization Collaborates on hydrogen liquefaction and biofuel production Research trends: 2016-2017 publications show emphasis on sustainable energy systems Combines traditional process engineering with modern optimization Key domains: hydrogen technology, chemical reactors, and thermal systems
David Schlipf is a Professor at the Fachbereich Energy and Life Science, Hochschule Flensburg, leading the Wind Energy Technology Institute. His expertise spans lidar-assisted control systems, floating offshore wind turbines, and aeroelastic modeling. He actively collaborates with international initiatives like IEA Wind Task 32 and contributes to projects such as the 'Lidar Knowledge Europe (LIKE)' network. His research focuses on enhancing wind turbine efficiency through advanced control strategies and sensor technology integration. He has been instrumental in developing the TorqTwin open-source framework for multibody modeling and has published extensively on topics including wind field reconstruction, load mitigation, and floating platform dynamics. His work bridges academic research with industrial applications, emphasizing practical solutions for offshore wind energy challenges. Notable projects include the evaluation of lidar-assisted control performance, optimization of floating turbine designs, and contributions to wind energy education's role in climate resilience. His research outputs span over 200 publications, highlighting his global impact in advancing renewable energy systems.
Lukas Einhaus is a Researcher and PhD student in the Embedded Systems department at the University of Duisburg-Essen since April 2020, affiliated with the Intelligent Embedded Systems (IES) research group and contributing to initiatives including Elastic AI and the IoT Garage. His academic background includes: Bachelor of Science from University of Duisburg-Essen, thesis focused on programming abstractions for concurrent embedded systems Master of Science from University of Duisburg-Essen, specializing in distributed and reliable systems with thesis research on quantizing neural networks Einhaus's research centers on designing neural networks for efficient hardware implementation on FPGAs, with primary expertise in quantized or low-precision neural networks that reduce bit depth (typically 1-3 bits) for computations and information flow. This work enables energy-efficient AI solutions for embedded and IoT devices where resource constraints are critical. His publication record from 2021-2025 reveals consistent innovation in FPGA-based neural network optimization, with applications spanning fluid flow estimation, time-series analysis, and real-time stream processing. Core themes include Elastic AI for adaptive systems, precomputation techniques for convolutional layers, and hardware-aware neural architecture design. He previously contributed to the BMBF-funded project "KI-Sprung: LUTNet" (until March 2022), developing energy-efficient AI networks using elementary lookup tables for FPGA deployment. Einhaus actively mentors students through the IoT Garage initiative, supervising practical projects including drink-mixing machines, exoskeletons, and ball-challenge systems.
Prof. Can Dincer is a Professor of Sensors and Wearables for Healthcare at the TUM School of Computation, Information and Technology, Technische Universität München (TUM). His research focuses on bioanalytical materials, wearable sensors, and AI-driven diagnostics for One-Health applications, integrating disposable sensor technology with data science. He holds a doctorate from the University of Freiburg (summa cum laude, 2016) and worked as a visiting scientist at Imperial College London before joining TUM in 2024. He is a member of the Munich Institute of Biomedical Engineering (MIBE). Key research interests include: Development of wearable biosensors for real-time health monitoring CRISPR-based diagnostics for nucleic acids and proteins AI integration for therapeutic drug monitoring in sepsis and other critical conditions Environmental health connections via point-of-need diagnostics Notable achievements include the 2021 Biosensors & Bioelectronics Best Paper Award and inclusion in Stanford's World's Top 2% Scientists since 2022. His work spans clinical applications, microfluidic platforms, and nanotechnology-based solutions for healthcare challenges. Publications highlight innovations like optogenetic bioassays (Science Advances, 2024), CRISPR-powered multiplexed biosensors, and wearable systems for continuous biomarker monitoring. His research bridges material science, electrical engineering, and biomedicine to create practical diagnostic tools. Prof. Dincer collaborates across disciplines, focusing on translating lab innovations into clinical and commercial applications through advanced sensor technologies.
Leonid Goubergrits is a Professor of Cardiovascular Modeling and Simulation at the Einstein Center Digital Future and Charité – Universitätsmedizin Berlin . With a background in applied mathematics and physics from the Moscow Institute of Physics and Technology, he has dedicated his career to applying computational fluid dynamics (CFD) to cardiovascular medicine since immigrating to Germany in 1995. His work bridges fundamental research and clinical applications, aiming to integrate numerical models into everyday medical practice to enhance diagnostics and reduce invasiveness. Doctorate at Technische Universität Berlin (2000) Habilitation at Technische Universität Berlin (2016) His research spans blood flow modeling in coronary vessels, cerebral aneurysms, heart valves, and the aorta, alongside artificial organ development and blood damage modeling . He leads a research group at Charité and the German Heart Center Berlin, focusing on patient-specific simulations and their translation to clinical settings. Recent publications highlight his work on deep learning integration for hemodynamic analysis, 4D Flow MRI validation , and medical device optimization using computational models. His team’s research includes virtual therapy planning for aortic valve replacements, hemolysis modeling , and pulmonary artery pressure sensors . Leonid actively contributes to education, redesigning TU Berlin’s Fluid Mechanics in Medicine curriculum and fostering interdisciplinary collaboration between engineers, physicians, and computer scientists. His vision emphasizes the digital transformation of medicine through computational modeling and simulation.
