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Prof. Dr. Marcus Vetter is the founder and director of the Institute for Applied Artificial Intelligence and Robotics (A²IR) at Mannheim University of Technology's Faculty of Information Technology. His work bridges Deep learning Medical imaging and navigation Embedded systems Real-time computing Software engineering for medical devices He has taught courses including Deep Learning Methods, Image-Guided Medicine, and Embedded Systems. Education Computer Science, Technical University of Mannheim, 1999 Doctorate ('summa cum laude superato') in 'Image-based navigation systems', University of Heidelberg, 2003 Research focuses on AI-driven medical imaging tools, real-time deformation models, and open-source frameworks like MITK. His 15 most recent publications span 6D pose estimation for medical robotics Spectroscopy-based diagnostics Formal software verification Gesture and gaze recognition interfaces UAV drive train optimization Scientific achievements Doctorate with distinction (2003) Co-founder of MITK open-source project Director of A²IR institute since 2007 He has received BMBF grants for real-time deformation models and tracking systems, and has led development of navigation systems for laparoscopic surgery and cardiac ablation procedures.

• Deep Learning
• Medical Technology
• Embedded Systems
• +4 more

Raziye Tekin is an Associate Professor from Turkey and currently serves as a Technical Lead at ROKETSAN Inc. in the defense industry. She holds a doctoral degree from the Technical University of Munich (TUM) with a thesis titled 'A New Design Framework for Impact Time Control' and has conducted research at the German Aerospace Center. Her academic roles include co-chair of the European Guidance, Navigation and Control Technical Committee (TC), membership in the AIAA GNC TC, and an associate editor position for IEEE Transactions on Aerospace and Electronics Systems. Education: Bachelor's in Control Engineering from Istanbul Technical University (2006) Master's in Electrical and Electronics Engineering from Middle East Technical University (2010) PhD from TUM (2018) Research interests focus on missile guidance and control systems, including trajectory shaping, impact-angle control, thrust vector control, and vertical launch systems. She has contributed to both academic and industrial applications of aerospace sciences, integrating theoretical frameworks with practical defense technologies. Scientific Awards: Best Thesis Award (Master’s, Middle East Technical University) Research and Development Awards from ROKETSAN and ASELSAN Top Ten Most Read Article in AIAA Journal of Guidance, Control, and Dynamics Her work emphasizes robust autopilot design and trajectory optimization, with grants including the Rudolf Diesel Industry Fellowship at TUM-IAS. She collaborates across disciplines to address challenges in advanced air mobility, particularly through her Focus Group on 'Smart GNC for Advanced Air Mobility.'

• Aerospace Engineering
• Guidance, Navigation, and Control (GNC)
• Flight Dynamics
• +3 more

Enrico Rukzio is a Full Professor of Human-Computer Interaction at the University of Ulm, leading the Human-Computer Interaction group and directing the Institute for Media Research and Media Development. His research spans interactive systems design, focusing on automotive UIs, extended reality, accessibility, and sustainable interaction. He holds a Ph.D. in Computer Science from the University of Munich and has held prior roles at Lancaster University and the Ruhr Institute for Software Technology. Roles: Faculty Dean (2017–2020), Admissions Committee Chairman, Doctoral Committee Chairman Educations: Ph.D., Munich; Lecturer qualifications from Lancaster and Duisburg-Essen Research emphasizes enabling efficient, inclusive, and sustainable interactions through novel interfaces. His work addresses automated vehicles, health-supporting tech, and accessibility for visually impaired users. Recent articles explore Bayesian optimization for UI design, automated vehicle communication, and urban air mobility visualization. Notable awards include best paper recognitions at CHI, EuroVR, and IEEE VR. His grants come from BMBF, DFG, and industry partners like Mercedes-Benz Group. Advises on over 20 funded projects and has mentored award-winning students.

• Human-Computer Interaction (HCI)
• Automotive User Interfaces
• Extended Reality (XR)
• +5 more

Prof. Dr.-Ing. Katharina Schmitz serves as Institute Director and Vice Dean at the Institute for Fluid Power Drives and Systems, RWTH Aachen University. Her leadership within the Production Technology Cluster and extensive contributions to fluid power engineering establish her as a leading authority in mechanical engineering research and education. Her research spans fluid power systems, hydraulic component design, tribology, and physics-informed machine learning applications. She pioneers sustainable propulsion solutions through bio-hybrid fuels research while addressing fundamental challenges in polymer material behavior under hydraulic stresses. Current work focuses on carbon-neutral heavy-duty transportation, physics-based neural networks for lubrication modeling, and advanced control systems for electro-hydraulic actuators. Analysis of her 15 most recent publications reveals a dominant trend toward integrating physics-based modeling with deep learning to solve complex engineering problems. Her team consistently develops novel frameworks for cavitation prediction, flow rate determination, and material compatibility assessment - significantly advancing fluid power system reliability, efficiency, and digitalization. Scientific recognition includes: GfT Förderpreis 2023 for experimental and simulative investigation of partially hydrostatic relieved contacts in variable speed axial piston machines As head of the Institute for Fluid Power Drives and Systems, she leads cutting-edge research in sustainable fluid power technologies. The institute maintains strong industry partnerships while driving innovation in hydraulic component design, digital twins for condition monitoring, and next-generation propulsion systems through its position within RWTH Aachen's Production Technology Cluster.

• Fluid Power Engineering
• Hydraulic Systems
• Tribology
• +4 more

Dongdong She is an Assistant Professor in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology (HKUST). His research focuses on the intersection of security and machine learning, applying data-driven approaches to solve security problems. He has established himself as a prominent researcher in software security and fuzzing techniques with publications in top conferences including IEEE S&P, CCS, and USENIX Security. Dr. She received his Ph.D. from Columbia University's Department of Computer Science, where he worked with Professors Suman Jana and Baishakhi Ray. Prior to Columbia, he conducted research with Zhiyun Qian on Android Security at the University of California, Riverside. He completed his undergraduate studies at Huazhong University of Science and Technology. His research spans two main areas: LLM Security, which investigates the security of large language models and LLM-powered systems, and LLM for Traditional Security, which leverages LLMs to solve traditional security problems such as program analysis and vulnerability discovery. His work often combines machine learning techniques with traditional security approaches to develop innovative solutions for software security challenges. Dr. She's publication record shows a consistent evolution from foundational work in neural network-assisted fuzzing (NEUZZ) toward more advanced applications in LLM security and program analysis, demonstrating both theoretical rigor and practical impact with techniques adopted by the security community. Among his notable achievements: Distinguished Paper Award at ISSTA 2025 Distinguished Paper Award at IEEE S&P 2025 Best Paper Award Runner-Up at CCS 2022 Second Place in SBFT 2024 Fuzzing Competition Finalist in 2019 NYU CSAW Applied Research Competition Dr. She currently advises several Ph.D. students including Yuchong Xie, Shuangjie Yao, and Qiao Zhang, who began their studies in Fall 2024. He serves on program committees for major conferences including ASE 2025, where he is a PC Member for the Research Papers track. His research is supported by grants enabling his team to pursue innovative approaches at the intersection of machine learning and security. His research group maintains active collaborations with institutions worldwide and contributes to open-source security tools that are widely used in both academia and industry, with a particular focus on developing advanced techniques for software security analysis through the application of machine learning.

• Security
• Machine Learning
• Fuzzing
• +3 more

Felix Ebert, M.Sc., is a Researcher at the Chair of Space Mobility and Propulsion at the Technical University of Munich (TUM), where he has worked since March 2022. His research focuses on intelligent control systems for rocket engines, particularly fault detection and recovery mechanisms to enhance spacecraft reliability. He is actively involved in the development of the ASCENT Hopper , a test platform for autonomous control algorithms. Research Highlights : Advancing adaptive control strategies for fault-tolerant rocket propulsion systems Investigating water electrolysis propulsion for CubeSats Contributing to SPARK's mission for innovative, sustainable space propulsion solutions Recent Publications demonstrate his work on autonomous recovery systems for low-atmosphere hoppers and green propulsion in small satellites. His projects align with Europe's need for reusable, cost-effective propulsion technologies in the face of growing private-sector space exploration.

• Rocket Propulsion Systems
• Intelligent Control Algorithms
• Fault Detection and Recovery
• +3 more

Karim Cherifi is a Researcher at the Institute of Mathematics , Technical University of Berlin, within the College of Mathematics and Natural Sciences. His academic journey includes a PhD in Control Theory (2015–2019) and postdoctoral work at the Max Planck Institute Magdeburg (2019–2020). Since 2021, he contributes to the ProFIT project "Electric Drives 2.0" at the Werner von Siemens Centre (WvSC). 2010–2013: Bachelor in Electrical and Electronic Engineering 2013–2015: Master in Control Engineering 2015–2019: PhD in Control Theory His research focuses on Control Theory , Numerical Analysis , and Port-Hamiltonian Systems , with applications in Linear Systems , Data-driven Modeling , and Model Reduction . Key trends include geometric formulations for discrete-time systems, dissipativity analysis, and integration of energy-based models with machine learning. Notable scientific recognition includes the DAAD Scholarship (2018) . His work spans publications on topics like structure-preserving interconnections, digital twin simulations, and data-driven realization techniques. Affiliated with the Institute of Mathematics at TU Berlin, he is based in Room MA 469 and collaborates within the Numerical Analysis research group.

• Control Theory
• Numerical Analysis
• Port-Hamiltonian Systems
• +3 more

Matthias Heller is a Professor at Technische Universität München (TUM) and holds the title of Honorary Professor for Highly Augmented Aircraft Systems. He is affiliated with the Department of Flight Mechanics & Performance and has been a Rudolf Diesel Industry Fellow at TUM-IAS since 2010. His research focuses on flight dynamics, robust control systems, and handling qualities analysis for advanced aircraft configurations. Heller has extensive industry experience with Airbus Defence & Space, where he contributed to flight control system development and stability analysis of hypersonic vehicles. Education: 1987–1992: Aerospace Engineering, TUM (Diplom Ingenieur) 1999: Dr.-Ing. (summa cum laude) from TUM, Dissertation: “Analysis and Robust Control of the Lateral Dynamics of Hypersonic Vehicles” Research Interests: Flight dynamics modeling & simulation Robust flight control system design Pilot-in-the-loop oscillation (PIO) prevention Handling qualities assessment for autonomous systems Stability analysis of innovative aircraft configurations Key Achievements: Willy Messerschmitt Prize (2001) for contributions to flight dynamics research Founder of the Focus Group “Aircraft Stability and Control” at TUM-IAS Leading work on UAV control systems and hybrid flight control architectures Labs & Collaborations: Active in the Safe Adaptive Dependable Aerospace Systems (SADAS) Focus Group, focusing on dynamics and control of autonomous flight systems. Previously led the Aircraft Stability and Control group.

• Flight Mechanics
• Flight Control Systems
• Aerospace Engineering
• +3 more

Ralf Salomon is a Professor at the Faculty of Computer Science and Electrical Engineering , University of Rostock , Germany. He holds the title of Prof. Dr.-Ing. habil. and is actively involved in research and teaching in embedded systems, localization, and signal processing. University: University of Rostock School: Faculty of Computer Science and Electrical Engineering Position: Full Professor Contact: Room 201, Tel: +49 381 498 7260 His research focuses on high-precision time measurement , ambient assisted living , industrial embedded systems , and localization technologies . He applies bio-inspired principles, particularly from the barn owl auditory system, to develop low-cost, high-accuracy systems. His work spans health monitoring (e.g., fall detection, cochlear implants), sports technology, and animal experimentation systems. The recent publications (2020–2025) show a strong trend in sensor systems , embedded vision , and real-time measurement , with applications in sports, healthcare, and automation. His work combines theoretical innovation with practical implementation, often using FPGAs and microcontrollers. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: He advises students such as Theo Gabloffsky , who co-authors multiple publications and assists in teaching. He has led multiple funded projects including Welisa (DFG Graduate College) , iHeal , CurlDat , and BOUNCE . Many of his projects focus on health, localization, and embedded intelligence. Labs and Teams: He collaborates closely with researchers like Ralf Joost , Matthias Hinkfoth , Gerald Bieber , and Marian Lüder . His team develops FPGA-based systems, embedded sensors, and intelligent algorithms for real-world applications in health, industry, and sports.

• Embedded Systems
• Localization and Positioning
• Time Interval Measurement
• +12 more

Prof. Rolf Findeisen is a Professor in the Department of Control and Cyber-Physical Systems (CCPS) at Technische Universität Darmstadt. His work focuses on advancing control theory and its applications in cyber-physical systems, autonomous systems, and energy storage systems. Key areas include model predictive control (MPC), battery management systems, machine learning integration into control frameworks, and optimization of crystallization processes. He leads research on safety-critical systems, data-driven control methods, and interdisciplinary applications in robotics and biotechnology. His research spans theoretical advancements in MPC stability, stochastic control, and Gaussian process modeling, alongside practical implementations in autonomous vehicles, lithium-ion battery systems, and bioprocess optimization. Notable contributions include frameworks like HILO-MPC for integrating machine learning with control systems, and methodologies for safe exploration in autonomous navigation. Prof. Findeisen's publications emphasize energy-efficient trajectory planning, fault detection in battery systems, and real-time optimization of manufacturing processes. His work bridges academic theory with industrial applications, addressing challenges in scalability, safety, and computational efficiency. His lab collaborates on national projects like IN-Fly-Tec and INFLIGHT, focusing on innovative flight control systems and sensor technologies. Current research trends include hybrid intelligent optimization, cybergenetic control of microbial systems, and safe reinforcement learning for control systems.

• Model Predictive Control (MPC)
• Cyber-Physical Systems
• Battery Systems Optimization
• +5 more

Prof. Dr. Po Wen Cheng is a Professor and Head of the Stuttgart Chair of Wind Energy (SWE) at the Institute of Aircraft Design, University of Stuttgart. His research focuses on wind energy systems, including floating offshore wind turbines, lidar applications in wind farm control, and structural dynamics of renewable energy systems. He leads interdisciplinary projects addressing challenges in mooring systems, aeroelastic analysis, and noise mitigation. Key areas of expertise include aerodynamic load optimization, lidar-assisted control strategies, and numerical modeling of wind farm interactions. His work integrates advanced machine learning techniques for predictive maintenance and performance enhancement. Cheng collaborates with international institutions and participates in high-profile wind energy initiatives like the Alpha Ventus offshore wind farm study. Teaching: Courses on Wind Turbine Design and Wind Energy Utilization Research Labs: Stuttgart Chair of Wind Energy, Institute of Aircraft Design Recent Projects: Scaled Flight Demonstrator e-Genius-Mod, Passively Self-Adjusting Floating Wind Farms, Lidar-Based Virtual Sensors His research emphasizes sustainable energy transitions, with particular attention to offshore wind infrastructure and turbulence mitigation in complex environments.

• Wind Energy
• Aerospace Engineering
• Aerodynamics
• +6 more

Prof. Dr. Alexander Borst is Director of the Department "Circuits - Information - Models" at the Max Planck Institute for Biological Intelligence in Martinsried, Germany. His research focuses on understanding neural computation in the visual system of Drosophila, particularly how direction-selective motion detection circuits process visual information to guide behavior. Education: Diploma in Biology, University of Würzburg (1981) Doctoral thesis with Martin Heisenberg, University of Würzburg (1984) Habilitation and private lecturer, University of Tübingen (1989) Prof. Borst's research employs a multidisciplinary approach to investigate neural information processing at the level of individual neurons and small circuits. His department uses the fruit fly Drosophila as a model system due to its computationally tractable visual system, with circuits containing fewer than 100 neurons that can be genetically manipulated and observed. The research integrates anatomical reconstructions, physiological characterization, behavioral analysis, and computational modeling to build a comprehensive understanding of visual processing. Analysis of Prof. Borst's recent publications reveals a consistent focus on motion vision mechanisms in Drosophila, with particular emphasis on directional selectivity, neural circuit organization, and the molecular basis of visual processing. His work demonstrates how specific subpopulations of T4 and T5 cells are directionally tuned to cardinal directions and how ON and OFF pathways segregate motion processing. The publications highlight the integration of experimental techniques like 2-photon calcium imaging with computational modeling to understand circuit function. Scientific Awards: Valentino Braitenberg Award in Computational Neurobiology (2014) FENS Award (2014) Member of the HHMI Scientific Advisory Board (2018) Member of the Bavarian Academy of Sciences (2012) EMBO Member (2011) Member of the German Academy of Sciences Leopoldina (2011) Human Frontier Science Program (HFSP) Prize (2006) Prof. Borst has led his department since 2001, first at the Max Planck Institute of Neurobiology and now at the Max Planck Institute for Biological Intelligence. His research has been supported by numerous grants from German and international funding agencies. He has mentored many students and postdoctoral researchers who have established successful careers in neuroscience. His department includes multiple research groups focusing on different aspects of neural computation in the Drosophila visual system. His laboratory comprises several specialized teams working on neurogenetics, molecular characterization, electrophysiology, 2-photon functional imaging, tethered and free behavior analysis, and computational modeling. These teams collaborate closely to investigate how visual information is processed from photoreceptors to behavioral output, with particular focus on motion detection circuits and their developmental and molecular underpinnings.

• Neuroscience
• Computational Neuroscience
• Neural Circuits
• +5 more

Prof. Dr.-Ing. Sergio Montenegro is a Professor of Aerospace Information Technology at Julius-Maximilians-University Würzburg, where he leads the Chair of Computer Science VIII. His academic journey includes a Bachelor's in Computer Science from Universidad del Valle de Guatemala (1978-1982), a Diploma from Technische Universität Berlin (1983-1985), and a Dr.-Ing. from TU Berlin (1989). Prior to joining academia, he held positions as a software developer (1979-1982), research coordinator at Fraunhofer Gesellschaft (1985-2007), and Head of Department at DLR (2007-2010). His research focuses on dependable distributed systems for aerospace applications, including satellite networks, real-time operating systems (RODOS), UAV swarm control, fault-tolerant architectures, and space mission software. Key projects span satellite formation flight (TET, AsteroidFinder), solar sail missions, distributed avionics (VIDANA), and medical IoT systems. Recent publications (2018) demonstrate strong emphasis on distributed spacecraft systems, UAV navigation, fault tolerance, and software engineering for space applications. Trends include miniaturized satellite technologies, decentralized control algorithms, real-time OS verification, and Java-based space systems. He leads research in distributed computing networks and UAV laboratories, supervising projects like VaMEx-LaOLA (Mars exploration) and ultra-wideband positioning systems. Though no awards are documented, he has coordinated over 100 projects including ESA and DLR missions.

• Aerospace Information Technology
• Dependable Computing
• Distributed Systems
• +6 more

Overview Prof. Gudrun Klinker is a Professor at Technische Universität München (TUM), leading the Chair of Computer Science Applications in Medicine & Augmented Reality. She holds a PhD from Carnegie-Mellon University and has extensive experience in academia and industry, including roles at Digital Equipment Corporation and Fraunhofer Institute. Affiliations Professor (C3/W2) since 2000 Head of the FAR (Augmented Reality) research group Member of the CAMP (Computer Aided Medical Procedures) interdisciplinary team Research Dr. Klinker specializes in augmented reality (AR) with focuses on industrial applications, sensor fusion, 3D interaction, and healthcare integration. Her work bridges computer science with medical and industrial challenges, emphasizing user-centric design and real-world deployment. Key projects include: AR-based maintenance systems for complex machinery Healthcare applications like serious games for nutrition education VR/AR training environments for medical and aerospace domains Awards and Recognition Robert Sauer Prize (2010) for contributions to Bavarian science ISMAR Lasting Impact Award (2014) for influential AR research Teaching and Mentorship Prof. Klinker teaches courses on 3D user interfaces, AR fundamentals, and game design. She advises students in thesis projects, focusing on AR applications, HCI, and medical computing. Labs and Collaborations Her research is supported by partnerships with industry and institutions, leveraging TUM's interdisciplinary environment to advance AR/VR systems for real-world impact.

• Industrial Augmented Reality
• Sensing
• Ubiquitous Tracking (Sensor Fusion)
• +4 more

Dr.-Ing. André Bauknecht is a Senior Scientist at the Institute of Fluid Mechanics, Technische Universität Braunschweig . He leads independent research groups within the Cluster of Excellence for Sustainable and Energy-Efficient Aviation, and collaborates with both academic and industrial partners. Research focus: unsteady aerodynamics, flow control, rotary aerodynamics, aircraft aerodynamics Key collaborations: flow control for gust/aircraft load reduction, multicopter flow field analysis Academic Background: Degree in aerospace engineering, University of Stuttgart Doctorate (2016) for helicopter rotor aerodynamics research at DLR Göttingen Postdoctoral work at Alfred Gessow Rotorcraft Center (University of Maryland) Research Trends: His recent publications (2022-2024) emphasize flow control technologies for load alleviation in fixed-wing and multicopter aircraft. Key areas include Coanda-type actuation , circulation control airfoils , and multicopter aerodynamic characterization through combined experimental and numerical methods. Technical Expertise: Specializes in blade vortex measurements (2015-2017), multi-camera BOS systems , and large-scale aerodynamic simulations . Current work integrates multifunctional leading edge devices and flow-structure deformation analysis for next-generation aircraft.

• Unsteady aerodynamics
• Flow control
• Rotary aerodynamics
• +3 more