Prof. Dr. Sarah Genon is a Professor and Group Leader at the Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour) of Forschungszentrum Jülich . Her research focuses on understanding brain-behavior relationships through neuroimaging, machine learning, and large-scale data analysis. She leads interdisciplinary projects investigating hippocampal organization, predictive modeling of mental health outcomes, and replicability in neuroscience. Key areas include: Brain structural health prediction using exposome data Hippocampal morphological networks linked to self-regulation Generalizable machine learning approaches for depression and Alzheimer's biomarkers Cross-cultural generalization failures in behavioral prediction models She emphasizes open science practices, leading initiatives like the Individual Brain Charting dataset and promoting diversity in neuroscience research. Her work bridges basic research with clinical applications, particularly in psychiatry and neurodegenerative diseases. Recent efforts include: Developing connectivity-based brain atlases Studying sleep-cardiometabolic brain interactions Addressing gender biases in neuroscience methodologies Her team collaborates internationally to advance reproducible brain-behavior mapping and improve translational neuroscience outcomes.
UnivProf. Dr. Jens Grabowski is a full professor at the Institute of Computer Science at Georg-August-Universität Göttingen, leading the Software Engineering for Distributed Systems group. His primary roles include teaching advanced courses on software engineering, software testing, and parallel computing, as well as supervising practical internships in these domains. His research focuses on software engineering methodologies, cloud computing architectures, static analysis tools, and model-driven approaches to system design. Education details are not explicitly listed, but his academic position implies a PhD in Computer Science. His work spans both theoretical contributions (e.g., defect prediction models, developer behavior studies) and applied systems (e.g., cloud resource management frameworks, testing tool development). He is actively involved in open-source software research, particularly analyzing Apache projects and Python ecosystems. Key research themes include: Model-driven cloud orchestration using standards like TOSCA and OCCI Static analysis tool evaluation and warning management Empirical studies on software evolution and developer practices Simulation-based approaches for system validation His recent publications (2021-2025) demonstrate sustained contributions to cloud computing infrastructure, static analysis tool efficacy, and software testing methodologies. Notable frameworks developed include MoDMaCAO for cloud application management and the SmartShark ecosystem for mining software repositories. Grants and advising activities are not explicitly detailed in the provided texts, but his leadership in multiple research groups implies significant involvement in academic funding and PhD supervision. He maintains collaborations in distributed systems, cloud computing, and software engineering education.
Prof. Arno Zürbes holds the position of Professor of Design Theory, Machine Elements, and Technical Mechanics at the University of Applied Sciences Bingen and Technical University Bingen since 2009. Previously, he served as a Professor of Mechanical Engineering at the Institut Supérieur de Technologie, Luxembourg (2002–2009). His professional background includes roles as Head of Testing/Calculation Department (BOMAG, 1997–2002) and Project Manager in Soil Mechanics (BOMAG, 1992–1996). He earned a Diplom-Ingenieur from the University of Kaiserslautern (1987) and a doctorate in Machine Dynamics (1992). Research interests focus on vibration analysis, mechanical systems design, materials fatigue, noise reduction, and structural mechanics. His work bridges academia and industry, addressing challenges in automotive, aerospace, and civil engineering sectors. Publications span topics like crankshaft vibration modeling, lightweight panel fatigue, and acoustics in construction machinery. Collaborations with institutions like the University of Luxembourg and industry partners (e.g., BOMAG) highlight applied research approaches.
Prof. Johannes Reuter is a Professor in the Department of Control Engineering at Konstanz University of Applied Sciences and a member of the Institute for System Dynamics (ISD). He serves as Vice Dean and Dean of Studies for the Electrical Systems M.Eng. program. His expertise includes control engineering, tracking, and multi-sensor data fusion. Reuter holds a doctorate in Automatic Control and System Dynamics from Berlin Technical University. Before joining Konstanz in 2007, he worked at IAV GmbH, IAV Automotive Engineering (USA), and Eaton Corp.'s Innovation Center (USA). His research focuses on autonomous systems, maritime control, and optimization algorithms, with contributions to conferences like ICRA and journals such as the Journal of Ocean Engineering. He leads projects on energy-efficient autonomous vessels (Solgenia) and advanced control strategies for dynamic systems. Education: Studied Mathematics/Physics at Bielefeld University Electrical Engineering degrees from Bielefeld University of Applied Sciences and Berlin Technical University Doctorate in Automatic Control and System Dynamics, Berlin Technical University Research Interests: Reuter’s work bridges theoretical control engineering with practical applications, emphasizing autonomous systems, maritime robotics, and sensor data fusion. Key areas include model predictive control (MPC), trajectory optimization, and energy-efficient vessel design. His research often integrates advanced algorithms like MPPI (Model Predictive Path Integral) for stochastic systems and develops methods for extended object tracking using LiDAR and radar sensors. Publications: Recent work highlights energy-optimal vessel docking, trajectory planning with signal temporal logic, and extended object tracking. His articles reflect a focus on interdisciplinary solutions combining control theory, robotics, and sensor technology. Awards/Grants: No specific awards listed, but his work is supported through academic and industrial collaborations. Labs/Teams: Active in the Institute for System Dynamics (ISD), Konstanz, which focuses on control systems, signal processing, and dynamic optimization across robotics, marine systems, and energy management.
Benoît Macq is a distinguished professor at the ICTEAM Institute , Université catholique de Louvain, Belgium. With over 350 publications spanning 1990–2025, his work bridges signal processing , medical imaging , machine learning , and data security . Key collaborators: Christophe De Vleeschouwer Simon K. Warfield Jean-François Delaigle Mathieu De Craene Research interests include: Adaptive algorithms for real-time model deployment and domain adaptation 3D reconstruction and medical image segmentation for radiation therapy Security in blockchain-based distributed learning systems Transformers for EEG classification and proton radiography Recent publications focus on foundation models in cytology and remote sensing, holonic multi-agent systems for VR, and secure codestreams for UAV object detection. His work emphasizes scalable architectures and privacy-preserving techniques in dynamic environments. Advising: Dani Manjah Antoine Aspeel Maxime Zanella
Dr.-Ing. Peter Scholz is a Senior Research Fellow at the Institute of Fluid Mechanics , Technische Universität Braunschweig. With a PhD in Mechanical Engineering (2009) and a background in Aerospace Engineering from TU Braunschweig, he specializes in aerodynamics , active flow control , and experimental fluid dynamics , particularly using fluidic vortex generators and numerical simulations . He leads research groups and played a pivotal role in designing the university’s large water tunnel. Core Research Areas: Aerodynamics, Flow Control, Fluid Mechanics, Experimental Methods, Numerical Simulations, Aerospace Applications. His recent publications focus on supersonic flow dynamics , laminar flow control , and wake structure analysis , with methodologies spanning Large-Eddy Simulation , PIV measurements , and high-speed flow diagnostics . Though no formal awards are documented, his work is integral to Germany’s flow control research initiatives. Dr. Scholz collaborates extensively with institutions like DLR and Fraunhofer WKI, advancing sustainable propulsion and flow control technologies.
Felix Kaule is a Laboratory Engineer at the Institute for Development-Oriented Mechanical Engineering , Faculty of Engineering, HTWK Leipzig. He works under the supervision of Prof. Dr.-Ing. Anke Bucher and Prof. Dr.-Ing. Stephan Schönfelder, focusing on mechanical strength analysis of silicon wafers and solar cells. Current research in PV production technologies Project manager for BMWi-funded NextTec project Expertise in finite element modeling and experimental validation His work bridges computational simulation with practical testing in laboratories like bikelab , where mechanical properties of components are evaluated. Recent publications highlight innovations in half-cell module manufacturing, thermal laser separation, and microcrack mitigation in photovoltaic materials. Scientific contributions include: Optimizing diamond wire sawing processes Analyzing residual stress effects in solar cells Advancing kerfless cutting technologies Improving mechanical strength through plasma etching
Florian Loffing is a Senior Lecturer in the Department of Performance Psychology at the Psychological Institute of the German Sport University Cologne. His academic career spans multiple institutions, including the University of Kassel, Carl von Ossietzky University of Oldenburg, and Westfälische Wilhelms-Universität Münster. He specializes in sensorimotor expertise, laterality (particularly handedness), and perception-action dynamics in sports. Senior Lecturer, German Sport University Cologne (2023–present) Lecturer for Special Tasks, German Sport University Cologne (2021–2022) Research Associate, University of Oldenburg (2017–2021) Research Associate, University of Kassel (2009–2016) Research Associate, WWU Münster (2007–2009, 2010–2011) His research interests focus on cognitive and perceptual aspects of sports performance, particularly in anticipation, expertise, and laterality. He is deeply involved in quantitative research methods and teaches courses in sports psychology, motor learning, and statistical software such as SPSS, JASP, and PsychoPy. His work emphasizes scientific thinking and evidence-based practice in sport. The analysis of his recent publications reveals a strong focus on cognitive skills in sport, particularly in goalkeeping and table tennis. Themes include anticipation, decision-making, gaze behavior, and expertise development. His methodological contributions highlight data visualization and robust statistical practices. Many studies employ experimental designs and scoping reviews to explore perceptual-cognitive mechanisms in elite and developing athletes. Florian Loffing has contributed to several scientific journals as a peer reviewer, including Laterality: Asymmetries of Body, Brain and Cognition , Psychophysiology , and PLOS ONE . While no formal awards are listed, his sustained scholarly activity and editorial engagement reflect recognition in the academic community. He advises on research methodology and statistical analysis, supporting students and colleagues in designing and evaluating empirical studies. His teaching integrates software-supported tools to enhance scientific rigor. Though no formal grants are listed, his participation in DFG-funded projects (e.g., 'Laterality in Sport') indicates prior research funding. Loffing is affiliated with the research group Sensorimotor Expertise and the Department of Performance Psychology , where he collaborates on projects related to elite athlete cognition, anxiety, and heart rate variability. His network includes researchers such as Babett Lobinger, Philip Furley, and Jens Kleinert, with whom he has co-authored multiple publications.
Adilson Marques da Cunha is a Professor at the Brazilian Aeronautical Institute of Technology (ITA), with a focus on software engineering and computational systems. His career spans academic research and development in embedded systems, real-time applications, and machine learning methodologies. Affiliation: Brazilian Aeronautical Institute of Technology Research Interests: Dr. da Cunha's work centers on agile software development , embedded system optimization , and numerical integrator frameworks . He has contributed to deep reinforcement learning for robotics and recommender systems for news, while also exploring climate prediction models using big data. Publication Trends : 2025 papers focus on universal numerical integrators and Python testing frameworks; 2024 work involves autonomous air navigation; 2022 studies include humanoid robotics and climate modeling
Chao Yin is a researcher at Shanghai University , Department of Computer Engineering and Science. His work spans multiple domains including Machine Learning, Cloud Computing, Fault Diagnosis, and Supply Chain Optimization. Key research areas: Machine Learning , Cloud Computing , Quantum Computing , Supply Chain Systems , Network Security Scientific Contributions (2024-2025): Developed heterogeneous graph neural networks for automotive supply chain analysis Created MSDF-VAE cloud-edge fault diagnosis framework using transfer learning Proposed quantum metrology methods with Heisenberg-limited precision Designed LARP pseudonym protocol for V2X communication Optimized fog computing resource scheduling with hybrid metaheuristics Prior Work (2012-2023): Contributed to fluid animation feature preservation from single images Developed label distribution learning for facial age estimation Designed erasure coding storage systems for big data Created multi-agent manufacturing networks in cloud environments
Henry Hoffmann is Professor and Liew Family Chair of the Department of Computer Science at the University of Chicago. He serves as Chair of the department and leads research in self-aware and adaptive computing systems. His work bridges traditional computer systems areas with control theory and machine learning to create systems that automatically adapt to meet high-level goals. Hoffmann received his Ph.D. from MIT in 2013 under advisors Anant Agarwal and Srinivas Devadas, with his dissertation titled "SEEC: a framework for self-aware management of goals and constraints in computing systems." He earned an S.M. from MIT in 2003 and a B.S. with highest honors and distinction from UNC-Chapel Hill in 1999. Hoffmann's research focuses on developing self-aware computing systems that understand high-level goals and automatically adapt their behavior to meet those goals optimally. His recent work has shifted toward applying these techniques to control machine learning and AI systems, building learning systems that dynamically adapt their internal structure and resource usage to meet accuracy, energy, performance, and security goals at inference time. His interdisciplinary approach combines operating systems, computer architecture, control theory, and machine learning. Analysis of Hoffmann's recent publications reveals a clear trajectory toward increasingly sophisticated applications of self-aware computing principles. His work has evolved from foundational resource management to cutting-edge applications in AI/ML systems, quantum computing, and security. The publications demonstrate a consistent theme of using control theory and machine learning to create adaptive systems that optimize multiple competing objectives like performance, energy efficiency, and reliability. Recent papers show expanding applications into large language models, quantum algorithms, and privacy-preserving techniques. Presidential Early Career Award for Scientists and Engineers (PECASE) 2019 DOE Early Career Award 2015 Samsung Security Hall of Fame recognition IEEE Micro Top Picks Honorable Mention awards FSE Test of Time Honorable Mention ASPLOS Hall of Fame recognition Hoffmann has mentored numerous PhD and Master's students who have gone on to successful careers in academia and industry. His research has secured over $19 million in funding for the University of Chicago. He co-founded Config Dynamics in 2019 to commercialize aspects of his self-aware computing research. His work has practical applications across data centers, edge computing, AI systems, and quantum computing. Hoffmann leads the SEEC (Self-aware, Energy-Efficient Computing) research group at the University of Chicago. The group focuses on developing frameworks and techniques for building self-aware computing systems that can dynamically adapt to changing conditions and requirements. The group maintains strong collaborations with industry partners and other academic institutions, particularly in the areas of quantum computing, AI systems, and energy-efficient computing.
Prof. Dr. Andreas Glöckner is a Senior Research Fellow (part-time) at the University of Cologne, where he leads the Glöckner Group in Social Psychology at the Social Cognition Center Cologne (SoCCCo). His research spans judgment and decision making, cooperation, open science, intuition, stereotypes and discrimination, cross-cultural studies, eye-tracking, computational modeling, neural networks, behavioral economics, and empirical legal studies. Glöckner's research interests focus on understanding how people make decisions under various conditions, particularly examining the interplay between intuitive and deliberate processes. His work employs multiple methodologies including experimental approaches, computational modeling, eye-tracking, and cross-cultural comparisons. He has made significant contributions to understanding how people process information, how they cooperate across societal boundaries, and how cognitive biases influence legal decision-making. His recent publications reveal strong trends in cross-cultural decision making, computational modeling of cognitive processes, and the application of open science principles to psychological research. Glöckner has published extensively in top journals including Proceedings of the National Academy of Sciences, Cognition, and Journal of Behavioral Decision Making, with recent work focusing on multinational cooperation studies, computational models of decision strategies, and the psychological impacts of the pandemic on research practices. Scientific Awards and Distinctions: Award for Quality Assurance in Psychology of the German Psychological Society (DGPs) for the Network of Open Science Initiatives (NOSI), 2020 Editor-in-chief of Judgment and Decision Making, since 2018 President of the European Association for Decision Making (EADM), 2017-2019 Vice chairman of the academic advisory council of the Leibniz Institute for Psychology Information (ZPID), since 2018 Glöckner has secured research grants from major funding organizations including the German Research Foundation (DFG), German-Israeli Foundation (GIF), Max Planck Society (MPG), and European Association for Decision Making (EADM). His editorial leadership includes serving as Associate/Action Editor for Judgment and Decision Making (2012-2018) and Journal of Behavioral and Experimental Economics (2013-2018), as well as guest editing special issues on methodology and strategy selection. He leads the Glöckner Group at the Social Cognition Center Cologne, which includes researchers Angela Dorrough, Marc Jekel, and others, focusing on decision-making processes using multiple methodologies including eye-tracking and computational modeling. The group has produced influential work on parallel constraint satisfaction models, cross-cultural cooperation studies, and the psychology of legal decision-making.
Ştefania-Gabriela Dumbravă is an Associate Professor at Institut Polytechnique de Paris (ENSIIE/Samovar Laboratory). Her research focuses on formal methods for graph database algorithms , including schema design, query processing, and verification. She contributes to international standards through co-chairing VLDB 2026 Demonstration Track and organizing workshops like VLDB Summer School 2025 . Dumbravă serves on editorial boards (e.g., ACM Transactions on Database Systems ) and program committees for top-tier conferences ( SIGMOD , ICDE ). Research Interests include formal verification of graph databases , property graph schema constraints , certified inference engines , and distributed graph systems . She integrates proof assistants (Coq, Isabelle) with practical database development, emphasizing reliability and mechanical correctness . Her work spans theoretical foundations (e.g., category theory , type theory ) and real-world applications (e.g., transit accessibility analysis , SDN controllers ). Selected Scientific Awards : EASST Best Software Science Paper Award (ICGT 2025) SIGMOD Best Paper Award (2023) VLDB Best Regular Paper Runner-Up (2022) D4Gen Hackathon 3rd Prize Teaching includes Graph Databases , Functional Programming , and Formal Languages at ENSIIE, with additional roles at Université Paris-Saclay, ENS Lyon, and Université Rennes 1. She supervises research internships and participates in gender parity initiatives (e.g., Paris-Saclay Women & Science Mentorship Program).
Prof. Dr.-Ing. Florian Stamer is a Professor of Production Management at the Institute for Production Engineering and Systems (IPTS) at Leuphana University of Lüneburg. His work integrates AI methods with production and quality management to enhance profitability while reducing resource consumption for circular value chains . He has held academic roles at Karlsruhe Institute of Technology (KIT) and now leads research at Leuphana. Education B.Sc. Industrial Engineering (Mechanical Engineering) – RWTH Aachen University (2014) M.Sc. Industrial Engineering (Mechanical Engineering) – RWTH Aachen University (2017) Dr.-Ing. (Doctorate in Engineering Sciences) – KIT (2022, Summa cum Laude) Research Focus : Production Networks : AI-driven price/delivery time optimization, scenario simulation of global value structures Production Systems : Digital twins for layout planning, lean-digitalization integration, cognitive systems for adaptive disturbance response Quality Management : Component quality in circular production, data-driven test planning Scientific Contributions : Developed data models for process robustness in deep-drawing tools (2024-2025) Advanced AI applications in 5G-enabled manufacturing (EVOLVE5G, USIN5G) Optimized magnesium nanocomposites and fiber-metal laminates (2018-2022) Awards Summa cum Laude Doctorate – KIT (2022) Research Affiliate – CIRP (2023-present) Industry Collaboration : Works closely with industrial partners through third-party funding and consulting projects, translating academic insights into practical applications.
Irene Brückle is a Professor for Conservation and Restoration of Works of Art on Paper at the State Academy of Fine Arts Stuttgart. With a career spanning over 25 years, she has held key roles including Head of the Conservation and Restoration Program (since 2008) and former leadership positions at Berlin State Museums. Her expertise bridges theoretical and practical conservation, emphasizing scientific rigor and historical material analysis. Doctorate from State Academy of Fine Arts Stuttgart (2007) Editorial roles: Associate Editor of Studies in Conservation (since 2019), co-editor of Restaurator (2007–2013) Research interests focus on: Paper degradation mechanics under environmental stressors Historical and modern bleaching techniques Chemical interactions in conservation treatments Preservation of graphic works, archives, and library materials Recent publications highlight advancements in LED bleaching, hydrogen peroxide alternatives, and structural support systems for fragile materials, reflecting her commitment to innovative yet scientifically validated methods across Journal of Paper Conservation , Restaurator , and Topics in Photographic Preservation . Scientific awards include: Sheldon and Caroline Keck Award for Conservation Education (2005) Getty Senior Fellowship (1990–1991) Samuel H. Kress Foundation Fellowship (2001) She supervises doctoral students like GJ Dietz (16th-century charcoal drawings) and L. Stiber (16th–17th-century Italian woodcuts), and leads DFG-funded projects on optical radiation damage prediction and Piranesi print identification.
