Dr. Almut Sophia Koepke is a junior research group leader and TUM Junior Fellow at the Technical University of Munich (TUM) and University of Tübingen. She leads the multi-modal learning research group focusing on video understanding through sound, vision, and text integration. University: Technical University of Munich School: TUM School of Computation, Information and Technology Department: Informatics 9 Academic Rank: Researcher Her research spans multi-modal learning, audio-visual foundation models, and cross-modal attention mechanisms. Key themes include: Advancing zero-shot learning through language-guided audio-visual models Developing explainable AI systems via attention pattern translation in VQA Exploring temporal understanding in video-adverb retrieval Building robust multi-modal representations for self-driving applications Recent publications analyze foundation model capabilities in audio-visual tasks (ICCV 2025), temporal reasoning (ACMMM 2024), and cross-modal attention frameworks (ECCV 2022). She co-organizes CVPR workshops on foundation model evaluations and serves as area chair/reviewer for major conferences.
Xinyu Jia is currently a Humboldt Research Fellow at the Engineering Risk Analysis Group, Technical University of Munich since June 2024, and concurrently serves as Associate Professor in the Department of Mechanical Engineering at Hebei University of Technology, China since October 2022. Her research focuses on advancing uncertainty quantification, structural reliability, and risk assessment methodologies for engineering systems. Her academic background includes: PhD in Mechanical Engineering, University of Thessaly, Greece (2018-2021) Bachelor of Engineering and Master of Science in Mechanical Engineering, Hunan University, China (2011-2018) Dr. Jia specializes in Bayesian learning frameworks for physics-based models, with particular expertise in uncertainty propagation in structural dynamics and industrial robotics applications. Her work develops hierarchical Bayesian approaches that integrate multi-level data to enhance predictive accuracy for complex engineering systems, addressing critical challenges in structural health monitoring and risk-informed decision making. Analysis of her 2022-2023 publications reveals a concentrated research trajectory in applying Bayesian inference to structural dynamics, with emphasis on hierarchical modeling techniques, variational inference schemes, and nonlinear model updating. These contributions predominantly appear in top-tier mechanical engineering journals, demonstrating methodological innovations that bridge theoretical statistics with practical engineering reliability problems. Her scientific recognition includes: Humboldt Research Fellowship (2023) Marie Curie Early Stage Researcher Fellowship (2018) No specific student advisement records are documented, though her Associate Professor role implies teaching responsibilities. Her fellowship awards represent significant research funding supporting her work in uncertainty quantification. As an active member of TUM's Engineering Risk Analysis Group, she contributes to high-impact projects including digital twins for ships, S3UQDyn, Navigating Risk, and infrastructure resilience initiatives like BIG-ROHU and INFRA.RELEARN, focusing on probabilistic risk modeling across civil and mechanical engineering domains.
Prof. Dr. rer. nat. Rainer Leupers is a faculty member at RWTH Aachen University, chairing the Department of Software for Systems on Silicon. His research focuses on embedded systems, hardware-software co-design, virtual prototyping, and security in computing-in-memory architectures. He has published extensively on RRAM accelerators, logic locking, and neuromorphic security. Chair of Software for Systems on Silicon Research in hardware security and deep learning accelerators Recent publications on cross-tool virtual frameworks and thermal side-channel attacks His work bridges system-level modeling with practical security implementations, emphasizing reliability and performance in heterogeneous computing environments. Key trends in his 2025-2023 articles include compute-in-memory optimization, neural network inference efficiency, and security vulnerabilities in emerging hardware. Awards and formal recognitions are not explicitly detailed in the provided materials. He has not directly mentioned advising students or research grants in the given text fragments. The chair's contact information includes an office at ICT Cube 1, Electrical Engineering, Aachen, with direct email and website links.
Michael Sammler is an Assistant Professor leading the Programming Languages and Verification Group at the Institute of Science and Technology Austria (ISTA). He holds a PhD from the Max Planck Institute for Software Systems (MPI-SWS) and was a postdoctoral researcher at ETH Zürich. His research focuses on formal verification of low-level systems code, combining foundational proofs with automation. Key projects include RefinedC (C verification), Islaris (assembly code verification), and DimSum (multi-language interoperability). Education: PhD at MPI-SWS/Saarland Informatics Campus, postdoc at ETH Zürich. Research interests emphasize tool development for safety-critical systems, including Rust verification (RefinedRust), OCaml/C interoperability (Melocoton), and decentralized multi-language semantics (DimSum). Awards: Runner-Up for Informatics Europe 2024 Best Dissertation Award, Dr. Eduard Martin Prize, Distinguished Paper Awards at PLDI/POPL/USENIX, and Google PhD Fellowship. Labs/Teams: Programming Languages and Verification Group at ISTA, collaborations with MPI-SWS and international researchers. His work bridges foundational theory with practical tools for industry-relevant verification challenges.
Liji Shen is Professor of Operations Management and Chairholder at WHU – Otto Beisheim School of Management, Campus Vallendar, Germany. She is affiliated with the Supply Chain Management Group and leads research in scheduling, optimization, and sustainable manufacturing. Her academic journey includes a Ph.D. and Habilitation from Technische Universität Dresden, and she has held visiting scholar positions at institutions including École des Mines de Saint-Étienne and Huazhong University of Science and Technology. Ph.D. (Dr.rer.pol.), summa cum laude, Technische Universität Dresden (2009) Habilitation, Technische Universität Dresden (2015) Master of Business Administration (Dipl.-Kffr.), Technische Universität Dresden (2006) Liji Shen's research focuses on Operations Management , particularly scheduling optimization in manufacturing systems. Her work spans flexible job shops , parallel machine scheduling , energy-efficient production , and sequence-dependent setup times . She applies advanced techniques such as evolutionary algorithms , hybrid metaheuristics , and mathematical programming to solve complex industrial problems. Her recent publications emphasize sustainability through energy-aware scheduling and time-of-use pricing models. The 15 most recent publications highlight a consistent research trajectory in production scheduling , with increasing emphasis on energy efficiency , distributed manufacturing , and real-world constraints like eligibility and delivery times. Her work frequently appears in top journals such as European Journal of Operational Research , IEEE Transactions on Evolutionary Computation , and Computers & Operations Research , often in collaboration with leading researchers like Dauzère-Pérès, Mönch, and Buscher. Scientific Awards: European Journal of Operational Research, Best Paper Award (2021) DFG and TU Dresden, 'Support the Best' Prize for Outstanding Researchers (2013) Dr. Feldbausch-Prize for Best Dissertation, TU Dresden (2010) Scholarship for Young Researchers in Saxony (2006–2009) DAAD Prize for Best Foreign Students (2007) Best Master’s Thesis, German Operations Research Society (2007) Liji Shen has been an active advisor and researcher, leading projects in operations research and industrial optimization. Her editorial role on Operations Research Perspectives underscores her standing in the academic community. She has directed research labs and collaborated internationally, contributing to both theoretical advancements and practical applications in manufacturing and logistics. No specific grants are mentioned, but her sustained publication record and leadership roles indicate strong research support. She leads the Operations Management research group at WHU, focusing on algorithmic solutions for complex scheduling problems. Her team investigates energy-aware production, hybrid flow shops, and distributed systems, aiming to bridge the gap between theoretical models and industrial implementation. The lab collaborates with researchers across Europe and China, fostering a global research network in operations research and supply chain management.
Prof. Jörn Meissner, PhD, is a Full Professor of Supply Chain Management & Pricing Strategy at Kühne Logistics University (KLU) since 2011. He holds a PhD and Master’s in Management Science from Columbia Business School and a Diploma in Business from University of Hamburg . As an academic and entrepreneur, he founded Manhattan Review and Lancaster Executive . Education: PhD in Management Science, Columbia University (2005) Master of Philosophy, Columbia University (2005) Diplom-Kaufmann, University of Hamburg (1997) Research Expertise: Focus on stochastic and dynamic decision-making using mathematical optimization and machine learning Key projects: Global supply chain optimization , Inventory control , Revenue management , and Operations & service management Industry collaborations with British Telecom , British Airways , Apple Europe , and SAP Germany Publication Trends: Recent work addresses intermittent demand forecasting for spare parts, lateral transshipment optimization , and risk-sensitive capacity control Historical contributions include progressive interval heuristics for multi-item lot sizing and dynamic pricing with customer choice models Teaching Experience: Previously held academic positions at Lancaster University Management School , University of Hamburg , and University of Mannheim Developed MBA electives in Advanced Decision Models , Supply Chain Management, and Revenue Management
Dr. Torge Martin serves as a Senior Scientist in Ocean Dynamics at the GEOMAR Helmholtz Centre for Ocean Research Kiel, where he is actively engaged in research on ocean circulation and climate dynamics. His work focuses on polar climate systems with particular emphasis on the interactions between ice sheets, oceans, and atmosphere in both the Arctic and Antarctic regions. As a member of the GEOMAR scientific council and student advisor in physical oceanography, he contributes significantly to institutional governance and academic training. Dr. Martin's research interests center on physical processes driving marine climate variability in high-latitude regions. He investigates how melting ice sheets impact ocean circulation patterns, with special attention to the role of mesoscale eddies (10-100km) in redistributing heat and freshwater. His work explores the connections between surface changes and deep ocean variability, particularly examining how rapid ice melt translates into changes in the Atlantic Meridional Overturning Circulation. He is deeply involved in high-resolution ocean and coupled climate modeling, developing and applying the Flexible Ocean and Climate Infrastructure (FOCI) with regional refinement capabilities to study ice-ocean-atmosphere interactions at multiple scales. The analysis of Dr. Martin's recent publications reveals a consistent focus on polar ocean dynamics and climate change impacts. His work spans from Arctic sea ice dynamics to Southern Ocean circulation, with particular emphasis on how freshwater input from melting ice sheets affects ocean circulation patterns. The research employs advanced modeling techniques, often incorporating mesoscale resolution to capture critical ocean processes. A significant portion of his recent work contributes to the Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative, examining multi-model responses to Antarctic meltwater. Member of CLIVAR Ocean Model Development Panel (OMDP) Co-lead of the Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative Antarctica InSync national committee member and lead of modeling working group Member of GRISO working group Ice Forcing Ocean around Greenland POF-IV subtopic 2.3 sea level change center representative Member of GEOMAR scientific council Dr. Martin actively mentors students in physical oceanography and has developed innovative teaching approaches using rotating tank experiments to demonstrate ocean dynamics principles. His research is supported through multiple projects including SCENIC (Storyline Scenarios of Extreme Weather), G-shocx (Greenland Ice Sheet–melting exiting ocean extremes), PalMod Phase 2, and the Flexible Ocean and Climate Infrastructure (FOCI) development. He chairs sessions at major international conferences including EGU General Assembly and Ocean Sciences Meeting, and has served as co-chair of the Southern Ocean Region Panel (SORP) of CLIVAR, CliC and SCAR from 2020 to 2023. His laboratory work centers on high-resolution ocean modeling with the FOCI climate model, featuring regional refinement capabilities for the subpolar North Atlantic (VIKING10) and Southern Ocean (ORION10X), allowing explicit simulation of mesoscale dynamics critical to understanding polar climate processes.
Mathias Munschauer leads the Department of Molecular Virology at Heidelberg University's Faculty of Medicine, within the Center for Infectious Diseases. His research group focuses on unraveling RNA regulatory mechanisms that govern viral infection outcomes, with emphasis on HCV, HBV, and Dengue virus. His research interests lie at the intersection of RNA biology and virology, particularly in understanding how viral RNA molecules interact with host cell components. The lab employs cutting-edge methodologies including RAP-MS and SHIFTR for RNA interactomics, integrated with functional genomics, single-cell transcriptomics, and AI-driven analysis of high-dimensional data. This systems-level approach enables the identification of host factors and regulatory pathways critical for viral replication and immune evasion. The recent publications highlight a strong trend toward spatially and temporally resolved analysis of RNA-protein interactions across diverse RNA viruses. There is a consistent focus on developing and applying innovative technologies to map host-virus interfaces, with applications in identifying antiviral targets and understanding infection mechanisms. The work spans molecular, cellular, and systems biology, with increasing integration of computational and machine learning approaches. Systems virology RNA-protein interactomics Host-pathogen interactions CRISPR screening Single-cell analysis Antiviral strategies Dr. Munschauer mentors a research team and contributes to the doctoral program in Infectious Diseases. His lab develops and shares novel reagents and methods, fostering collaborative science. While specific grants are not listed, the technological sophistication suggests substantial funding support. The lab operates within a vibrant research environment alongside other virology groups such as AG Bartenschlager and AG Ruggieri. The Munschauer Lab is part of a larger virology and infectious disease research ecosystem at Heidelberg University, collaborating across disciplines to advance understanding of viral pathogenesis. The team actively develops and applies innovative tools for RNA-centric discovery, positioning the group at the forefront of molecular virology.
Prof. Dr. Matteo Große-Kampmann is a faculty member at Hochschule Rhein-Waal, serving as Professor of Distributed Systems within the Faculty of Communication and Environment. His research and teaching are centered on building secure, resilient, and reliable digital systems, with a strong emphasis on integrating information security from the earliest stages of system design. He is based at the Kamp-Lintfort Campus and actively leads research in the Cloud Resilience Lab. His research interests span a wide range of cybersecurity domains, including information security awareness, healthcare IT security, mobile and 5G/6G network security, threat modeling, and privacy in smart devices. He advocates for a proactive, design-first approach to security, particularly in increasingly interconnected environments. His work combines technical depth with human factors, examining both system-level vulnerabilities and user behavior in cyber risk contexts. The recent publications reflect a strong focus on applied cybersecurity research, with trends in mobile network penetration testing, privacy in wearables, governmental cybersecurity communication, and security in healthcare and childcare technologies. His work frequently appears in top-tier venues such as DSN, PETS, ESORICS, and ACSAC, often in collaboration with students and international researchers. His scientific contributions have been recognized with awards including an Honorable Mention Award at the International Conference on Mobile and Ubiquitous Multimedia (2024) and a Best Paper Candidate at the ACM Web Conference 2022. He also contributes to the academic community as a reviewer and technical program committee member for major security conferences including NDSS, PETS, ESORICS, and ACSAC. Prof. Große-Kampmann actively supervises bachelor's and master's theses, encouraging students to explore topics such as post-Darknet marketplaces, AI in cybersecurity education, and flood of information challenges. He emphasizes ownership, preparedness, and learning through failure, fostering independent research skills. He collaborates with students and industry partners on practical projects, particularly in the areas of penetration testing and security analysis. He is involved in several research initiatives, most notably the Cloud Resilience Lab , where he and his team investigate real-world security and privacy issues in modern digital systems. His work bridges academic research with practical applications, often receiving media attention, such as coverage in Wired , EFF , and Die Zeit for his study on childcare app security.
Dr. Sarah Wolf serves as Head of the Junior Research Group 'Mathematics for Sustainability Transitions' at Free University of Berlin's Department of Mathematics and Computer Science and as a Senior Researcher and Board Member at the Global Climate Forum (GCF). Her dual affiliation bridges rigorous mathematical modeling with real-world sustainability policy, focusing on complex socio-ecological systems through an interdisciplinary lens since joining GCF's Green Growth initiative in 2012. Wolf earned her PhD in Mathematics from Freie Universität Berlin in 2010 with the thesis 'From Vulnerability Formalization to Finitely Additive Probability Monads,' developed during interdisciplinary work at the Potsdam Institute for Climate Impact Research. Her academic foundation combines pure mathematics with applied climate impact research, establishing her unique approach to formalizing sustainability concepts. Her research centers on agent-based modeling of socio-technical systems, with core expertise in sustainability transitions , green growth mechanics , and sustainable mobility . She develops mathematical frameworks to clarify vulnerability concepts while embedding simulations in stakeholder dialogues through innovations like the 'Decision Theatre Triangle.' This work uniquely positions mathematics as both analytical tool and communication medium for climate policy. Analysis of her 15 most recent publications reveals an evolutionary trajectory from foundational vulnerability formalization (2009-2012) toward applied stakeholder-integrated modeling (2021-2023). Her work consistently bridges mathematical rigor with policy relevance, showing increasing emphasis on participatory approaches while maintaining computational sophistication in agent-based systems. No scientific awards are documented in the source material, though her leadership in the MATH+ junior research group indicates competitive funding attainment. As group head, she directs research strategy and likely mentors junior researchers, though no formal student advisees are listed. Wolf leads the 'Mathematics for Sustainability Transitions' junior research group within FU Berlin's Biocomputing Group, collaborating with institutions like the Potsdam Institute. Her team develops computational frameworks for green growth transitions, emphasizing stakeholder co-creation through platforms like the Decision Theatre while maintaining strong ties to GCF's global policy networks.
Zhang Yang is an Associate Professor at the School of Medical Engineering, Harbin Institute of Technology (Shenzhen), with a joint appointment as Visiting Professor at the University of Tokyo starting in July 2024. He holds a PhD from the University of Cambridge's Department of Pathology and an M.Phil. from the University of Hong Kong's HKU-Pasteur Research Center. Previously, he served as an Assistant Professor at Harbin Institute of Technology (Shenzhen) from September 2015 to December 2020. His research integrates computational and experimental approaches to address challenges in pathogen and cancer research. On the computational side, his work focuses on developing AI-powered microscopic imaging systems, applying deep learning to analyze multi-omics data (including proteins, DNA, miRNAs, LncRNAs, and mRNAs), and utilizing deep learning in cheminformatics for drug discovery. On the experimental side, his laboratory combines imaging, high-throughput sequencing, mass spectrometry, and chemical biology to understand disease mechanisms at the molecular level. His publication record demonstrates significant impact, with over 50 SCI-indexed papers in high-impact journals including Nature Communications, Briefings in Bioinformatics, Bioinformatics, Analytical Chemistry, and Trends in Biotechnology. His work has been cited by prestigious journals such as Nature Reviews Methods Primers and Nature Communications, with three ESI highly cited papers. His research spans multiple interdisciplinary fields, combining artificial intelligence with biomedical applications to advance diagnostic and therapeutic approaches. World's Top 2% Scientists 2021 Fellow of the Royal Society of Biology Three ESI Highly Cited Papers Five authorized national invention patents As an academic leader, he serves as Associate Editor for BMC Biology and Frontiers in Microbiology, Academic Editor for PLOS Genetics, Editorial Board Member for Communications Biology, and Guest Editor for a Special Issue on AI in analytical chemistry in Trends in Analytical Chemistry. His laboratory actively collaborates with international institutions, with graduates pursuing further studies at Hong Kong Chinese University, Hong Kong University of Science and Technology, Hong Kong Polytechnic University, Macau University, and the University of New South Wales. He teaches Introduction to Modern Biology for undergraduates and Bioanalytical Chemistry for graduate students.
Prof. Johannes Weyer is a faculty member at the Technical University of Dortmund , affiliated with the Faculty of Social Sciences . His research focuses on the intersection of sociology, technology, and mobility, particularly in the context of sustainable urban systems and human-machine interaction. Email: johannes.weyer@tu-dortmund.de Phone: +49 231 755 3281 Key research areas include agent-based modeling , socio-technical systems , sustainable mobility , and the implications of digital society on governance and behavior. His recent publications emphasize simulation frameworks like SimCo, mobility transitions in the Ruhr region, and participatory methods for sustainable policy design. Notable trends in his 15 most recent articles (2023-2025) include: Agent-based modeling of transportation systems Human-AI interaction in real-time society Living lab experiments for sustainable mobility Behavioral analysis of mode choice Multi-level governance of technological discontinuation
Prof. Dr. Andreas Herkersdorf is a Full Professor and Chair of Integrated Systems at the Technical University of Munich (TUM) School of Computation, Information and Technology. His research focuses on application-specific multicore processors (MPSoC), FPGA-based prototyping, fault-tolerant systems, and energy-efficient architectures, with applications in IP packet processing, automotive systems, and visual computing. He has received multiple IBM innovation awards and serves on editorial boards including the DFG Review Board for computer architecture. Education: Dipl.-Ing. Electrical Engineering (TUM, 1987), Dr. techn. Electrical Engineering (ETH Zurich, 1991) Research: MPSoC architectures, autonomic computing, NoC resilience, FPGA acceleration, and self-optimizing systems. Awards: IBM Master Inventor (1998), IBM Outstanding Technical Achievement Award (2001), multiple IBM Innovation Achievement Awards (1996-2003) His recent publications emphasize hardware/software co-design, machine learning integration for runtime optimization, and network-on-chip innovations. He collaborates on projects involving 6G systems, smartNICs, and automotive communication protocols.
Prof. Dr. Haris Gačanin is a faculty member at RWTH Aachen University, affiliated with the Institute for Distributed Signal Processing under the College of Electrical Engineering. His research focuses on integrating machine learning with wireless communication systems, particularly in industrial IoT, edge computing, and network optimization. Current academic rank: Professor Contact: harisg@dsp.rwth-aachen.de Research Interests: Wireless systems, machine learning, signal processing, and network optimization. Key contributions include: Adaptive resource allocation in IIoT and vehicular networks AI-driven channel estimation and feedback mechanisms Security-oriented emitter identification via metric learning Federated/transfer learning for edge environments Hardware-efficient deep learning models for mmWave and THz communications Methodological Focus: Combines reinforcement learning, attention mechanisms, and robust neural architectures with practical implementations on FPGA and vehicular systems.
Claudia Pahl-Wostl is a full professor for resources management at the Institute for Environmental Systems Research (USF) at the University of Osnabrück, Germany. She holds a dual affiliation with both the Institute for Environmental Systems Research and the Institute of Geography, working from room 66/106 at Barbarastr. 12 in Osnabrück. Professor Pahl-Wostl is an internationally leading scholar specializing in governance and adaptive management of water resources, with particular expertise in the role of social and societal learning in environmental systems. Her research builds on systems science foundations that acknowledge the complex and often unpredictable dynamics of the systems being managed. Her work spans multiple critical areas including adaptive governance, transformation processes toward sustainability, global water governance within multi-level systems, and conceptual frameworks for analyzing social-ecological systems. Her recent research has expanded to address the water-energy-food nexus, SDG implementation, and social-ecological network analysis, reflecting an evolving focus on integrated approaches to global sustainability challenges. The publications demonstrate a clear trajectory toward increasingly complex, interconnected systems analysis with emphasis on governance structures capable of addressing multi-scalar environmental challenges. Her scientific achievements have been recognized with the prestigious Bode Foundation Water Management Prize in 2012 for her pioneering interdisciplinary work on 'Governance in times of change' and comparative analyses of water governance in large river basins. Professor Pahl-Wostl teaches courses in Adaptive Management, Participatory Modeling, Environmental Risk Analysis and Governance, Actor-based and Social Network Analysis, Complex Adaptive Systems, Rule-based Modeling, and Adaptive Governance and Political Steering, reflecting the interdisciplinary nature of her research program.
