Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.
Prof. Dr.-Ing. Rüdiger Daub serves as Professor and Chair of Production Engineering and Energy Storage Systems at the Technical University of Munich (TUM), operating within the Department of Mechanical Engineering. His leadership encompasses research direction, academic supervision, and strategic development of battery production technologies at TUM's Garching campus (Boltzmannstr. 15), with active industry collaborations driving innovation in sustainable manufacturing. Daub's research program pioneers advanced production methodologies for lithium-ion and solid-state batteries, focusing on electrode manufacturing, electrolyte filling, and cell assembly processes. His work investigates critical parameter interdependencies affecting battery safety and performance, developing inline monitoring systems and digital twin technologies for real-time process optimization. Key contributions include moisture control in electrode production, electrochemo-mechanical characterization of solid-state systems, and robotics solutions for deformable object assembly, all integrated with machine learning for quality assurance in industrial settings. Analysis of his 2023-2025 publications reveals a dominant research trajectory toward solving production bottlenecks in next-generation energy storage. The work demonstrates increasing integration of computational modeling with empirical validation, particularly in solid-state battery manufacturing and high-voltage electrolyte systems. A notable trend is the cross-pollination of robotics, computer vision, and uncertainty quantification techniques to address complex assembly challenges and distribution shifts in quality monitoring, reflecting industry's urgent need for adaptable, data-driven production systems. Leading TUM's specialized laboratories for battery cell production, Daub's team maintains comprehensive facilities for electrode calendering, electrolyte filling, and cell assembly with integrated tracking and tracing capabilities. The research infrastructure supports collaborative projects with automotive OEMs and battery manufacturers to develop scalable production processes, emphasizing environmental sustainability through water-based electrode production and footprint optimization. Current initiatives focus on digital factory modeling and prelithiation technologies for next-generation battery systems.
Prof. Alexander Pretschner is a Professor of Software & Systems Engineering at the Technical University of Munich (TUM) and Founding Director of the Bavarian Research Institute for Digital Transformation (bidt). He also serves as Scientific Director of fortiss, a Bavarian research institute for software-intensive systems. His research focuses on software engineering, testing, information security, and ethical software development. Pretschner holds a PhD from TUM and has held academic positions at Karlsruhe Institute of Technology (KIT) and TU Kaiserslautern. He is a co-editor of several prestigious journals, including IEEE Transactions on Reliability and the Journal of Software Testing, Verification and Reliability. Education: PhD in Computer Science, Technical University of Munich MSc in Computer Science, University of Kansas (on Fulbright Scholarship) Diplom in Computer Science, RWTH Aachen University Research Interests: His work spans testing methodologies, secure software design, and ethical considerations in agile development. Notable contributions include frameworks for metamorphic testing, distributed data usage control, and accountability mechanisms for cyber-physical systems. Awards: IBM Faculty Award (2012, 2013) Google Focused Research Award (2011, 2012) EARTO Innovation Prize (2014) 2nd Platz Supervisory Award (2020) Advising & Grants: Pretschner has supervised numerous PhD and Master’s students, contributing to over 200 publications. He leads projects like EDAP (Ethical Deliberation in Agile Processes) and collaborates with industry partners on cybersecurity and AI ethics initiatives. Labs & Teams: His work is anchored in bidt, fortiss, and TUM’s Chair of Software & Systems Engineering, focusing on societal impacts of digitalization and trustworthy AI systems.
Prof. Dr.-Ing. Ahmad Osman is a Professor at the Saarland University of Applied Sciences (htw saar), specializing in Test Technologies and Test Methods within the Faculty of Engineering. He also holds an Adjunct Professor position at Laval University in Quebec, Canada, in the Department of Electrical Engineering and Computer Science. His research focuses on Artificial Intelligence applications in Signal and Image Processing for Non-destructive Testing (NDT) , with extensive work on Deep Learning , 3D Ultrasound Tomography , and Sensor Data Fusion in industrial contexts. Engineering Artificial Intelligence Signal Processing Image Processing Non-destructive Testing Quality Control Augmented Reality Osman leads the AutomaTiQ research group and serves as Head of the Algorithms/Signal and Data Processing Department at Fraunhofer IZFP . His recent publications (2017–2022) emphasize Deep Learning for defect detection in CFRP , Terahertz Imaging for artwork diagnostics, and Acoustic Sensors for agricultural quality control. He has organized international conferences on Structural Health Monitoring and contributed to Springer books on NDT technologies. His projects include ComforTex-AI (2024) and development of 3D positioners for ultrasound measurements. Collaborations span institutions in Germany, Canada, Italy, and Brazil, with advisory roles in the German Society for NDT and technical committees for conferences in Montreal and Egypt.
Prof. David Hunger leads the Cavity Quantum Optics Group at the Physics Institute (PHI) of Karlsruhe Institute of Technology (KIT). His research focuses on optically addressable spins in condensed matter, cavity-enhanced light-matter interactions, and quantum photonics with applications in sensing, spectroscopy, and quantum computing. The group develops fiber-based microcavities for coherent spin-photon interfaces, rare-earth ion qubits, and cavity-enhanced imaging of nanoscale systems. Notable projects include the BMBF-funded NEQSIS and SPINNING initiatives for quantum communication and diamond-based quantum computing. The group also pioneered Qlibri , a spin-off company commercializing optical fiber microcavities for quantum optics and microscopy. Recent breakthroughs include record spin coherence in SnV centers and ultra-stable nanopositioning platforms for cryogenic experiments. Affiliations: Faculty of Physics, KIT; Max Planck School of Photonics Grants: BMBF Grand Challenge (Quantum Communication), BMBF SPINNING (Diamond Qubits) Labs/Teams: Cavity Quantum Optics Group, Qlibri spin-off Students and postdocs in the group work on topics like collective cavity effects, molecular spin platforms, and cavity-enhanced sensing of liquid-phase nanosystems.
Prof. Dr. Tobias Gemmeke is a University Professor at RWTH Aachen University's Faculty of Electrical Engineering and Information Technology, leading the Chair of Integrated Digital Systems and Circuit Design. His work focuses on neuromorphic computing, hardware accelerators, and energy-efficient electronics. He has pioneered advancements in FPGA-based computational neuroscience simulators, neuromorphic processor architectures, and sensor integration for industrial and medical applications. Research interests include time-domain computing, ReRAM reliability, and co-optimization of neural networks with hardware. Notable contributions include the neuroAIx framework for accelerated neuroscience simulations and energy-efficient ASIC designs for post-quantum cryptography. He actively explores memristive devices and domain generalization techniques for edge computing. Recent publications highlight innovations in spiking neural networks, sensor systems for plain bearings, and time-domain compute-in-memory engines. His work bridges theoretical neuroscience with practical hardware implementations, emphasizing scalability and real-time performance.
Chanchal K. Roy is Professor of Software Engineering/Computer Science at the University of Saskatchewan and Co-Director of the Software Research Lab. He leads an NSERC CREATE graduate program on Software Analytics Research and co-leads the Data Management group for an NSERC CFREF project on Food Security, with over 170 publications cited 6,000+ times. His research centers on software clone detection using the widely adopted NICAD system, software evolution, empirical studies, and AI-driven software analytics. Recent work integrates large language models for code generation, clone detection in the AI era, and developer interactions with tools like ChatGPT, emphasizing practical applications in maintenance and analytics. Analysis of his 15 most recent publications reveals a strong trend toward AI/ML integration in software engineering: 12 of 15 articles (2025) explore LLMs, quantum computing, or deep learning for tasks like bug localization, code snippet generation, and feature-toggle analysis. Key themes include empirical validation of AI tools, Stack Overflow data mining, and cross-domain frameworks for Society 5.0. His scientific awards include: Most Influential Paper Awards (SANER 2018, ICPC 2018) Outstanding Young Computer Science Researcher Award (CS-Can/Info-Can, 2018) New Researcher Award (University of Saskatchewan, 2019) New Scientist Research Award (College of Arts and Science, 2019) As lead of the NSERC CREATE program and CFREF data group, he mentors graduate students in software analytics while securing major grants. He actively serves on program committees for ASE, ICSE, and FSE, reviewing journals and organizing workshops on clone detection and empirical methods. His lab focuses on real-world applications in food security data management and software evolution. The Software Research Lab, co-directed by Roy, drives projects like NICAD and the NSERC CREATE initiative, emphasizing open-source contributions and industry collaboration. Current efforts include quantum-SE integration and AI-augmented maintenance tools under the CFREF food security mandate.
Professor Emiliano Cortés is a faculty member at the Ludwig Maximilian University of Munich (LMU), where he leads research in Plasmonic and Photonic Chemistry at the Nano-Institute Munich. His work bridges the fields of nanotechnology, physical chemistry, and materials science, focusing on light-matter interactions for energy conversion applications. Dr. Cortés' research focuses on plasmonics , photocatalysis , and electrocatalysis at the nanoscale. His group investigates how the dynamics of photons, plasmon-polaritons, carriers, phonons, and molecular states influence chemical reactivity. A key aspect of his work involves developing techniques to study plasmonic systems at the single particle level and designing rational synthesis approaches for plasmonic colloidal photo and electrocatalysts. His research has significant implications for sustainable energy technologies, environmental remediation, and advanced sensing applications. Analysis of Professor Cortés' recent publications reveals a strong focus on energy conversion processes, with particular emphasis on CO2 reduction, ammonia synthesis, and hydrogen production. His work integrates plasmonic effects with catalytic processes to enhance reaction efficiencies, often through innovative interface engineering and nanostructure design. The research spans fundamental studies of charge carrier dynamics to practical applications in energy storage and environmental technologies. Professor Cortés actively mentors doctoral candidates and postdoctoral researchers, currently advertising open positions for projects on Single particle photo and electrocatalysis and Synthesis of hybrid colloids . His research group, the Hybrid Plasmonics Lab (www.hybridplasmonics.org), receives funding from various sources to support their work on plasmon-mediated chemistry for sustainable applications. The Cortés research group operates within the Nano-Institute Munich, utilizing state-of-the-art facilities for nanomaterial synthesis, characterization, and testing. Their work combines experimental approaches with theoretical modeling to understand and harness light-matter interactions at the nanoscale for practical applications in energy conversion and environmental technologies.
Dr. Jing Wang is a Professor in the Department of Bioinformatics at Southern Medical University's School of Medicine, with extensive research at the intersection of artificial intelligence and biomedical applications. Her work demonstrates strong cross-disciplinary collaboration across medical institutions, engineering departments, and computer science research groups. Her primary research interests include Artificial Intelligence in Healthcare , Biomedical Engineering , and Traditional Chinese Medicine Informatics , with recent publications showing particular expertise in medical imaging analysis, diagnostic assistance systems, and clinical decision support. Her work spans both theoretical algorithm development and practical clinical implementations. Analysis of her 15 most recent publications (2025-2026) reveals a strong trend toward clinically applicable AI systems, with approximately 60% of publications focused on medical diagnostics and treatment support systems. The remaining publications demonstrate expertise in industrial applications of computer vision and fundamental AI research. Her work shows consistent collaboration with both domestic Chinese institutions and international research groups. Notable scientific contributions include: Development of 'Tianyi', a traditional Chinese medicine language model for clinical practice Innovations in bionic soft robotics for rehabilitation assistance Novel approaches to medical image analysis for cancer diagnostics Her research program appears well-funded with consistent publication output across high-impact journals in biomedical engineering, AI, and medical informatics. Current work suggests strong emphasis on translating AI research into clinical practice, particularly in diagnostic support systems and rehabilitation technology.
Nikolaus Rajewsky is a leading Professor at the Max Delbrück Center for Molecular Medicine (MDC) and Charité – Universitätsmedizin Berlin , where he founded and directs the Berlin Institute for Medical Systems Biology (BIMSB) . His lab integrates experimental (biochemistry, molecular biology) and computational (bioinformatics, physics) approaches to study RNA regulation in gene expression , with applications to developmental biology, regeneration, neurodegenerative diseases, and cancer . Using model systems like C. elegans , planaria, and human brain organoids, his team pioneers cutting-edge methods such as MirDeep , DistMap , and FLAM-seq for RNA analysis. His research focuses on single-cell transcriptomics , spatial RNA sequencing , and circular RNA (circRNA) regulation , revealing novel roles for circRNAs like CDR1as in neuropsychiatric disorders. Recent work includes 3D tumor microenvironment mapping and computational modeling of RNA metabolism in diseases. Scientific Awards : Gottfried Wilhelm Leibniz Prize (2012) EMBO Membership (2010) Honorary PhD, Sapienza University of Rome (2014) Berlin Science Award (2009) His team's recent articles highlight breakthroughs in 3D spatial transcriptomics , circRNA degradation mechanisms , and mitochondrial disease modeling using human brain organoids. The lab actively collaborates with clinical partners across Charité and European institutions, driving the LifeTime initiative for cell-based interceptive medicine.
Karin Jacobs is a Professor in the Department of Physics at Saarland University, where she leads the research group for soft matter physics within the Faculty of Natural Sciences and Technology. Her work bridges experimental physics and applied materials science, focusing on interfacial phenomena, thin films, and functional materials. Research Interests: Her group investigates the stability of coatings, properties of simple and complex fluids, and the adhesion of biomolecules on surfaces. Using advanced experimental techniques such as atomic force microscopy (AFM), ellipsometry, surface plasmon resonance spectroscopy, optical microscopy, and ultra-high vacuum (UHV) methods like photoelectron spectroscopy, her team probes nanoscale and microscale interactions at solid-liquid and solid-gas interfaces. The research spans fundamental and applied domains, including the synthesis and characterization of graphene and boronitrene, production of water-in-water vesicles using hydrophobins, and bacterial adhesion studies. These investigations are often linked to industrial applications in the paint, semiconductor, and biomedical sectors. Publication Trends: Over the past 15 years, her publications reflect a consistent focus on surface physics and soft matter. Key themes include graphene synthesis via liquid precursor deposition (including unconventional sources like fingerprints), interfacial rheology, biopolymer adsorption, and quantitative imaging analysis. The interdisciplinary nature of her work is evident in the combination of physics, chemistry, and biological interfaces. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: As head of an active research group, Prof. Jacobs supervises graduate students and postdoctoral researchers, though specific names are not listed. Her collaborations with theoretical groups and external institutions (e.g., University of Augsburg) suggest participation in joint grants and funded projects, particularly in nanomaterials and surface science. The applied orientation of her research indicates engagement with industry partners in coatings and semiconductor technologies. Labs and Teams: The Jacobs Group operates a well-equipped experimental laboratory at Campus E2 9, Saarland University, specializing in surface analysis and soft matter characterization. The team includes researchers working on biofilms, microfluidics, and functional materials, supported by technical and administrative staff.
James C. Davis is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He leads the Duality Lab, which focuses on the engineering of software-intensive computing systems with particular interest in how these systems fail and how those failures can be mitigated. His research takes a socio-technical approach, considering both human and technical perspectives in system engineering. Dr. Davis received his PhD in Computer Science from Virginia Tech, where he was advised by Dongyoon Lee. His research interests span empirical software engineering, security, safety, testing, and web technologies, with a strong emphasis on practical impact and measurement. He applies a socio-technical philosophy to his work, believing high-quality systems must be engineered considering both human and technical perspectives. His recent research focuses on software supply chain security, regular expression vulnerabilities (particularly ReDoS), pre-trained model security, and failure analysis in software systems. His work often involves empirical studies of real-world software systems and security practices, with a strong emphasis on practical impact and measurable results. Dr. Davis has received significant funding from the National Science Foundation, Google, Cisco, and Rolls Royce for his research. His publications appear in top-tier venues including ICSE, FSE, ASE, and USENIX Security. He has served on program committees for many major software engineering and security conferences. Among his notable achievements are being elevated to IEEE Senior Member in 2022, receiving the Ruth and Joel Spira Outstanding Teacher Award from ECE@Purdue in 2022, and multiple Best Paper and Best Poster awards. He has successfully mentored numerous PhD and Master's students, with several completing their theses on topics related to software security and engineering. Dr. Davis actively recruits graduate and undergraduate research assistants for his Duality Lab, which has produced influential work on software failure analysis, regular expression security, and machine learning supply chain security. His lab is supported by multiple federal and industry grants focused on improving the security and reliability of software systems.
Yingfei Xiong is an active Associate Professor at Peking University, China, specializing in software engineering and programming languages. With a consistent research trajectory from 2013 through 2026, Xiong has established themselves as a prominent figure in the software engineering research community, regularly contributing to top-tier conferences including SPLASH, ICSE, ASE, and PLDI. Dr. Xiong's research primarily focuses on program synthesis, automated program repair, and software analysis techniques. Their work bridges theoretical programming language concepts with practical software engineering applications, particularly in developing novel approaches for code generation, bug fixing, and program optimization. The research demonstrates strong interdisciplinary connections between traditional software engineering, programming languages theory, and emerging AI techniques. Analysis of Xiong's publication trends reveals a clear evolution in research focus, beginning with foundational work in API transformations and program adaptation around 2013-2016, shifting toward program repair techniques from 2017-2020, and most recently incorporating machine learning and neural approaches into program synthesis and repair (2021-2026). The work consistently addresses practical challenges in software development while maintaining theoretical rigor, with increasing integration of AI techniques in recent years. Dr. Xiong has served in various leadership roles across the software engineering conference ecosystem, including program committee membership and session chair positions at major conferences. Their extensive service demonstrates recognition by peers as a subject matter expert in software engineering and programming languages research. While specific grant information isn't detailed in the provided text, the sustained publication record suggests successful research funding.
Rainald Loehner is a Distinguished Professor of Fluid Dynamics at George Mason University's Center for Computational Fluid Dynamics. Since 2003, he has led the Center for Computational Fluid Dynamics at George Mason University. He is currently a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS) for 2023, hosted by Professors Kai-Uwe Bletzinger and Roland Wüchner in the 'Adjoint-Based System Identification of Large-Scale Structures' Focus Group. Loehner received his Diplom Ingenieur (Maschinenbau) degree from the Technical University of Braunschweig, and his PhD and a DSc in civil engineering from the University College of Swansea, Wales. After teaching at Swansea for a year, he worked at the Naval Research Laboratory in Washington, DC, followed by a research professorship at George Washington University. He joined George Mason University as an associate professor and was promoted to full professor in 1995 and distinguished professor in 2004. With over 35 years of experience, Professor Loehner's research spans the complete pipeline of numerical solvers and simulation tools. His expertise includes pre-processing, grid generation, numerical methods, field solvers, parallel computing, adaptive mesh refinement, fluid-structure interaction, shape optimization, system identification, and computational crowd dynamics. His current work focuses on developing advanced field solvers for compressible and incompressible flows, acoustics, electromagnetic wave propagation, heat and mass transfer, structural mechanics, and fluid-structure interaction. Key application areas include blast mitigation, ship hydrodynamics, blood flow, contaminant transport, and pedestrian safety. Loehner's recent research output (2020-2024) shows a strong trend toward digital twin technology and adjoint-based methods for structural analysis and optimization. His publications focus on high-fidelity digital twins for detecting structural weaknesses, risk assessment in engineering systems, and optimization of sensor placement. His work bridges computational mechanics with machine learning approaches, particularly in system identification and inverse problems, demonstrating how computational methods can solve complex real-world engineering challenges. 2020: Ranked #15119 in the Stanford List of Most Influential Scientists of the World; #8 in Aerospace and Aeronautics 2010: Distinguished International Career Award, Argentine Association of Computational Mechanics 2008: Fellow, International Association for Computational Mechanics 2006: Associate Fellow, AIAA 2005: Honorary Professor, University of Wales Swansea 2005: Advisory Professor, Shanghai Jiao Tong University 2004: Distinguished Professor of Fluid Dynamics, George Mason University 1999: Computational Mechanics Achievements Award, Japan Society of Mechanical Engineering 1993: Doctor of Science in Civil Engineering, University College of Swansea 1979-1983: Studienstiftung des Deutschen Volkes (Top 1% of German Students) Professor Loehner has mentored numerous students through his work at George Mason University and has supervised research in computational fluid dynamics, structural mechanics, and related fields. His research has been supported by various grants from government agencies and industry partners, enabling the development of advanced simulation tools applied in aerodynamics, hydrodynamics, shock-structure interaction, and medical applications. His codes and methods have been widely adopted in industry and academia for applications ranging from aircraft and ship design to medical simulations and urban pathogen transmission modeling. Loehner leads the Center for Computational Fluid Dynamics at George Mason University, which focuses on developing cutting-edge computational methods for fluid dynamics and related multiphysics problems. The center works on strategic application areas including blast mitigation, ship hydrodynamics, blood flow simulation, and pedestrian movement modeling. As a TUM-IAS Fellow, he collaborates with the Chair of Computational Modeling and Simulation at TUM on adjoint-based system identification of large-scale structures, bringing together expertise in computational mechanics and digital twin technology to address complex engineering challenges.
Lionel C. Briand is a Professor of Software Engineering with shared appointments at the University of Luxembourg's SnT Centre for Security, Reliability, and Trust and the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a Canada Research Chair (Tier 1) in Intelligent Software Dependability and Compliance and serves as Director of Lero, Ireland's national software research center. His academic leadership spans over 25 years of collaborative research with industry partners across automotive, aerospace, energy, financial, and legal domains. Professor Briand's research focuses on software verification and validation, trustworthy AI systems, model-driven engineering, and empirical software engineering methodologies. His work bridges theoretical foundations with industrial applications, particularly in cyber-physical systems where machine learning components interact with safety-critical control systems. He has pioneered techniques for testing AI-enabled systems, GDPR compliance automation, and mutation analysis for space systems. His publication portfolio demonstrates consistent innovation in software testing, with recent emphasis on large language models for test generation, automated compliance checking, and safety analysis of deep neural networks. Key trends include black-box testing methodologies, metamorphic testing for security, and search-based approaches for DNN validation. IEEE Fellow and ACM Fellow IEEE Computer Society Harlan Mills Award (2012) ACM SIGSOFT Outstanding Research Award (2022) IEEE Reliability Society Engineer-of-the-Year Award (2013) ERC Advanced Grant recipient (2016) Fellow of the Academy of Science, Royal Society of Canada (2023) ICSE 2011 Most Influential Paper Award As Director of Lero and holder of a Canada Research Chair, Professor Briand leads major research initiatives including an ERC Advanced Grant on cyber-physical system modeling and testing. His industrial collaborations generate substantial grant funding, particularly in automotive safety validation and regulatory compliance automation. He mentors numerous researchers through his dual appointments and serves on program committees for top software engineering conferences. Professor Briand directs research activities at the SnT Centre's SVV department, focusing on software verification and validation. His team develops practical tools like MASS for space system mutation analysis and COREQQA for compliance requirements understanding, with strong industry adoption in automotive and aerospace sectors.
