James H. Cross II is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering, with prior affiliations at the University of Nevada Las Vegas' Business School and Drexel University's College of Medicine. His research focuses on software engineering education, program visualization, reverse engineering, and educational technology. Key Roles : Software Engineering Educator, Java Pedagogy Innovator, Program Visualization Researcher His work emphasizes enhancing code comprehension through dynamic data structure visualizations (e.g., jGRASP IDE), reverse engineering methodologies, and interdisciplinary applications in software maintenance and curriculum development. Recent trends in his publications (2019–2024) include FAIR data principles, ontological frameworks, and token-based incentives for scholarly contributions. Notable collaborations include T. Dean Hendrix, Larry A. Barowski, and David A. Umphress. Affiliated with institutions like Auburn University, University of Nevada Las Vegas, and Drexel University's College of Medicine, his career spans software engineering research, educational tool development, and academic leadership.
Bo Wang is an active academic researcher primarily affiliated with multiple Chinese institutions, with strong connections to Tsinghua University, Beijing Jiaotong University, and other leading Chinese universities. His research spans artificial intelligence, machine learning, computer vision, medical image analysis, and intelligent control systems, demonstrating significant interdisciplinary work across computer science, engineering, and biomedical applications. Primary institutional affiliation: School of Computer Science and Technology at multiple Chinese universities Active research areas: AI/ML applications in healthcare, computer vision, federated learning, and intelligent control systems Extensive publication record across top-tier venues in multiple disciplines Wang's research interests focus on the intersection of artificial intelligence and practical applications. His work demonstrates strong expertise in developing novel machine learning architectures for medical image analysis, including applications in CT imaging, MRI, and sperm tracking. He has made significant contributions to federated learning approaches for large language models, sliding mode control systems, and molecular optimization frameworks. His research consistently bridges theoretical advances with practical implementations across healthcare, manufacturing, and environmental monitoring domains. Analysis of Wang's recent publications reveals a strong trend toward interdisciplinary AI applications, particularly in medical imaging and bioinformatics. His work on VAE-GANMDA for microbe-drug association prediction, ACE-QSM for accelerating MRI acquisition, and text-guided molecular optimization demonstrates innovative approaches at the intersection of AI and life sciences. Wang also maintains active research in industrial applications including digital twin technology for energy systems and robust scheduling approaches for multi-factory production. Notable research contributions include: FLFT: A Large-Scale Pre-Training Model Distributed Fine-Tuning Method with Federated Learning VAE-GANMDA: Microbe-drug association prediction model ACE-QSM: Accelerating quantitative susceptibility mapping using diffusion models Digital twin-empowered power consumption prediction systems Wang actively collaborates with researchers across China and internationally, with publications spanning computer science, engineering, medical imaging, and environmental science journals. His work demonstrates strong technical depth across multiple AI methodologies while maintaining focus on practical applications that address real-world challenges in healthcare, manufacturing, and environmental monitoring.
Professor Siegfried Müller is a full professor at the Institute for Geometry and Practical Mathematics within the Faculty of Mathematics, Computer Science and Natural Sciences at RWTH Aachen University. His research focuses on developing advanced numerical methods for solving complex fluid dynamics problems, with particular expertise in conservation laws, adaptive multiscale techniques, and multiphase flow modeling. He maintains an active research program with numerous publications in leading computational mathematics journals and collaborates extensively with researchers across multiple institutions. Professor Müller's research interests span a wide range of computational mathematics topics including Conservation Laws, Finite Volume Schemes, Discontinuous Galerkin Methods, Adaptive Multiscale Techniques, and specialized applications in Fluid Dynamics. His work demonstrates particular strength in developing numerical methods for two-phase flow systems, transpiration cooling applications, and surface lubrication phenomena. His research bridges theoretical mathematical analysis with practical engineering applications, particularly in aerospace and mechanical engineering contexts. His recent publications reveal a strong focus on advancing numerical techniques for hyperbolic conservation laws, with increasing emphasis on stochastic methods, multilevel approaches, and coupled system modeling. His work spans both theoretical developments in numerical analysis and practical applications in fluid dynamics, with particular attention to multiphase flow systems and cooling technologies. The publications show a clear progression toward more complex, high-dimensional problems and increasingly sophisticated numerical techniques to address computational challenges. Professor Müller has led and participated in numerous research projects funded by German research organizations including DFG Priority Programmes, BMBF projects, and DFG Research Training Groups. His projects have focused on hyperbolic balance laws, adaptive numerical methods, transpiration cooling, and textured surface lubrication. He has organized multiple workshops on multiresolution methods and active drag reduction, demonstrating leadership in his research community. Professor Müller's research group at RWTH Aachen collaborates closely with engineering departments and industry partners to apply advanced numerical methods to practical engineering challenges. His team has developed specialized computational tools for simulating complex fluid phenomena, particularly in aerospace applications where cooling technologies and fluid-structure interactions are critical. The group maintains strong connections with international research communities in computational mathematics and fluid dynamics.
Dirk Müller is a Professor at RWTH Aachen University, holding positions as Director of the Institute for Energy Efficient Buildings and Indoor Climate (E.ON Energy Research Center) and Deputy Dean of the Faculty of Mechanical Engineering. He leads research in building climate technology, energy systems, and sustainable building design. Müller's career includes roles at Behr GmbH & Co. and Robert Bosch GmbH before academia. His research focuses on heat pumps, thermal systems, and energy efficiency in buildings. Education: Diplom in Mechanical Engineering (RWTH Aachen), Ph.D. in Heat Transfer and Climate Technology (RWTH Aachen), and MBA from Fernuniversität Hagen. He also holds a DAAD fellowship at Dartmouth College (USA). Research Interests: Advanced HVAC systems, refrigerant optimization, building energy systems, and grid integration of renewable energy. Notable projects include the SUSTAIN 2 initiative for smart building renovation and the Agentensysteme (AGENT) project for building energy control. Awards: Borchers-Plakette (2000), VDI Ehrenring (2004), and Fellow of the European HVAC Associations (2014). His work spans 150+ publications in 2023-2025, focusing on heat pump efficiency, energy storage, and indoor climate modeling. Leadership roles include Chair of the Fachkommission Gebäude-Klima and Board Member of the Helmholtz Institute IEK-10. He advises companies like Viessmann and TROX GmbH.
Klaus Wehrle is a Professor of Computer Science and Head of the Communication and Distributed Systems Group (Informatik 4) at RWTH Aachen University. He holds a diploma (1999) and doctorate (2002) from the University of Karlsruhe (now KIT). His research focuses on network protocols, cybersecurity, and distributed systems, funded by DFG, ERC, EU, and industry. He leads the DFG Priority Program on Cyber-Physical Networking and holds ERC grants. Awards include Südwestmetall and FZI Dissertation Prizes. He serves on IEEE, ACM, and DFG committees. His work spans protocol engineering, network simulation, and reliable communication software. He advises the Department of Computer Science at RWTH and collaborates on projects like In-Network Computing and Industrial IoT security. His research addresses industrial systems, smart grids, and privacy-preserving data sharing.
Nadine Großmann is a PhD Candidate at Freie Universität Berlin, affiliated with the Department of Biochemistry under the School of Chemistry and Biochemistry within the Department of Biology, Chemistry, and Pharmacy. She is a member of the Knaus Group , specializing in Signal Transduction research. Research Interests Signal Transduction Protein Interactions Chemical Biology Molecular Biology Cell Signaling Sustainable Research Practices Her work contributes to the lab’s focus on developing chemical dimerizer systems for protein interaction control and monitoring, as seen in recent publications like MT36 sensor development in Angewandte Chemie . Contact Email: nadine.grossmann@fu-berlin.de Phone: +49 30 838 52911
Michael B. Chamunorwa is a Research and Design Engineer and PhD candidate at the University of Oldenburg's Department of Computing Science (School II), specializing in Media Informatics and Multimedia Systems. His research focuses on designing user interfaces embedded in everyday objects for smart home control, exploring embodied interaction and repurposing household items as smart home interfaces. He holds a Bachelor of Technology in Software Engineering and a Master's in Computer Science from the Namibia University of Science and Technology. Michael has taught as a tutor and project supervisor in courses such as 'Experiments and Studies' and 'Makers’ Lab - Things that Think', supervising projects like 'Rich Interactive Materials for Everyday Objects in the Home'. His work bridges theoretical research with practical applications, including developing tools for cultural preservation with marginalized communities in Namibia. Key research areas include tangible user interfaces, embodied interaction, and smart home systems. His projects often involve collaborations with industry-standard frameworks and have been published in venues like ACM International Conference on Mobile and Ubiquitous Multimedia (MUM) and Interactive Surfaces and Spaces. Michael's current PhD project investigates secondary affordances of everyday objects to enhance smart home user experiences. He has contributed to open-source tools like the 'Popup Observation Kit' for remote usability testing and the 'Sweet Spots' AR platform for interaction area visualization. He has been actively involved in the Virtual and Augmented Reality Lab (inf174) and the Makers’ Lab, emphasizing hands-on innovation in technology design. His work reflects a commitment to both academic rigor and real-world societal impact through technology.
Prof. Dr. Armando Walter Colombo is a Professor at the Department of Technology, Electrical Engineering and Informatics at the University of Applied Sciences Emden/Leer. He leads the Institute I2AR as Scientific Director and coordinates the DAAD/DAHZ Binational Master in Industrial Informatics with the Universidad Tecnológica Nacional-FRRe in Argentina. His research focuses on Cyber-Physical Systems (CPS), Industrial Digitalization, Industry 4.0, and Smart Manufacturing. Key areas include asset administration shells, IoT integration, and sustainable industrial automation. He holds IEEE Fellow status and is a Distinguished Lecturer for the IEEE Systems Council. He has pioneered educational frameworks like T-CHAT and contributed to standards alignment (RAMI4.0, IEEE Industrial Agents). Recent publications emphasize Industry 4.0 compliance, digital twins, and AI in logistics. Responsibilities: DAAD Master Coordinator, Institute I2AR Director, and International Relations Officer. Awards: IEEE Fellow, Distinguished Lecturer (IEEE Systems Council). Grants & Partnerships: DAAD-funded binational programs, EU-funded PERFoRM projects. His work bridges academia and industry through platforms like the ICPS-based Digital Factory Lab, addressing SME digitalization and sustainable automation.
Prof. Sven Steinigeweg is a Professor of Environmental Technology and Process Automation at the University of Applied Sciences Emden/Leer, affiliated with the School of Natural Science and Technology. His work focuses on sustainable energy systems, particularly biogas production optimization, CO2 capture, and hydrogen technology. He leads projects like H2Watt (Hydrogen on North Sea Islands) and Smart-RLT (Energy Efficiency in Air Handling Devices), funded by Interreg, the German Federal Environmental Foundation, and the EU. Research interests include flexible biogas plant operation, power-to-gas systems, and eco-efficient energy processes. Notable contributions address residual load management, anaerobic digestion modeling, microbial community dynamics, and life cycle assessment of technical processes. He collaborates on EU-funded initiatives such as HPEM2GAS (cost-effective PEM electrolysis) and Power2Flex (flexible renewable energy use). His publications span 2014–2019, emphasizing biogas flexibility, environmental impact analysis, and process automation. Key projects include Synflex (synergy effects in biogas plants) and Biomasstec-Raman (Raman spectroscopy for biogas monitoring). Prof. Steinigeweg’s research integrates modeling, experimental validation, and interdisciplinary approaches to advance sustainable energy solutions, with a focus on grid balancing, carbon utilization, and renewable integration.
Prof. Dr. Gefei Zhang is a Professor of Media Informatics at HTW Berlin. He holds a Master’s and PhD from Ludwig-Maximilians-Universität München (LMU). His research focuses on Data Science and Software Engineering, with expertise in aspect-oriented modeling, UML state machines, and model-driven development. He teaches software and data science courses and previously contributed to the Programming and Software Engineering Group (PST) at LMU, now part of the Software and Computational Systems Lab (SoSy). Research interests include aspect-oriented programming, web engineering, and adaptive systems. He has published extensively on topics like UML state machines, software metrics, and HiLA framework applications. Awards include the Best Paper Award at AOM@MoDELS'09. Office hours are by appointment. His work bridges academic research and industry, with past roles in software development for large-scale web applications. Collaborations and grants are part of his ongoing contributions to computer science education and innovation.
Prof. Dr. Christof Menzel is a Professor in the Department of Nutritional Science at Niederrhein University of Applied Sciences. His research focuses on Life Cycle Assessment (LCA) of food systems, sustainability, and environmental impacts of food production and consumption. He leads projects such as JACK&05 (2016-2018) and Life Cycle Assessments (2014-present), emphasizing digital tools in education and sustainable practices. He has supervised numerous theses on topics like eco-balance of oat milk, kitas' meals, and coffee preparation systems. Awards include the Wissenschaftspreis 2023 and Nachwuchspreis 2021. He actively participates in university committees, including the Internal Accreditation Commission and Sustainability Advisory Board. Education: Advanced degrees in Mathematics and Environmental Science (implied from publications). Key Projects: LCA methodology development, RFID applications in food quality management, and educational technology integration. Teaching: Mathematics, statistics, and applied IT for nutritional science students. Grants: Funded by Stiftung zur Förderung der Qualität in Lehre und Studium (QV-Mittel) and EU Interreg programs. His research spans food packaging sustainability, consumer behavior analysis, and institutional catering systems. Collaborations with industry partners include dairy producers, bakeries, and food laboratories. He also contributed to the LowFett 30 dietary program evaluation and RFID-NRW-NL supply chain optimization. Recent work includes optimizing eco-balances for decentralized food production and introducing LCA tools like Umberto 11. His interdisciplinary approach bridges environmental science, food technology, and data analysis.
Prof. Dr. Swen Günther holds the Chair of Process and Innovation Management at HTW Dresden within the Faculty of Business Administration . His academic leadership spans teaching and research in production management, project management, process/quality management, and technology/innovation management. He oversees the Bachelor's and Master's programs in Industrial Engineering and collaborates with international partner universities like Satakunta/VAMK (Finland) and FH Burgenland (Austria). Education & Career: Günther earned his PhD (Dr. rer. pol.) from TU Dresden's Market-Oriented Management department. Prior to academia, he worked at Procter & Gamble in manufacturing and quality management (2008-2015). His research focuses on Lean Six Sigma, TRIZ Reverse, transfer indicators, and digitalization. He leads the BMBF-funded 'Transfer_i' project (2019-2021), developing transfer metrics for academia-industry collaboration. Research Interests: His work emphasizes systematic knowledge/technology transfer, digital transformation in processes, and innovative management methodologies. Recent studies address transfer indicators for universities, cost-benefit analyses of digital projects, and empirical research on management trends. Teaching & Advising: Over 50+ theses supervised (2018-2021) across process optimization, quality management, and innovation transfer. He advises companies on Lean/Six Sigma implementation and organizes industry excursions with firms like T-Systems MMS and König & Bauer. Professional Engagement: Member of German Society for Quality (DGQ) and Society for Organisation (GFO). Regularly publishes in journals like Qualität in der Wissenschaft and Zeitschrift für Organisation .
Prof. Dr. Siegfried Blechert is a Professor at the Institute of Chemistry, Technische Universität Berlin, specializing in homogeneous catalysis, organic synthesis, and natural product synthesis. He is affiliated with the Organic Chemistry Research Group within Faculty II (Mathematics and Natural Sciences). His research focuses include catalyst development, alternating copolymerizations, and substrate synthesis, with contributions to UniCat (Cluster of Excellence for Unifying Systems in Catalysis). His work emphasizes sustainable chemistry and photocatalytic processes, as evidenced by publications in journals like Energy Technology and Angewandte Chemie International Edition. Blechert’s lab has developed novel catalysts for reactions such as hydroamination and ring-closing metathesis. He collaborates with institutions like the Fritz Haber Institute and leads projects on energy-efficient chemical processes. Research interests span the design of microporous polymer networks, light-driven reactions, and transition metal complexes. His team investigates catalysts for hydrogen evolution and C-C bond formation, with applications in green chemistry and renewable energy. Blechert’s work bridges fundamental catalytic mechanisms with industrial applications, including collaborations with companies like ORAFOL Europe and B. Braun Melsungen AG. He has contributed to initiatives like the Green Chemistry East network, promoting sustainable chemistry in Eastern Germany. His publications highlight advancements in organocatalysts, carbon nitride semiconductors, and metal-organic frameworks, reflecting a commitment to both academic and applied research. Blechert’s group is involved in training programs, such as the ChemClub and ChemKids, fostering interest in chemistry among students. Despite no explicitly listed awards, his contributions to catalysis research have been recognized through institutional collaborations and funding in sustainable chemistry.
Ulf Meyer is a Lecturer at the Department of Mechanical Engineering and Process Technology at the University of Applied Sciences Osnabrück. His research focuses on automation technology, industrial robotics, and energy-efficient manufacturing systems. He leads the Automation Technology Department, emphasizing practical applications in modern production environments. His research interests span automation systems in manufacturing, sensor and control technologies, and digital transformation in industrial processes. Key themes include improving energy efficiency, integrating robotics into production workflows, and leveraging Industry 4.0 principles for smart factories. Ulf Meyer's publications from 2017 to 2022 highlight advancements in automation, emphasizing trends like energy-efficient solutions, digitalization, and the role of robotics in industrial applications. His work bridges theoretical concepts with real-world manufacturing challenges. He currently leads the Automation Technology Department, driving interdisciplinary research and practical innovation in mechanical engineering and process technology.
Prof. Wangzhong Mu is a Senior Lecturer (Docent) in the Department of Materials Science and Engineering at KTH Royal Institute of Technology, Stockholm. His research focuses on sustainable metallurgy, microstructure physics, and alloy design. He leads the thermo-physical property analysis section in the Hultgren Lab and is affiliated with Digital Futures at KTH. Educations: PhD in Materials Science, KTH Royal Institute of Technology (2015) MSc/Bachelor's in Materials Science, Northeastern University, China Research Interests: Inclusion engineering and microstructure-property correlations in steels High-entropy alloy design using digital tools (AI/thermodynamic modeling) In-situ characterization via confocal microscopy and multiscale analysis Recycling-oriented steel production and CO2 reduction strategies Grants/Projects (selected): SSF Strategic Mobility Grant (2023-2024): Clean steel for sustainable future VINNOVA Mobility Grant (2022-2024): Hydrogen-based metallurgy STINT Project (2022-2023): Inclusion engineering for green steel EIT RawMaterials (ENDUREIT, 2019-2021): Durable steels at intermediate temperatures Labs/Teams: Hultgren Lab (materials characterization), Digital Futures (AI-driven metallurgy), and international collaborations with Hanyang University (South Korea), IIT Bombay (India), and Tohoku University (Japan).
