Thomas Mayer is a Doctoral Researcher affiliated with the Professorship for Information Systems and Digital Innovation at the University of Hamburg Business School. His research focuses on Digital Transformations in industrial organizations, Scaled Agile Transformations, Enterprise Architecture Management, and Generative Artificial Intelligence (GenAI) Development. He holds an office at Von-Melle-Park 5, Room 3091, and can be contacted via thomas.mayer@uni-hamburg.de. His recent publications explore financial management challenges in agile transformations within automotive manufacturing and the application of GenAI in industrial contexts. Mayer collaborates with Prof. Dr. Recker and other researchers on case studies involving German automotive firms. His work bridges theoretical frameworks with practical implementation challenges in digital innovation and organizational change.
Ohad Fried is an Associate Professor of Computer Science at Reichman University. He was previously a postdoctoral research scholar at Stanford University under Prof. Maneesh Agrawala and completed his PhD with Prof. Adam Finkelstein as part of the Princeton Graphics group. He holds an M.Sc. in Computer Science and a B.Sc. in Computational Biology from The Hebrew University. His research lies at the intersection of computer graphics, computer vision, and Generative AI , focusing on tools, algorithms, and paradigms for photo and video editing and synthesis . His work has been widely recognized in top conferences including CVPR, SIGGRAPH, and ECCV, with recent contributions to tiled diffusion models, expressive 4D facial motion generation, and synthetic image detection. Ohad has received numerous awards, including the Israel Science Foundation personal research grant (2021) , the Outstanding faculty researcher at Reichman University (2022) , and the Siebel Scholar award (2017) . He has advised multiple students in research projects, and his work is covered by media outlets like Wired , The Washington Post , and CNN . Teaching roles include courses at Reichman University such as "GenAI for Games & Entertainment" and "Synthetic Media Detection", and at Stanford University "Computational Video Manipulation". Key Research Themes: Neural Rendering Diffusion Models 3D Facial Animation Image/Video Editing Media Forensics Scientific Awards: ISF Personal Grant (2021) Siebel Scholar (2017) Google PhD Fellowship (2014-2016) Gordon Y.S. Wu Fellowship (2012-2013) Excellence Scholarships
Mike Perkins is an Associate Professor and Head of the Centre for Research & Innovation at the British University Vietnam (BUV). He holds a PhD in Management from the University of York, UK, with research on performance management in local police service delivery. His current research focuses on generative AI (GenAI) in education, academic integrity, and performance management. Education: PhD in Management (University of York, UK, 2013), Senior Fellow of Higher Education Academy (2019) Research Interests: GenAI in education, AI ethics, academic integrity, and public sector management. His work bridges technology, education, and academic ethics, with a focus on AI assessment tools and synthetic media challenges. Scientific Awards: St Andrew’s Global Research Fellow (2025–2026) Visiting Scholar at Werklund School of Education, University of Calgary (2026) 2024 Paper of the Year – Journal of University Teaching and Learning Practice Prof. Tracey Bretag Academic Integrity Award (2024 Honored, 2025 Shortlisted) BUV President's Research Award (2023) BUV President's Teaching Award (2019) Grants: Led the International Science Partnership Fund (£80,000, 2024–2026) for GenAI integration in Vietnamese higher education. Co-led Going Global Partnerships (£80,000, 2023–2025) for digital transformation in Vietnamese universities.
Dana-Kristin Mah is a Junior Professor for Digital Teaching and Learning at Leuphana University of Lüneburg. Her research focuses on educational technology, artificial intelligence in education, and digital transformation in higher education. She explores topics such as AI literacy, open educational resources (OER), learning analytics, and instructional design. Research Areas: Educational Technology, AI in Education, Digital Transformation, Learning Analytics, OER Her recent publications highlight trends in AI-driven pedagogy, digital mindset development for educators, and the integration of generative AI with learning analytics. She has received fellowships from Forschungskolleg KI-Kompetenzen and Zia – Visible Women in Science. Projects: Artificial Intelligence in Education (Germany/Denmark), GenAI-Natives (teacher training for generative AI), and Digital-Didactic Potentials in Transformation. Her work bridges technology and pedagogy, emphasizing practical applications for enhancing teaching and learning experiences.
Michael Harr is a doctoral researcher and research assistant at the University of Duisburg-Essen, affiliated with the Faculty of Computer Science and the Chair of Business Informatics and Integrated Information Systems. His work focuses on artificial intelligence, digital transformation of HR management, enterprise systems, new work arrangements, and digital communication. He has published extensively on these topics in leading journals and conferences. Education: M.Sc. in Business Information Systems (2020-2023), University of Duisburg-Essen B.Sc. in Business Information Systems (2016-2020), University of Duisburg-Essen His research explores the intersection of AI and human-centric systems, including studies on retail service robots, intelligent HRIS, generative AI in MOOCs, and user annoyances in voice assistants. Recent publications analyze digital communication trends and digitalization challenges in the construction sector. Publications: Harr has contributed to key areas such as retail automation, HRIS optimization, and AI-driven e-learning, with a focus on practical applications and theoretical frameworks. Supervised Theses: Exploring ChatGPT for MOOCs AI in Knowledge Management Technostress and Quiet Quitting Taxonomy of AI Recruitment Tools Talent Recruitment on Social Networks Labs and Teams: Harr is involved in the Retail Artificial Intelligence Lab (retAIL) and SAP Innovation Lab, contributing to projects on digital transformation and enterprise systems.
Dr. rer. nat. Agnes Grünerbl is a researcher at the Embedded Intelligence group within the German Research Center for Artificial Intelligence (DFKI), focusing on Human-Computer Interaction (HCI) and artificial intelligence applications. She contributes to interdisciplinary projects like STELEC (Sustainable Textile Electronics) funded by the European Innovation Council (EIC). Her work explores the integration of Generative AI (GenAI) and "Large Whatever Models" in HCI methodologies, as well as sensor-based state detection for mental health applications. Recent research includes participation in key conferences such as CHI-2024 , UbiComp-2024 , and MobileHCI-2024 , where she presented studies on AI-driven interface design, mental care standards, and mobile cognition-altering technologies. Her projects emphasize sustainability and human-centered design in emerging computing paradigms. Agnes Grünerbl is affiliated with the Embedded Intelligence lab, which develops innovative wearable and textile-based electronic systems. Her collaborations span institutions like the University of Kaiserslautern and international researchers, reflecting her focus on interdisciplinary approaches to computational challenges.
Muhammad Hamad Alizai is an Associate Professor in the Department of Computer Science at the School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Pakistan. His research spans the Internet of Things (IoT), Cyber-Physical Systems, Embedded AI, and intermittent computing, with a focus on sustainable and accessible technologies for developing regions. His research interests include energy harvesting, batteryless computing, GenAI for IoT, wireless sensor networks, and distributed systems . He explores how generative AI can democratize IoT access in low- and middle-income countries and addresses societal challenges through computational solutions. His work is supported by grants from HEC, LUMS, DAAD, and NCBC. Recent publications reveal a strong trend in intermittent computing, energy-efficient IoT, and AI-driven system optimization , with high-impact papers in ACM SenSys, IPSN, BuildSys, and CACM. His team develops innovative systems like CheckMate, Glitch in Time, and Guardian Angel, tackling reliability, security, and accessibility in transiently powered devices. Scientific recognitions include: Best Paper Candidate at ACM SenSys 2019 Audience Choice Award at ACM BuildSys 2017 Best Abstract Award at ACM SenSys 2010 He has advised numerous graduate students, including PhDs like Saad Ahmed and Samar Abbas, and leads pedagogical innovation as head of the LUMS Learning Institute , promoting teaching excellence and AI integration in education. He has served on technical committees for ACM CoNEXT, IPSN, MobiSys, and BuildSys, and organized key workshops in transient computing. His lab focuses on building privacy-preserving, energy-neutral, and AI-augmented embedded systems , particularly for applications in water, energy, and transportation in developing regions.
Imke Grashoff is a Researcher at the University of Hamburg Business School , affiliated with the Professorship for Information Systems and Digital Innovation. Her work focuses on artificial intelligence (AI), digital innovation, and technology implementation within business contexts. She collaborates closely with industry partners like GuideCom and German automotive manufacturers to explore practical applications of AI solutions. Her research interests include AI system design, GenAI development challenges, and the strategic adoption of low-code platforms. Grashoff’s recent publications analyze case studies in telecom and automotive sectors, emphasizing real-world implementation strategies and organizational challenges. She is part of Prof. Dr. Recker’s research group, contributing to interdisciplinary projects at the intersection of business administration and information systems. Grashoff holds a doctoral researcher position and has presented at major conferences such as the International Conference on Information Systems (ICIS) and ECIS. Her work bridges theoretical research with actionable insights for enterprises adopting emerging technologies.
Yves T. Staudenmaier is a PhD Candidate and Academic Staff Member at the University of Mannheim's School of Business Informatics and Mathematics, affiliated with the Chair of Practical Computer Science IV (Dependable Systems Engineering led by Prof. Dr. Armknecht) and InES (led by Dr. Christian Bartelt). His research focuses on physical signal processing, AI-driven security solutions, GenAI applications, wireless networks, and smart home security systems. Education: M.Sc. Business Informatics (2021–2023, University of Mannheim); B.Sc. Business Informatics (2017–2020, DHBW Mannheim). Professional experience includes working as an IT Systems Engineer at SV Informatik GmbH (2017–2023). Current projects include the Physical Guards initiative exploring physical-layer security for smart homes using AI. He teaches the European Master Team Project at InES focused on this project, which will launch soon. Research interests emphasize interdisciplinary approaches combining AI with cybersecurity, with open thesis opportunities in smart home security domains.
Dr. Fenja Kuchenbuch is a Junior Professor for Digital Teaching and Learning at Leuphana University Lüneburg. She specializes in educational technology, teacher professionalization, and generative AI applications in education. Her current research focuses on the GenAI-Natives project, where she designs teaching materials and analyzes interview data on AI's impact in classrooms. Education: Ph.D. in Education, Leuphana University Lüneburg (2020-2025) Master of Education in History, English & Pedagogy, European University of Flensburg (2017-2019) Bachelor of Arts in Education, Europa-Universität Flensburg (2014-2017) Research interests center on competency-based teaching frameworks, digital learning tools, and generative AI integration in teacher training programs. Her work emphasizes qualitative studies of teaching perception and task-oriented pedagogy. Publications focus on teacher professionalization, with her 2025 monograph examining competency development in English language instruction. Conference presentations consistently address AI's transformative role in education and task-oriented teaching methodologies. Active in multiple research projects: GenAI-Natives (2025-2027): Developing AI training resources for educators ZZL Network 2.0 (2019-2023): Theory-practice integration in teacher education
Florian Holldack serves as a Researcher at the University of Duisburg-Essen's Faculty of Computer Science within the Business Information Systems and Software Technology department under Prof. Dr. Stefan Eicker. His work focuses on cutting-edge intersections of artificial intelligence and practical business applications. His primary research domains include Generative AI in Software Engineering and Virtual Reality Training Systems , with significant contributions to understanding AI adoption frameworks and industrial VR implementations. Holldack actively supervises bachelor theses exploring multi-agent systems, healthcare diagnostics, and human-AI collaboration. His recent publications reveal strong trends in applying sociotechnical analysis to GenAI integration challenges and developing evidence-based design principles for industrial VR training. Key themes include productivity optimization, barrier identification in AI adoption, and cognitive aspects of immersive learning environments. Supervises 4 bachelor theses annually in Business Information Systems Collaborates with international researchers on GenAI and VR projects Integrates Design Science Research methodologies in healthcare diagnostics Holldack maintains active research partnerships through the paluno institute, focusing on practical implementations of theoretical frameworks in real-world industrial and medical contexts.
Dr. Markus Kowarschik is a researcher affiliated with the Chair of Computer Science Applications in Medicine at Technical University of Munich under Prof. Nassir Navab. His work focuses on interventional imaging, blood flow quantification, and tomographic reconstruction. He contributes to labs like DHM (Deutsches Herzzentrum München), NARVIS, and IFL, advancing medical imaging and AI applications in healthcare. His teaching includes courses on medical procedures, robotics, and deep learning in medical contexts. Recent research emphasizes AI-driven solutions for endovascular procedures, motion compensation in imaging, and 3D pose estimation. His research interests span medical image analysis, computer vision, and generative models applied to surgical data science. Key projects involve developing datasets for benchmarking, improving X-ray imaging systems, and integrating simulation for medical training. He has no listed awards but maintains an active publication record in top-tier journals and conferences. Labs and collaborations include the NARVIS Lab (navigation and robotics), DHM for cardiac imaging, and GenAI initiatives exploring generative models. His work bridges clinical needs with computational methods, addressing challenges in radiation dosimetry, robotic control systems, and real-time imaging analysis.
Nikos Askitas serves as Coordinator of Data and Technology at the Institute of Labor Economics (IZA) in Bonn, Germany, where he leads both the Research Data Center (IDSC) and ICT unit since joining in 2000. His dual role bridges technical infrastructure management and cutting-edge research in labor economics and social science. His research spans causal machine learning , epidemic disease modeling , big data analytics , and behavioral macroeconomics , with notable contributions to forecasting methodologies and web-based data applications. He develops novel approaches in opinion dynamics, game theory, and adaptive systems while addressing real-world challenges like pandemic response and technology-labor interactions. Recent publications reveal a strong trend toward AI-driven economic analysis , particularly examining generative AI's impact on scientific communication and labor markets. His work consistently integrates web data and real-time indicators with traditional economic modeling, emphasizing practical policy applications in consumption tracking, referendum forecasting, and mobility pattern analysis. His scientific recognition includes: CESifo Research Fellow in Economics of Digitisation Academic Editor for PLoS ONE (Economics section) As infrastructure leader, he oversees IZA's research data ecosystem and technological operations, enabling large-scale empirical studies while advancing methodological frontiers through hands-on machine learning pedagogy for social scientists. His current projects focus on GenAI implications, nowcasting techniques, and causal inference frameworks.
Jonas Witte is a PhD candidate and Research Associate at the Technical University of Munich since November 2024, focusing on the application of Generative AI in scientific research. He also serves as a Researcher at Fraunhofer-Gesellschaft since December 2024. Education : B.Sc. and M.Sc. in Information Systems from TU Darmstadt Professional Experience : Internships at PwC, Accenture, and zeb consulting Research Interests Use of Generative AI (GenAI) by researchers Identification of use cases and technical implementation (RAG, fine-tuning) Model comparison for understanding potentials/limitations Data security and protection challenges
Jan Laufer is a Research Associate at the Chair of Business Information Systems and Software Engineering within the Faculty of Computer Science at the University of Duisburg-Essen. He has been working in this position since October 2024, following previous research positions at the Chair of Software Systems Engineering at the same university from October 2023 to September 2024 (full-time) and January 2021 to September 2023 (part-time). His research focuses on Generative AI (GenAI) with special emphasis on real-world applications, physical interaction of AI systems with humans and environments (GenAI Embodiment), and Explainable AI. His earlier work centered on adaptive systems and data protection. He has contributed to significant projects including Dynabic (2024), FogProtect (2020-2022), and RestAssured (2018-2019). Laufer's publication record shows a clear evolution from data protection and adaptive systems toward GenAI and explainability. His recent work examines embodied generative AI, tax applications of AI assistants, and user studies on explainable reinforcement learning. His research bridges theoretical AI concepts with practical applications across multiple domains including legal technology, disaster response, healthcare, and security. Scientific Awards: Germany Scholarship (UDE-Stipendium) summer semester 2023 Germany Scholarship (UDE-Stipendium) winter semester 2020/2021 - summer semester 2021 (sponsored by Dr. Heinz-Horst Deichmann Foundation) Laufer has supervised numerous bachelor theses focusing on embodied generative AI applications across various domains including disaster response, water rescue, building security, and therapeutic interventions. His teaching activities include supervision of seminar papers on Generative AI applications and collaboration. He also serves as a member of the DLRG national squad since 2018.
