Jesper Simonsen is a Professor of Participatory Design at the Department of People and Technology, Roskilde University, Denmark. He directs the Information Technology Ph.D. program and has over 30 years of experience in action research, focusing on user-centered IT design and organizational change, particularly in healthcare settings since 2004. Current research projects involve AI implementation in clinical diagnostics (CNN-based renal tumor classification), task reallocation in healthcare (e.g., medication management shifts to pharmacists), and effects-driven innovation in bio-production processes via AI. Collaborations include Region Zealand, Capital Region of Denmark, and international institutions. His research integrates participatory design, action research, and sociotechnical approaches to address challenges in healthcare IT, AI ethics, and organizational transformation. Recent work emphasizes explainable AI, post-implementation evaluation, and modular innovation frameworks. Notable projects include the Roskilde University Strategic Research Initiative ‘Designing Human Technologies’ (2012-2016) and leadership roles in the Participatory Design Conferences Advisory Board (2014-2019). Supervised PhD students include Daniel van Dijk Jacobsen, Christopher Gyldenkærne, and Christine Bech Flagstad.
Marc Torrens Arnal is an Associate Professor in the Department of Operations, Innovation and Data Sciences at ESADE Business School, Ramon Llull University. He serves as Academic Director of the Executive Master in Business Analytics and is an active researcher at ESADE D3 – Institute for Data-Driven Decisions. Education: PhD in Artificial Intelligence, École Polytechnique Fédérale de Lausanne (EPFL) Computer Science Engineering, Universitat Politècnica de Catalunya (UPC) Marc's research centers on the application of Artificial Intelligence to solve real-world business and societal challenges. He is particularly passionate about leveraging AI to enhance human decision-making, improve lives, and bridge the gap between academic research and industrial implementation. His work spans machine learning, recommender systems, data-driven marketing, cybersecurity, and ethical AI. He emphasizes practical, impactful innovation grounded in scientific rigor. The most recent articles reflect a strong trend toward applying AI in business analytics, financial technology, and cybersecurity. There is a consistent focus on personalization, decision support, and ethical considerations. His publications span top venues in AI and human-computer interaction, demonstrating a long-standing contribution to both foundational and applied research. Scientific Awards: No awards explicitly mentioned in the text. Marc has advised numerous industry leaders through his entrepreneurial ventures and academic roles. He co-founded Strands, Inc., where he led innovation for over 14 years, building a globally recognized fintech platform. Though no formal students are listed, his leadership in executive education suggests significant mentorship of professionals and entrepreneurs. He has secured substantial real-world impact through patents and commercial deployment rather than traditional research grants. Labs and Research Teams: ESADE D3 - Institute for Data-Driven Decisions
Professor Anna Rakowska leads the Department of Intellectual Capital and Quality at Maria Curie-Skłodowska University's Faculty of Economics. With over 200 publications, her research spans human resource management, organizational diversity, and managerial competencies, while pioneering studies at the intersection of artificial intelligence in management and Human-Robot Interactions (HRI). She also investigates individual competencies within Circular Economy frameworks. Department Head of Intellectual Capital and Quality Deputy Editor in Human Management Systems Active in American Academy of Management and Polish Academy of Sciences (Lublin section) Focus on organizational justice, employee well-being, and diversity management Her scholarly work reveals trends in cross-cultural management studies, legal-comparative analyses of judicial systems, and evolving competencies for sustainable economies. Notably, she explores AI ethics in workplaces and migration-induced diversity challenges. Recipient of editorial board roles in international journals Research grant leadership in employee development and innovation Keynote speaker at conferences on organizational effectiveness Current projects examine robotic integration in business environments and diversity-driven innovation strategies, while maintaining active collaborations with industry leaders and policy experts.
Robin Carpentier is a Research Fellow at the School of Computing, Macquarie University . His work focuses on Data Privacy , Information Management , and Hardware Security , particularly in developing secure personal data management systems using Trusted Execution Environments (TEE) and SGX technology. Research Interests : Secure data processing with third-party code Privacy-preserving computation frameworks Hardware-based security for databases Dimensionality challenges in text privacy Resource-constrained privacy-preserving methods Recent Publications Trends : Robin's research over the past decade has explored data leakage mitigation, TEE-optimized database operations, and privacy-preserving mechanisms for large-scale data applications. His 2024 work extends these principles to secure AI/LLM interactions and advanced text privacy techniques.
Mathias Fischer is Professor for Computer Networks at the University of Hamburg since December 2021, affiliated with the MIN Department of Informatics. He previously served as an assistant professor at Universität Hamburg (2016-2021), University Münster (2015-16), and held postdoctoral positions at the International Computer Science Institute/UC Berkeley (2014-15) and the Center for Advanced Security Research Darmstadt/TU Darmstadt (2012-14). His educational background includes a PhD in Computer Science from TU Ilmenau (2012) and a diploma in Computer Science from the same institution (2008). He also served as Head of Data Literacy Education in IT Support at the University of Hamburg's ISA Center. Professor Fischer's research spans critical areas of modern network infrastructure, with particular emphasis on IT and network security , resilient distributed systems , and network monitoring . His work addresses fundamental challenges in cybersecurity including botnet monitoring, intrusion detection, and critical infrastructure protection. His research group actively investigates P2P networks and develops innovative approaches to network security that balance functionality with privacy preservation. Analysis of his recent publications reveals a strong focus on privacy-enhancing technologies, network security protocols, and resilient distributed systems. His research trajectory shows increasing attention to practical implementations of security solutions for edge computing environments, digital twin networks, and time-sensitive networking applications. The work demonstrates sophisticated integration of cryptographic techniques with network architecture design to address emerging security challenges in distributed systems. Among his notable recognitions are the Claussen-Simon Competition for Universities (2019), the University Prize of the Claussen-Simon Foundation (2019), and an Outstanding Paper Award at ACSAC (2018). Claussen-Simon Competition for Universities (2019) University Prize of the Claussen-Simon Foundation 2019 Outstanding Paper Award at ACSAC (2018) Professor Fischer leads multiple significant research projects including SOVEREIGN (Technologically sovereign security monitoring), RESISTANT (Resilient zero-trust platform for aircraft), and Dynamic situational awareness for rescue teams. His research group comprises numerous doctoral and master's students working on cutting-edge network security challenges. Current projects focus on developing resilient data and AI platforms for crisis situations, security monitoring for critical infrastructures, and innovative home network security solutions. The Computer Networks research group at the University of Hamburg, led by Professor Fischer, maintains active collaborations with industry and academic partners. The group operates specialized laboratories focused on network security testing, intrusion detection systems, and resilient network architectures. Current research directions include QUIC protocol security, federated learning security, and privacy-preserving network analytics, with strong emphasis on practical implementations that address real-world security challenges.
Sanmi (Oluwasanmi) Koyejo is an Assistant Professor in the Department of Computer Science at Stanford University and an adjunct Associate Professor at the University of Illinois at Urbana-Champaign. He leads Stanford Trustworthy AI Research (STAIR), working to develop the principles and practice of trustworthy machine learning with applications to neuroscience and healthcare. Koyejo holds affiliations with multiple Stanford institutes including SAIL, HAI, CRFM, AIMI, AI Safety, Machine Learning Group, and Bio-X. Koyejo completed his Ph.D. at the University of Texas at Austin followed by postdoctoral research at Stanford University. His research bridges theoretical machine learning with practical healthcare applications, focusing on developing robust and fair AI systems that can be trusted in critical domains. His work spans algorithmic fairness, robust distributed learning, metric elicitation, and applications to medical imaging and neuroscience. His recent publications demonstrate a strong focus on emerging challenges in AI including emergent abilities in large language models, fairness in medical AI, federated learning, and robustness against adversarial attacks. His work has increasingly addressed real-world healthcare challenges through deep learning applications to medical imaging, particularly chest radiographs for disease detection. Scientific Awards: NSF CAREER Award 2021 Skip Ellis Early Career Award Sloan Research Fellowship Frederick E. Terman Faculty Fellow (2022) Best Paper Award from UAI Kavli Fellowship IJCAI Early Career Spotlight Koyejo actively mentors a large research group with numerous PhD students and postdocs. His research has been supported by significant grants including NSF funding for projects like 'Fair Federated Representation Learning for Breast Cancer Risk Scoring.' He serves in leadership roles including as General Co-chair for NeurIPS 2022 and President of the Black in AI organization. His STAIR research group focuses on developing trustworthy AI principles and practices, with applications to healthcare and neuroimaging. The group collaborates extensively with healthcare institutions including OSF Healthcare and participates in major initiatives like the NIH-funded MIDRC and the NSF AI research institute AIFARMS.
Sayna Rotbei is a postdoctoral researcher at the Karolinska Institutet , affiliated with the Department of Medical Epidemiology and Biostatistics and part of the Predictive Medicine – Mattias Rantalainen's Research Group . She holds a PhD in Information Technology and Electrical Engineering from the University of Naples Federico II (2024) and focuses on applying artificial intelligence to healthcare challenges. Education : PhD in Information Technology and Electrical Engineering, University of Naples Federico II (2024). Her research interests center on artificial intelligence and machine learning applications in healthcare, including clinical decision support systems , outcome prediction , and interdisciplinary data-driven solutions . She combines medical data , computational models , and public health perspectives to address real-world clinical challenges. Recent publications highlight her work on diabetes (2024), robot cybersecurity (2023), lockdown-induced psychiatric symptoms (2022), prostate surgery outcomes (2023, 2024), and early autism detection (2020, 2021). These studies span systematic reviews , predictive modeling , and smart diagnostic architectures . In teaching , she has supported undergraduate and postgraduate courses in information technology and data processing, and guided master’s students on research design and implementation.
Rick Kramer is an Assistant Professor at the Building Physics and Services unit within the Department of Built Environment at Eindhoven University of Technology (TU/e) in the Netherlands. His work focuses on advancing building automation and energy efficiency through innovative control strategies and fault detection systems for indoor environments. His educational background includes: MSc (with honors) in Building Services from Eindhoven University of Technology (2012) PhD (with honors) from Eindhoven University of Technology with dissertation on 'Energy efficient indoor climate control strategies for museums respecting collection preservation and thermal comfort of visitors' (2017) Rick Kramer's research centers on smart control of indoor environments and fault detection in HVAC systems. His work combines data-driven techniques with expert knowledge to develop algorithms that optimize energy efficiency while maintaining human wellbeing in offices, preserving collections in museums, and ensuring proper conditions in cleanrooms. He collaborates extensively with both large companies and SMEs on R&D projects aimed at accelerating market uptake of innovations to address societal challenges. His specific expertise spans low delta-T syndrome in cooling systems, cooling coil design and performance, automatic fault detection and diagnosis (AFDD), and the impact of indoor environmental conditions on human comfort and performance. His recent publications demonstrate a strong focus on cooling system optimization, particularly addressing low delta-T syndrome through advanced modeling techniques and practical solutions. His work bridges theoretical research with practical implementation in building systems, contributing significantly to energy conservation in the built environment. Rick has been recognized for his contributions to the field with: TVVL's BJ Max prize for his publications on the museum environment (2019) Best PhD dissertation award from the Department of Built Environment (2017) As an active member of the academic community, Rick serves as a reviewer for 20+ academic journals and has participated in several scientific committees for international conferences. Through his company DYSECO B.V., where he serves as co-founder, shareholder, and director, he bridges the gap between academic research and practical implementation in the building industry. Rick leads research within the EAISI (Eindhoven Artificial Intelligence Systems Institute) and EIRES (Energy Innovation and Research in the Built Environment) groups, focusing on applying AI and data science to building systems. His work contributes significantly to addressing sustainability challenges in the built environment through innovative technological solutions.
Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.
Gerald C. Kane is a Professor and the C. Herman and Mary Virginia Terry Distinguished Chair in Business Administration at the Terry College of Business, University of Georgia. He is a leading scholar in digital transformation, artificial intelligence ethics, and social media for knowledge management, with over 100 publications in top-tier journals including MIS Quarterly and Management Science. His educational background includes: PhD in Information Systems, Emory University, Goizueta Business School (2006) MBA in Computer Information Systems, Georgia State University, Robinson College of Business (2002) M. Div. in Theology, Emory University (1998) BA in Humanities, Furman University (1994) Professor Kane's research focuses on the social and ethical implications of artificial intelligence and machine learning, the success factors in digital transformation of legacy companies, and how organizations use digital tools to innovate through disruption (e.g., during the COVID-19 pandemic). He also explores social media for knowledge management across organizational boundaries and information systems in healthcare. His work provides critical insights for businesses navigating the digital era. His recent publications (2020-2025) demonstrate intense focus on AI ethics—particularly fairness and bias in machine learning algorithms—and the transformative impact of digital tools on organizational strategy and workplace design. Kane's research addresses digital strategy formulation challenges and post-pandemic workplace reinvention, reflecting his commitment to solving real-world organizational problems through technology-driven solutions. Professor Kane's contributions have been recognized with numerous prestigious awards: Davis-Dixon Impact Award, MIS Quarterly (2024) Axiom Business Book Awards Gold Medal (2021) Carroll School Coughlin Distinguished Teaching Award (2018) National Science Foundation CAREER Award ($500,000) (2009-2016) McKiernan Distinguished Fellow ($30,000), Boston College (2014-2016) Runner-up, Best Published Paper, Academy of Management (2015) U.S. Department of Defense Small Business Technology Transfer Award ($100,000) (2012) Professor Kane has secured significant research funding including a National Science Foundation CAREER Award and U.S. Department of Defense grant supporting his work on social media and knowledge management. His influential books 'The Technology Fallacy' and 'The Transformation Myth' have been translated into multiple languages and provide practical frameworks for digital transformation. While specific advisees are not documented, his role as former Senior Editor at MIS Quarterly and extensive publication record highlight his leadership in shaping information systems research.
Magnus Strand serves as Senior Lecturer in Civil Law at the Department of Law, Uppsala University (2025-present) and Associate researcher at the Department of Business Administration (2025-present). Previously, he was Research leader in commercial law (2021-2025), Member of the Education Committee of the Faculty of Social Sciences (2020-2025), and Director of Studies in Commercial Law (2016-2020). He also held a Part-time Professor position at the European University Institute in Florence (2019-2020). Doctor of Laws, Uppsala University (2015) Bachelor of Laws, Lund University (2006) Bachelor of Philosophy, Uppsala University (2006) Associate lawyer at Lindahl law firm (2006-2008) Professor Strand's research focuses on the complex interaction between EU law and national legal systems, with particular expertise in competition law, damages law, and the regulatory challenges posed by artificial intelligence and digital markets. His scholarly work has evolved from traditional EU competition law topics toward the emerging challenges of AI governance. Recent publications demonstrate his ability to identify and engage with cutting-edge legal challenges as they emerge in the digital economy, particularly examining how national legal frameworks interact with EU regulations in commercial contexts. His publication record reveals a clear trajectory from foundational work on competition damages (2010-2017) toward contemporary issues in AI regulation (2022-2025). The most recent articles show increasing focus on algorithmic trading, AI-based regulatory technology, and adaptation of damage law to AI systems. This evolution demonstrates his scholarly agility in addressing rapidly developing legal frontiers while maintaining expertise in core EU law principles. Editor of the European Law Journal (ERT) Member of steering group for Swedish Network for European Law Research (2012-2015) Coordinator for Uppsala University's European Law Moot Court Competition (2008-2012) As an educator and administrator, Strand has significantly contributed to legal education through curriculum development and interdisciplinary approaches. His research leadership extends to multiple funded projects examining regulatory governance in digital markets and AI technology, particularly within financial sectors, demonstrating his commitment to bridging theoretical scholarship with practical regulatory challenges. Professor Strand leads several major research initiatives including "Konkurrenstvister bortom harmoniseringen" (financed by Konkurrensverket), "AI Design Futures," and "AI-based RegTech" (both financed by The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society). These projects position him at the forefront of legal scholarship addressing the intersection of competition law, digital markets, and AI governance.
Thilo Stadelmann is the Founding Director of the Centre for Artificial Intelligence at the Zurich University of Applied Sciences (ZHAW) . A computer scientist by training, he earned his Doctor of Science degree from Marburg University, Germany, and has held engineering and leadership roles in the automotive industry before transitioning to academia. His research interests lie at the intersection of representation learning and the societal implications of artificial intelligence . He is particularly focused on understanding how AI systems can be designed to enhance human capabilities while addressing ethical concerns and societal challenges. Stadelmann is a prolific speaker and educator, delivering TEDx talks and lectures on topics such as "How Not to Fear AI" , "AI vs Human: Understanding the Fundamental Differences" , and "Decoding AI Fear: The Philosophy Behind It" . His work emphasizes the importance of demystifying AI and fostering a balanced perspective on its potential and limitations. His recent publications span a wide range of AI applications, from safety-critical network infrastructures and medical imaging to industrial process control and AI governance . Notable works include studies on AI risk assessment for public policy, document recognition, and the societal impact of AI technologies. Beyond his academic role, Stadelmann is actively involved in the digital ecosystem as a (co-)founder and senior leader in several organizations, bridging the gap between research and practical implementation in the AI space.
Tanvir Arafin serves as an Assistant Professor in the Department of Cyber Security Engineering at George Mason University, where his research focuses on hardware security and trust mechanisms for emerging computing platforms. With publications in premier venues including IEEE Transactions on Very Large Scale Integration Systems, IEEE Transactions on Computers, and ACM International Conference on Computer-Aided Design, he addresses critical security challenges in next-generation systems through rigorous hardware-software co-design approaches. His research portfolio spans Hardware Security, Trusted Computing, and IoT Security, with specialized expertise in Side-Channel Attacks and Secure Hardware Design. Dr. Arafin investigates electromagnetic side-channel vulnerabilities in O-RAN networks, develops countermeasures for autonomous vehicle cybersecurity, and pioneers RRAM-based security solutions for memory-constrained devices. His work bridges theoretical security models with practical implementations, emphasizing real-world applicability in edge computing environments and autonomous navigation systems. Current projects explore machine learning integration for anomaly detection in connected vehicles and secure acceleration of cryptographic operations. Analysis of Dr. Arafin's 2022-2025 publications reveals strategic focus areas: electromagnetic fingerprinting for radio units in O-RAN (2025), spatial acceleration of Kolmogorov-Arnold Networks (2025), and NTT-based cryptography accelerators (2024). His research demonstrates consistent innovation in securing autonomous navigation systems and edge devices, with emerging work on in-memory computing architectures using resistive memory technologies. Key trends include hardware-centric defense against model inversion attacks, voltage overscaling for lightweight authentication, and robust multi-robot coordination in dynamic environments. Scientific Awards: No scientific awards, fellowships, or medals were documented in the source materials. Dr. Arafin leads significant collaborative research, including the NSF CISE-MSI grant (DP: CNS) for edge-based robust multi-robot systems. His educational initiatives feature Capture-the-Flag competitions targeting underrepresented students in cybersecurity. Current grant activities emphasize practical security solutions for autonomous navigation, multi-robot coordination, and IoT edge devices, with demonstrated focus on translating research into deployable countermeasures for real-world threats in dynamic operational environments.
Thijs van Ede serves as an Assistant Professor in the Semantics, Cybersecurity and Services research group at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science. His academic work centers on security automation through machine learning and AI integration, with specialized expertise in large language models for intrusion detection systems and anomaly analysis in rapidly evolving network environments. His research program bridges theoretical AI advancements with practical cybersecurity applications, focusing on contextual security analysis using deep neural networks and Natural Language Processing techniques for cyber threat intelligence sharing. This work manifests in open-source tool development emphasizing collaborative science, including frameworks for encrypted traffic analysis and security event log interpretation. Recent publications demonstrate consistent innovation in applying deep learning to network security challenges, particularly through the DeepCASE (2022) and FlowPrint (2020) frameworks that address anomaly detection in security logs and mobile application fingerprinting respectively. These works establish patterns in leveraging sequential data analysis for real-time threat identification. Through active mentorship of the Twente Hacking Squad student team, he cultivates next-generation cybersecurity talent via Capture The Flag competitions while maintaining research infrastructure through open-source security tools. His academic service includes developing accessible research implementations that bridge theoretical concepts and operational security solutions. As a core member of the Semantics, Cybersecurity and Services research group, he contributes to the University of Twente's Digital Society Institute initiatives, focusing on deployable AI security systems that operate effectively in dynamic enterprise environments. His work maintains strong connections between academic research and practical security operations through toolchain development and student engagement.
Christine Moser is a Full Professor of Sustainable Organizing at the Vrije Universiteit Amsterdam's School of Business and Economics (Management and Organisation department). Her research focuses on technology's role in social interaction, corporate social responsibility (CSR), and knowledge flows within social networks. She holds editorial roles at Academy of Management Learning and Education and Organization Studies , and chairs the European Group of Organizational Studies (EGOS). Education: PhD in 'Not a piece of cake: What makes online communities work?' (Vrije Universiteit Amsterdam, 2013) Master's in Culture, Organization & Management (cum laude, Vrije Universiteit Amsterdam, 2006) Research Interests: Moser explores how technology shapes organizational practices, with emphasis on online communities, social media governance, and sustainability challenges like food waste. Her work bridges sociology, psychology, and management theory, addressing ethical implications of algorithmic decision-making and AI. Awards: Best Article Award (Academy of Management Learning & Education, 2023) Emerald Literati Award (2018) Wilhelmina Drucker Award (2017) Projects & Grants: She leads MOVUS (2024–2026), redesigning digital care systems for elderly populations, and collaborates on strengthening ICT capacity in Ugandan universities (2023–2026). Her research is funded by the ISR Grant (2018). Labs/Teams: Central to her work is the EGOS organizing team (2021 colloquium coordinator) and interdisciplinary collaborations in sustainability and technology ethics.
