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Fokeltje Cnossen is an Associate Professor at the University of Groningen with dual appointments in the Faculty of Science and Engineering (Department of Artificial Intelligence) and the Faculty of Medical Sciences (UMCG) through the Lifelong Learning, Education & Assessment Research Network (LEARN). Her work integrates Cognitive Psychology, Human Factors, and Artificial Intelligence to enhance patient safety, medical technology design, and clinical education. Her research prioritizes optimizing patient safety through cognitive engineering of medical systems, with focus areas including trustworthy AI implementation , stress/workload impact on clinical performance , and medical skill acquisition pedagogy . Key specialties span mental fatigue mitigation, usability evaluation, and autonomy in healthcare systems, contributing directly to UN Sustainable Development Goals for health and wellbeing. Recent publications reveal strong interdisciplinary convergence: AI-driven surgical planning tools (e.g., 3D fracture reduction visualization), physiological workload monitoring in cardiac surgery, and policy analyses of physician wellness frameworks. Her work bridges computer science, surgical practice, and healthcare administration with consistent patient-safety outcomes. Scientific Awards: Best Teacher Award - Faculty of Mathematics and Natural Sciences (2010) Dr. Cnossen supervises graduate research through the LEARN network and maintains active professional engagement, including keynote presentations at the Max Planck Institute of Human Cognition & Brain Sciences and Dutch Vascular Courses. Her team focuses on translating cognitive science into clinical safety improvements through the LEARN research consortium.

• Patient Safety
• Cognitive Psychology
• Human Factors
• +5 more

Xavier de Carné de Carnavalet is an Assistant Professor at Radboud University's Digital Security group within the Faculty of Science. His research focuses on network security, privacy, web security, and applications of machine learning in cybersecurity. He holds a PhD from Concordia University (2019) and completed postdoctoral work at Carleton University's CCSL lab. Research Interests: Network Security & Privacy Passwords & Authentication Systems Embedded/Firmware Security Machine Learning for Cybersecurity Home Router Vulnerabilities TLS Interception Mechanisms Publications highlight trends in analyzing security configurations (home routers), detecting vulnerabilities (command injection in firmware), and evaluating TLS interception practices. His work often bridges technical security analysis with human factors influencing secure practices. He has contributed to major conferences like CHI, NDSS, and USENIX Security. Notable projects include analyzing password strength meters and verifying TrueCrypt's build integrity. Current research includes database breach analysis and cryptographic software hardening. Labs/Teams: Active contributor to the Digital Security group at Radboud University, collaborating with institutions like HK PolyU and Concordia's Madiba Security Research Group.

• Network Security
• Privacy
• Web Security
• +4 more

Victoria Bruno is a University Researcher in the Department of Industrial Design at Eindhoven University of Technology (TU/e), specializing in human-centered AI applications for medical imaging. Her work bridges industrial design principles with clinical healthcare innovation, focusing on user trust in AI-assisted diagnostic systems. Her research spans Medical Imaging , Artificial Intelligence in Healthcare , and Human-Computer Interaction , with particular emphasis on lung cancer detection workflows. She investigates how design interventions like expectation management and model transparency influence radiologists' adoption of AI tools in computed tomography analysis, addressing critical human factors in medical AI deployment. Her 2024 publication in JMIR AI demonstrates how transparent AI interfaces significantly improve radiologists' trust and utilization patterns for lung nodule assessment, revealing nuanced interactions between system design and clinical decision-making. This work establishes foundational principles for designing trustworthy AI in high-stakes medical environments. Bruno actively contributes to the MEDical Engineering, Innovations and Applications project (2022-2027), a third-tier funded initiative involving cross-institutional collaboration with the E/MTIC Oncology Collaborative Group. Her role encompasses human factors research within a multidisciplinary team of medical engineers, oncologists, and AI specialists focused on translating engineering innovations into clinical oncology applications.

• Medical Imaging
• Artificial Intelligence in Healthcare
• Lung Cancer Detection
• +3 more

Dr. B.A. Kamphorst is a researcher in the Department of Media and Culture Studies at Utrecht University's Faculty of Humanities, where he is affiliated with the Media and Performance Studies group and the Institute for Cultural Inquiry. His work bridges philosophy, technology, and human behavior with a focus on ethical implications of digital systems. Faculty of Humanities, Utrecht University Department of Media and Culture Studies Media and Performance Studies research group Institute for Cultural Inquiry Dr. Kamphorst's research focuses on the intersection of philosophy of technology, ethics, and human-computer interaction. His expertise spans digital ethics, particularly concerning autonomy-respectful e-coaching systems, governance of digital society, and human-centered artificial intelligence. His work examines how technology affects human agency, decision-making, and behavioral patterns, with specific attention to bedtime procrastination and healthy lifestyle interventions. His publication record since 2009 demonstrates a consistent focus on ethical dimensions of technology, particularly examining how digital systems can support or undermine human autonomy. His most recent work explores hybrid intelligence applications for diabetes management and the voluntariness of public health apps, building on his foundational doctoral research on autonomy-respectful e-coaching systems completed in 2020. Editor for Philosophy & Technology journal Editor for Journal of Responsible Technology Editor for AI and Ethics journal Member of programme committee for International DEDA Seminar Member of programme committee for Procrastination Research Conference Dr. Kamphorst actively engages with the academic community through conference participation, invited talks, and editorial work. His research has practical implications for designing ethical AI systems that respect human autonomy while effectively supporting behavior change in health contexts. His multidisciplinary approach combines insights from philosophy, psychology, and computer science to address pressing challenges in the digital society.

• Philosophy of Technology
• Ethics
• E-Health
• +4 more

Yingqian Zhang is an Associate Professor in the Information Systems group at the Industrial Engineering and Innovation Sciences department of Eindhoven University of Technology (TU/e). She is affiliated with the Eindhoven Artificial Intelligence Systems Institute (EAISI), specifically with the EAISI High Tech Systems and EAISI Foundational groups. Her research focuses on applying Artificial Intelligence to solve complex decision-making problems across various domains including logistics, transportation, manufacturing, and e-commerce. Dr. Zhang received her PhD in Computer Science from the University of Manchester, UK. Prior to joining TU/e, she served as an Assistant Professor in the Econometrics Institute at Erasmus University Rotterdam and as a postdoc researcher in the Algorithmics group at TU Delft. She was also a visiting professor at the Institute for Advanced Computer Studies at University of Maryland, College Park, USA. Her research expertise lies at the intersection of Artificial Intelligence and optimization, with particular focus on machine learning, deep reinforcement learning, and trustworthy data-driven optimization. Dr. Zhang develops socially aware algorithms that can optimize decisions in data-rich environments. Her work bridges the gap between theoretical AI advancements and practical applications in industrial settings, addressing real-world challenges through innovative algorithmic solutions. She is particularly interested in how AI can support human decision-making while maintaining transparency and trustworthiness. Dr. Zhang's recent publications reveal a strong trend toward applying graph neural networks and reinforcement learning to complex scheduling and optimization problems. Her work demonstrates increasing sophistication in handling stochastic elements in decision-making processes, with applications spanning healthcare diagnostics, logistics, transportation, and manufacturing. She has made significant contributions to the field of neural combinatorial optimization, particularly for job shop scheduling problems and vehicle routing. Dr. Zhang has received several prestigious awards recognizing her contributions to the field: Winner of the MLVRP2023 GECCO competition (2023) Best Paper Award from Omega-International Journal of Management Science (2017) Best Industrial Paper Award (2020) Best Student Paper Award (2019) Best Student Paper Award of ICAART 2022 (2022) As a dedicated mentor, Dr. Zhang supervises numerous PhD students including Mohsen Abbaspour Onari, Abdo Abouelrous, Luca Begnardi, Xia Jiang, Chengpeng Hu, Minshuo Li, Robbert Reijnen, Jesse van Remmerden, Bart von Meijenfeldt, Ya Song, and Igor Smit. Her research is supported by various grants, including the LEO (Learning and Explaining Optimization) project co-funded by Holland High Tech | TKI HSTM via the PPP allowance scheme for public-private partnerships. Dr. Zhang actively contributes to the academic community as the Chair of the Benelux Association for Artificial Intelligence (BNVKI) and as a member of the Technical Board for the European Big Data Value Association (BDVA). She serves as an associate editor for the "Annals of Mathematics and Artificial Intelligence" journal and participates in the technical Program Committee for major AI conferences such as IJCAI, AAAI, AAMAS, and ECAI. She is also on the executive committee of the Data Science meets Optimisation (DSO) working group of EURO to promote collaboration between AI and Operations Research communities.

• Artificial Intelligence
• Machine Learning
• Deep Reinforcement Learning
• +7 more

Hinda Haned serves as Senior Lead Data Analytics at Janssen Biologics (Leiden, The Netherlands) while holding an endowed professorship in data science at the University of Amsterdam. Her dual-industry-academia role bridges practical biologics process optimization with cutting-edge AI research. Her research centers on responsible AI methods , developing frameworks for ethical, transparent, and accountable artificial intelligence systems. This work directly addresses critical challenges in industrial AI deployment, particularly within biologics manufacturing where algorithmic reliability impacts product quality and patient safety. Her methodology integrates technical rigor with ethical considerations across the AI lifecycle. At the University of Amsterdam, she leads a dedicated research team advancing trustworthy machine learning applications. Their collaborative efforts focus on translating theoretical AI governance principles into implementable industrial solutions, creating tangible impact at the intersection of data science and biopharmaceutical production.

• Artificial Intelligence
• Responsible AI
• Data Science
• +3 more

Carles Sierra serves as Research Professor and Director at the Artificial Intelligence Research Institute (IIIA) of the Spanish National Research Council (CSIC), concurrently holding the presidency of EurAI and an Adjunct Professorship at Western Sydney University. He obtained his PhD in Computer Science from the Technical University of Barcelona (UPC) in 1989, with visiting research appointments at Queen Mary University of London (1996-1997) and University of Technology Sydney (2004-2012). Sierra's research pioneered foundational work in Multiagent Systems, specifically developing frameworks for negotiation, argumentation-based protocols, computational trust mechanisms, team formation algorithms, and electronic institutions. His current investigations focus on AI-driven educational tools and socially impactful AI applications, reflecting an evolution toward human-centered technology. His publication record exceeds 300 scientific contributions spanning theoretical frameworks to applied implementations, demonstrating sustained innovation across three decades in artificial intelligence research. EurAI Fellow Sierra has significantly shaped the AI community through leadership roles including AAMAS General Chair (2009), Journal of Autonomous Agents and Multiagent Systems Editor-in-Chief (2014-2019), and IJCAI Program Chair (2017), while evaluating numerous EU research proposals. As Director of IIIA-CSIC, he oversees one of Europe's premier AI research institutes, fostering interdisciplinary collaboration on emerging challenges in trustworthy and socially beneficial artificial intelligence.

• Multiagent Systems
• Negotiation
• Argumentation
• +6 more