Miguel Ángel Sotelo Vázquez is a full Professor at the University of Alcalá, leading the INVETT Research Group (Intelligent Vehicles and Traffic Technologies). He holds the Department of Automatic Control and specializes in autonomous systems, particularly in path planning, sensor fusion, and human-vehicle interaction. His research integrates machine learning, robotics, and control theory to address challenges in intelligent transportation systems. He earned his Ph.D. in 2001 with a thesis on autonomous vehicle navigation in partially known environments. His work emphasizes real-world deployment, explainable AI, and safety-critical systems. Recent projects focus on lane change prediction, pedestrian behavior modeling, and cybersecurity for autonomous systems. Key contributions include neuro-symbolic frameworks for decision-making, real-time multi-physics field reconstruction, and cross-cultural studies of pedestrian interactions. He collaborates internationally on urban mobility resilience and hydrogen refueling infrastructure. Research Highlights : Development of knowledge graph-based prediction architectures Experimental validation of human-vehicle interaction in VR environments Creation of the SCOUT trajectory prediction framework
Prof. Felix Motzoi is an Associate Professor at the University of Cologne and Division Leader & Head of the 'Automatic Optimization, Control and Design' group at the Peter Grünberg Institute (PGI-8) in Jülich. His research focuses on advancing quantum technologies, including superconducting and semiconducting architectures, trapped cold atoms/ions, Rydberg qubits, and long-range entanglement. He leads theoretical efforts in quantum control theory, machine learning applications, hardware co-design, and error mitigation strategies. Key research areas include developing optimal control methodologies (e.g., DRAG, STA), numerical optimization, and dynamics modeling for quantum systems. His work bridges theoretical frameworks with experimental implementations, emphasizing practical solutions for scalable quantum computing. Recent publications highlight innovations in quantum gate design, error suppression via pulse shaping, and hybrid optimization techniques combining machine learning with physics-driven approaches. His team collaborates across disciplines to address challenges in qubit coherence, entanglement stabilization, and robust quantum processing.
Andrew Burton-Jones is a Professor of Business Information Systems at The University of Queensland Business School, where he also serves as co-lead of the Future of Health Research Hub and Chair of the Education Steering Committee of the Queensland Digital Health Centre. He is affiliated with multiple research centers including the Centre for the Business and Economics of Health, Centre for Enterprise AI, and Queensland Digital Health Centre across different faculties at UQ. His educational background includes a Bachelor (Honours) of Commerce and Master of Commerce from The University of Queensland, followed by a PhD from Georgia State University. With extensive international experience, he previously served as a tenured Associate Professor at the University of British Columbia before returning to UQ in May 2012. Burton-Jones' research focuses on three interconnected areas: organizational effectiveness in IT use (particularly electronic health records in healthcare settings), methods for analyzing and designing IT systems, and theoretical development within the Information Systems discipline. His work bridges academic theory with practical healthcare applications, with strong emphasis on digital transformation in health services. His recent publications reveal a strong focus on digital health applications, electronic medical records, and digital transformation in healthcare contexts. There's also significant attention to theoretical development in information systems, platform generativity, and research methodology. The work shows increasing integration of healthcare contexts with information systems theory. Fellow of the Association for Information Systems Fellow of the Academy of Social Sciences of Australia Editor-in-Chief of MIS Quarterly (2021-2023) President of the Association for Information Systems (2024-2025) Representative for the Americas for the Association of Information Systems International Representative for the Academy of Management (OCIS/CTO Division) Burton-Jones has supervised numerous PhD students across various topics related to digital health, information systems, and organizational transformation. He has secured substantial research funding including the UQ-QH HDR Alliance Program (2021-2027), ARC Training Centre for Information Resilience (2021-2026), and multiple Digital Health CRC grants. His leadership extends to helping found UQ's Graduate Certificate in Clinical Informatics and Digital Health. He is actively involved in the Future of Health Research Hub, Queensland Digital Health Centre, and Centre for Enterprise AI, where his work focuses on addressing real-world healthcare challenges through information systems research and digital transformation initiatives.
Crina Damsa is a Professor at the Department of Education, University of Oslo. Her research focuses on collaborative learning, interdisciplinary learning, and the role of digital technologies (including AI) in knowledge work and education. She leads projects like Unpacking collaboration: Multimodal analysis and combined method designs and Learning Ecologies in Higher Education , and is involved in research groups such as HEDWORK and LIDA. PhD in Educational Research, University of Oslo (2013) MSc in Learning Design and Technology, Utrecht University (Netherlands) BA in Language and Literature, Babes-Bolyai University (Romania) Her work examines sociocultural and sociomaterial aspects of learning, with a focus on student-centered environments, design-based research, and multimodal learning analysis. She supervises PhD students and contributes to methodological advancements in learning sciences. Editorial roles: Area Editor for Learning in Context , member of editorial boards for journals like Journal of the Learning Sciences and Frontline Learning Research Projects: Academic Hospitality in Interdisciplinary Education (AHIE) , Digital Integration of Video Assessment (DIVA) , Digital Tracing of Collaborative Learning (DigiT) , Global Teacher Education (GatherED)
Lisa Ollinger is a Professor of Production Automation at Ulm University of Applied Sciences (Technische Hochschule Ulm), where she has been serving since October 2019. She teaches courses in Automation Technology 1 and 2 for the Business Engineering program, Industrial Automation for the Digital Production program, and Flexible Automation for the Systems Engineering and Management Master's program. Her educational and professional background includes: Technology Leader for Engineering Projects in Automation and Digitalization at Procter & Gamble GmbH (2014-2019) Researcher at the German Research Center for Artificial Intelligence (DFKI) in the Innovative Factory Systems research area (2012-2014) Research Assistant at TU Kaiserslautern in the Production Automation department (2009-2011) Professor Ollinger's research focuses on the intersection of industrial automation and digital transformation. Her work explores how emerging technologies like Industrial Internet of Things, cyber-physical systems, and digital twins can revolutionize manufacturing and logistics processes. She investigates flexible production systems that can adapt to changing requirements through skill-based engineering approaches and novel communication architectures using OPC UA standards. Her research also extends to robotics applications, particularly industrial robotics and autonomous mobile robots, often leveraging ROS (Robot Operating System) frameworks. Her recent publications demonstrate a strong focus on practical implementations of Industry 4.0 concepts, particularly in warehouse management and production systems. She examines how digital twin technology can enhance logistics operations and how agent-based systems can improve manufacturing resilience. A common thread in her work is the application of OPC UA communication standards to create more flexible, interoperable industrial systems. Professor Ollinger holds significant administrative roles at THU: Dean of the Master's program in Systems Engineering and Management Member of the University Council Member of the Institute for Manufacturing Technology and Materials Testing (IFW) Founding Ambassador for Startup South She maintains active professional connections through ResearchGate, LinkedIn, and ORCID, reflecting her commitment to academic collaboration and knowledge sharing in the field of industrial automation and digital manufacturing.
Dr. Siqi Ma is a Senior Lecturer at the UNSW Institute for Cyber Security (IFCYBER) within the School of Systems & Computing at the University of New South Wales (UNSW). He previously served as a Lecturer at the University of Queensland's School of Information Technology and Electrical Engineering (ITEE). He holds a Ph.D. in Information Systems from Singapore Management University (2018) and was a Postdoctoral Research Fellow at Data61, CSIRO. He also visited Carnegie Mellon University (CMU) in 2015. Current Role: Senior Lecturer, UNSW Institute for Cyber Security Former Role: Lecturer, University of Queensland Education: Ph.D. (Singapore Management University), Postdoc (Data61, CSIRO) His research spans automated vulnerability detection, mobile security, IoT security, network authentication, and graph-based adversarial robustness. Recent work focuses on drone configuration bugs, Android malware analysis via GNNs, federated learning privacy, and credential leakage in open-source projects. Key trends in his 2024-2025 publications include automated security analysis for embedded systems, deepfake detection in multimedia, and privacy-preserving mechanisms for distributed networks. He collaborates with institutions like Purdue University, Singapore Management University, and CSIRO Data61.
Ellen Kuhl serves as the Catherine Holman Johnson Director of Stanford Bio-X and the Walter B. Reinhold Professor in the School of Engineering at Stanford University. She holds dual appointments as Professor of Mechanical Engineering and, by courtesy, Bioengineering, leading interdisciplinary research at the convergence of physics, computation, and biology. Her academic credentials include: Habil., TU Kaiserslautern (2004) Ph.D., University of Stuttgart (2000) M.S., Leibniz University of Hanover (1995) B.S., Leibniz University of Hanover (1993) Kuhl pioneers Living Matter Physics , developing computational frameworks that integrate physics-based modeling with machine learning to simulate biological systems across scales. Her work spans cardiovascular dynamics (including the 400-member global Living Heart Project), neurodegenerative disease progression (Alzheimer's tau pathology), and sustainable food systems (mechanics of plant/fungi-based meats). Recent innovations focus on automated model discovery using constitutive neural networks to democratize simulation tools for soft matter systems, with applications in precision medicine and climate-resilient food innovation. Her lab actively bridges engineering fundamentals with urgent societal challenges in healthcare and planetary health. Her publication trajectory reveals accelerating integration of AI with biomechanics, particularly in automated constitutive modeling for diverse tissues and food materials. Key trends include uncertainty quantification in neural networks, physics-informed machine learning for digital twins, and democratization of simulation tools for non-experts – reflecting her commitment to accessible computational science. Major recognitions include: National Science Foundation Career Award (2010) Humboldt Research Award (2016) ASME Ted Belytschko Applied Mechanics Award (2021) ERC Advanced Grant (2024) Fellowships in ASME and AIMBE As Bio-X Director, Kuhl orchestrates major interdisciplinary initiatives connecting engineering with life sciences, securing substantial funding including the 2024 ERC Advanced Grant. Her leadership extends to the US National Committee on Biomechanics and World Council of Biomechanics, while her Living Heart Project demonstrates exceptional translational impact through industry/medical partnerships across 24 countries. The Living Matter Lab operates as a nexus for high-impact research, developing computational tools that transform cardiovascular medicine, decode neurodegenerative mechanisms, and engineer sustainable food alternatives. Current projects leverage AI to accelerate plant-based meat development, model elephant-trunk-inspired soft robotics, and personalize cardiac simulations – all unified by her vision of physics-driven machine learning for global challenges.
Jeffrey S. Chase is a Professor of Computer Science at Duke University in the Department of Computer Science within Trinity College of Arts & Sciences. He has held this position since 2006 and currently serves as Director of Graduate Studies. His academic career spans decades with significant contributions to distributed systems research. Chase's research focuses on operating systems and distributed systems, with particular emphasis on cloud infrastructure services, trust management and security in cloud environments, energy-aware computing, and network storage. His work has evolved to center on integrity and trust: where it comes from, how we represent it, how we reason about it in software, and how we build software systems worthy of trust. His research group has developed notable systems including ExoGENI, Silver, and ADAMANT. His recent publications demonstrate his continued focus on secure data sharing architectures, networking for multi-tenant data centers, and federated authorization systems. These works collectively address fundamental challenges in distributed computing related to security, privacy, and network performance in cloud environments. Chase has received significant research funding including the CC*Data: ImPACT project (2017-2022), Collaborative Research: CICI: Secure and Resilient Architecture (2016-2020), and TWC: Frontier: Collaborative: Rethinking Security in the Era of Cloud Computing (2013-2019). He has taught advanced courses including CPS 512: Advanced Distributed Systems, CPS 310: Operating Systems, and CPS 510: Advanced Operating Systems. His teaching philosophy emphasizes deep understanding of core distributed systems concepts with practical applications to modern cloud infrastructure.
Christian Lundahl is Professor of Education at Örebro University, specializing in the history of assessments, evaluation, and Swedish educational research. His work focuses on internationalization of educational data, marketization of schools, and the role of PISA in policy debates. He leads the transnational research project The Global Laboratory – Torsten Husén and the Internationalization of Educational Research (funded by the Swedish Research Council) and co-edited books like Beyond PISA . Lundahl also developed Sweden’s first MOOC for teacher education and serves as scientific leader for the Open Parliament Laboratory (OPaL) . Research Interests : History of educational assessments and evaluations Transnational educational policy flows Marketization and computational analysis in education PISA data utilization and mis/trust Curriculum theory and policy Equity in grading and national tests Recent Trends in Publications include computational analytics in policy data, historical analysis of educational laboratories, and critiques of PISA’s political role. His 2025 articles examine sampling bias in parliamentary data and school marketization. Projects and Leadership : Principal investigator for The Global Laboratory (2020-2024) Co-developer of Sweden’s first MOOC for teacher training (2013) Scientific leader of OPaL – The Open Parliament Laboratory Visiting Professor at Humboldt University (2020)
Suren Jayasuriya is an Associate Professor at Arizona State University's The GAME School, with joint appointments in the School of Electrical, Computer and Energy Engineering (ECEE) and the Department of Arts, Media and Engineering (AME). He is also an Affiliate Faculty Member at the Mary Lou Fulton College for Teaching and Learning Innovation. His lab, the Imaging Lyceum, focuses on transdisciplinary research bridging computational imaging, computer vision, sensors, and STEAM education. Education Ph.D. Electrical and Computer Engineering, Cornell University (2017) M.S. Electrical and Computer Engineering, Cornell University (2015) B.S. Mathematics, University of Pittsburgh (2012) B.A. Philosophy, University of Pittsburgh (2012) Research Focus Dr. Jayasuriya's work integrates optics, computational photography, and machine learning to develop novel imaging systems. His research spans: Computational cameras and light transport analysis Atmospheric turbulence modeling and video restoration Neural volumetric reconstruction for sonar/radar STEAM education frameworks for K-12 teachers Philosophical aspects of imaging and representation His lab emphasizes interdisciplinary collaboration across engineering, arts, and humanities. Publication Trends Recent publications demonstrate strong focus on computational imaging (45%), AI/ML applications (30%), and educational technology (25%). Dominant themes include turbulence mitigation in videos, neural rendering for sonar/radar, sensor fusion, and AI curriculum development for middle schools. Work frequently appears in top venues like CVPR, SIGGRAPH, and IEEE Transactions. Awards Image Electronics Technology Excellence Award (IIEEJ, 2021) Best Demo Awards: IEEE ICCP 2019, MIRU 2018 Best Paper Award: IEEE ICCP 2014 ASEE Diversity Paper Finalist (2020) Teaching Honors: Fulton Top 5% Award (2019, 2021), ASU Game Changing Faculty (2021) Teaching & Advising Teaches graduate/undergraduate courses including Machine Vision (EEE 515), Minds and Machines (AME 400), and thesis supervision. Leads NSF-funded projects on computational imaging education and AI teacher training. Mentors students through the Imaging Lyceum lab with projects spanning optics, philosophy, and educational technology. Lab & Collaborations Directs the Imaging Lyceum, emphasizing Aristotle-inspired collaborative research. The lab works on: computational cameras, STEAM education, sensor development, and philosophical inquiries into imaging. Collaborates with Carnegie Mellon Robotics Institute and international partners. Funded by NSF, NEH, and industrial partners for projects in sonar imaging, heat resiliency sensing, and educational AI.
Emily Lines is a forest ecologist affiliated with the University of Cambridge, Department of Geography. She specializes in remote sensing (ground to satellite) and data science techniques to study forest structure, function, and dynamics. Her research addresses ecological and conservation questions, ranging from fundamental forest processes to applied challenges like climate change, deforestation, and forest management effectiveness. Department of Geography, University of Cambridge DLA Supervisor, Cambridge NERC Doctoral Landscape Awards Collaborator with geomorphologists, computer scientists, geneticists, and paleoecologists Her group employs fieldwork using terrestrial and drone laser scanning, photogrammetry, and traditional forest mensuration. Methodologically, she integrates deep learning, computer vision, and computational modeling to analyze forests at multiple scales. Priority topics include biodiversity assessment, structural dynamics, competitive interactions, dieback/disease monitoring, microclimate effects, radiative transfer, and regeneration patterns. Key tools: Terrestrial LiDAR, TLS validation, PlotToSat, FOR-species20K dataset, Deadtrees.earth database Recent work spans 3D remote sensing benchmarking, AI applications in forest monitoring, and climate change impacts on European forests Her publications highlight forest-landscape interactions, scalability of data science methods, and cross-disciplinary integration of ecological and computational approaches. She advocates for environmental sustainability in AI applications through initiatives like the C-CLEAR Doctoral Training Programme.
Tina Gupta will join the University of Oregon as an Assistant Professor in the Department of Psychology under the College of Arts and Sciences in Fall 2025. With expertise in clinical psychology and affective neuroscience, she focuses on adolescent emotional development and severe mental illness risk markers. Research Interests: Adolescent Development, Psychosis-risk, Resilience, Emotion Processing, Reward Processing, Early Intervention Methods: Clinical interviews, behavioral measures, facial expression coding, neuroimaging, eye-tracking, computational statistics Her work bridges clinical psychology and developmental psychopathology to identify biological and environmental factors contributing to severe mental illnesses like schizophrenia. She specifically examines disruptions in emotional processes and protective resilience mechanisms in at-risk adolescents. Dr. Gupta employs multi-modal approaches including fMRI , EMG , and longitudinal tracking to map brain-behavior relationships. Her recent publications analyze anhedonia trajectories, facial expressivity changes, and inflammation's role in adolescent mental health.
Brenda Connor serves as a Professor of Practice and Senior Technical Managing Director of the Critical Infrastructure Security Institute (CISI) at Texas Tech University, affiliated with the Department of Electrical & Computer Engineering in the Whitacre College of Engineering and the National Wind Institute. Her research focuses on Critical Infrastructure Security across key sectors: Energy Sector Water & Wastewater Systems Food & Agriculture Sector Healthcare & Public Health Sector Defense Industrial Base Sector Telecommunications applications include: Integrated Sensing and Communications (6G) AI-enhanced Internet of Things Supply Chain Security Dr. Connor directs the Critical Infrastructure Security Institute (CISI) and maintains active involvement with the National Wind Institute, driving initiatives in infrastructure resilience through advanced telecommunications frameworks.
Abayomi Baiyere serves as an Associate Professor in the Department of Digitalization at Copenhagen Business School (CBS), where he conducts cutting-edge research at the intersection of digital technologies and organizational transformation. His work significantly contributes to UN Sustainable Development Goals through digitally-enabled societal impact initiatives and has yielded 69 research outputs including high-impact publications in premier journals like Information Systems Journal and Information Systems Research . His research program focuses on: Digital transformation frameworks (notably the MIND framework for capability assessment) Platform design and governance mechanisms Smart service systems development Workplace transformation through digital subtraction logic Digital strategy implementation challenges Analysis of his 15 most recent publications (2024-2025) reveals a strong theoretical grounding in institutional and practice-based perspectives, with increasing emphasis on ethical dimensions of digital transformation, AI implementation constraints, and methodological innovations in computational research. His work consistently bridges conceptual rigor with practical applicability for organizational leaders. Dr. Baiyere actively shapes academic discourse through editorial roles including co-editing The Routledge Companion to Management Information Systems (2025) and organizing key events like the African IS Paper Development Workshop (2020). His public engagement includes 6 media contributions discussing digital workplace transformation and strategic implementation challenges, demonstrating commitment to translating research into practical insights for broader audiences. Within CBS, he has supervised 8 academic works while contributing to the department's international recognition in digitalization research. His activities reflect deep engagement with both theoretical advancement in information systems and practical solutions for organizational digital maturity.
Dr. Zhi Chen is a Lecturer in Computing at the School of Mathematics, Physics and Computing, University of Southern Queensland, specializing in Artificial Intelligence and Machine Learning with applications spanning digital agriculture and healthcare systems. Education: Master of Information Technology (MIT), University of Queensland, 2018 PhD, University of Queensland, 2023 Research Focus: His work centers on zero-shot learning, domain adaptation, and multimodal systems, addressing core challenges in computer vision and deep learning. Current projects integrate AI with agricultural risk modeling and medical diagnostics, emphasizing real-world deployment of robust algorithms under data-scarce conditions. Publication Trends: Recent output (2022-2025) shows concentrated expertise in source-free domain adaptation and generalized zero-shot learning, with significant contributions to plant disease recognition (via mobile multimodal systems) and diabetes subgroup analysis. His work consistently appears in premier venues including AAAI, CVPR, and ACM MM, demonstrating methodological innovation applied to critical domains like climate-resilient agriculture and precision medicine. Supervision: Currently serves as Associate Supervisor for a doctoral candidate developing parametric insurance models for oyster farms to mitigate climate-related risks from king tides and extreme weather events. Awards: No scientific awards were documented in the provided materials.
