Jean Ponce is a Professor at Ecole Normale Supérieure - PSL and a Global Distinguished Professor at New York University's Courant Institute and Center for Data Science. He serves as Scientific Director of PRAIRIE Interdisciplinary AI Research Institute and co-founded Enhance Lab, commercializing super-resolution imaging software. His research focuses on computer vision, machine learning, robotics, and image processing. Ponce has held roles at Inria, MIT, Stanford, and the University of Illinois, and is an IEEE and ELLIS Fellow. He has served as chair of major conferences like CVPR, ECCV, and ICCV, and authored the textbook 'Computer Vision: A Modern Approach.' Research interests include statistical models for exoplanet detection, neural networks for 3D reconstruction, and self-supervised learning. His work combines theoretical foundations with practical applications in astrophysics, robotics, and imaging. Notable awards include the IEEE CVPR Longuet-Higgins Prize (2016, 2020) and ICML Test-of-Time Award (2019). Key projects include Enhance Lab's high dynamic range imaging and PRAIRIE's interdisciplinary AI initiatives. Ponce's articles explore cutting-edge topics like neural object priors, geodesic motion planning, and satellite image analysis. His contributions bridge academic research and industrial applications, emphasizing both fundamental theory and real-world impact.
Lars-Olof Johansson is a Senior Lecturer at Halmstad University's School of Information Technology, specializing in Informatics. His research focuses on digital service innovation from a learning perspective, emphasizing collaboration between diverse stakeholders and knowledge exchange in innovation processes. He is actively involved in the LeaDS research program (Learning in a Digitalized Society) and teaches in the bachelor's program 'Digital Business Development' and the master's program 'Digital Learning'. His work bridges educational methodologies and technological innovation, particularly in fostering environments where interdisciplinary learning drives successful digital service creation. Notably recognized as an 'Excellent Teacher in Informatics,' he integrates practical experience with academic rigor, contributing to both scholarly discourse and pedagogical advancements. Key projects include SESMA (2019-2021), exploring sustainable mobility solutions, and ongoing collaborations in boundary practices for ICT innovation. His publications span topics like knowledgeability in digital service innovation, ethics in autonomous systems, and collaborative learning frameworks. His awards highlight his pedagogical impact, while his research addresses systemic challenges in innovation through interdisciplinary approaches.
Professor Nir Oren is a faculty member at the School of Natural and Computing Sciences , University of Aberdeen. His research focuses on multi-agent systems , formal argumentation , computational trust theory , and norm-based reasoning . He currently supervises PhD students in Computing Science and serves as Dean for Research Performance. Research Specialisms: Artificial Intelligence, Operational Research Contact: n.oren@abdn.ac.uk Research Trends (2022–2025): Nir Oren's publications span argumentation theory , BDI agent modeling , resilience in autonomous systems , and human-machine collaboration . His recent work addresses responsibility-aware AI , medical explainability , and environmental sensor networks . Key methods include probabilistic reasoning , game theory , and logical formalisms .
Michael O'Dea is a Senior Lecturer in the Department of Computer Science at the University of York, United Kingdom. He has held previous academic positions at York St John University, Beijing University of Technology, University of Hull, and Waikato Institute of Technology, bringing extensive international experience in computer science education. He is actively engaged in pedagogical scholarship and leadership in higher education innovation. Senior Lecturer, Department of Computer Science, University of York Senior Lecturer in Computer Science, York St John University Lecturer in Software Engineering, Beijing University of Technology, China Lecturer in Computer Science, University of Hull Lecturer in Information Technology, Waikato Institute of Technology, NZ Dr. O'Dea earned his Ed.D. in Computer Based Learning from the University of Leeds. His research centers on the integration of artificial intelligence into educational practices, with a strong emphasis on AI literacy, the effectiveness of generative AI in teaching and learning, and the evolving landscape of technology acceptance in higher education. He investigates how AI tools can enhance student learning, faculty development, and institutional policy. His recent publications span topics such as AI literacy assessment, the future of online and blended learning, the application of machine learning in earthquake prediction, and international study abroad effectiveness. These works reflect a broad interdisciplinary approach, combining computer science, educational theory, and policy analysis. His scholarship is increasingly focused on the transformative potential of generative AI in academic settings, as evidenced by his leadership in special journal issues and funded research projects. Dr. O'Dea holds significant editorial responsibilities as Associate Editor and Lead Guest Editor for the Journal of University Teaching and Learning Practice and as Guest Editor for a special issue in Education Sciences on generative-AI-enhanced learning. He is also an Invited External Academic Affiliate at the King's Institute for Artificial Intelligence, King's College London. Associate Editor - Special Issues, Journal of University Teaching and Learning Practice Lead Guest Editor, Special Issue on Technology Acceptance Models, JUTLP (2024) Guest Editor, Special Issue on Generative-AI-Enhanced Learning, Education Sciences Principal Investigator, QAA Collaborative Enhancement Project on Graduate Attributes in the Era of GenAI (2025) He has delivered numerous invited talks and workshops at institutions such as the University of York, Queen Mary University of London, and international conferences including the Academy of Management and the International Conference on Artificial Intelligence in Education. His work bridges research, practice, and policy in higher education, with a strong commitment to inclusive and innovative teaching methodologies.
Rosella Gennari is an Associate Professor in Computer Science at the Faculty of Engineering, Free University of Bozen-Bolzano, where she conducts research and teaches in Human-Computer Interaction (HCI). Her work is centered on designing interactive technologies for children, focusing on physical-digital (phygital) artefacts, Technology-Enhanced Learning (TEL), and inclusive design. She leads the Research Unit Human-Centred Intelligent Systems and is actively involved in institutional leadership, including serving on the Third-Mission Board. Ph.D. : Computer Science, Amsterdam University (2002) Postdoctoral Experience : CWI, Amsterdam (ERCIM Alain Bensoussan Fellow); FBK-irst, Trento Leadership : Scientific & Technological Coordinator of the FP7-EU TERENCE project Her research explores how children interact with and design smart technologies, including IoT and AI, through playful and tangible interfaces. She investigates socio-emotional learning, digital well-being, and responsible design, often employing participatory and action research methods. Her work bridges computer science, education, and social impact, aiming to empower young learners as co-creators of technology. The analysis of her recent publications reveals a strong trend in developing and evaluating toolkits and frameworks for children and pre-teens to engage in designing smart things, IoT systems, and sustainable cities. Her work consistently emphasizes inclusivity, reflection, and responsible design, often in collaboration with teachers and learners. The publications span top HCI venues and journals, demonstrating a focus on practical applications in educational settings and the impact of technology on young users. Scientific Awards and Recognition ERCIM Alain Bensoussan Fellowship for talented young researchers Editorial Board Member, Journal of Child Computer Interaction (Elsevier, Q1) Regular reviewer for top HCI conferences and journals Advising and Grants : While specific advisees are not listed, her leadership role in the FP7-EU TERENCE project and numerous other research initiatives indicates extensive experience in securing and managing competitive grants. She mentors students through her research group and teaching, fostering the next generation of HCI researchers. Her collaborative network is extensive, with frequent co-authorship with researchers such as Alessandra Melonio, Maristella Matera, and Mehdi Rizvi. Labs and Teams : She leads the Human-Centred Intelligent Systems research unit, which serves as her primary lab and team. This group focuses on placing humans at the center of computer science and information engineering research. She is also a core member of the organizing committee for the MIS4TEL international conference series, highlighting her role in building and sustaining a global research community in Technology-Enhanced Learning.
Carolynn Patten is a Professor in the Department of Neurobiology, Physiology and Behavior at the University of California, Davis, with affiliations in Physical Medicine and Rehabilitation. Her work bridges neuroscience, biomechanics, and clinical rehabilitation to advance neurorehabilitation for individuals with motor impairments. Research Interests: Dr. Patten's research investigates the neural basis of human movement, focusing on motor dysfunction in aging and neurological conditions such as stroke. She employs transcranial magnetic stimulation (TMS), EEG, EMG, biomechanical analysis, and clinical assessments to study motor recovery mechanisms and neuroplasticity. Her work aims to develop biomarkers of recovery and improve rehabilitation efficacy. Publication Trends: Recent publications emphasize computational modeling of musculoskeletal systems, gait analysis post-stroke, and assessment tools for locomotor efficacy. These works reflect a strong trend toward integrating engineering, neuroscience, and clinical practice to enhance rehabilitation outcomes. Scientific Awards: No awards listed in the provided text. Advising and Grants: While specific students and grants are not mentioned, her active publication record suggests ongoing mentorship and externally funded research in neurorehabilitation and translational neuroscience. Labs and Teams: Her research involves interdisciplinary collaboration across neuroscience, bioengineering, and rehabilitation medicine, likely within UC Davis research centers focused on movement disorders and neurorecovery.
Dr. Joseph Wang is the Distinguished Professor of Nanoengineering and the SAIC Endowed Chair at UC San Diego. He leads the NBE Lab and directs the Center of Wearable Sensors and the Center for Mobile-health Systems. With over 50 researchers in his team, his work focuses on nanomachines, wearable sensors, electrochemistry, and analytical chemistry. His global citation ranking places him #13 in Chemistry and #31 in Materials Science, with an H-index of 217 and over 180,000 citations. He has been a Highly Cited Researcher since 2014 and ranks #4 in Nanoscience & Nanotechnology in the 2025 World Top 100 Scientists list. His research has led to groundbreaking innovations, including microrobots for lung cancer treatment, multiplexed microneedle sensors, and wearable devices for real-time health monitoring. He has been honored with prestigious awards such as the 2024 ACS Award in Analytical Chemistry, IEEE Sensors Council Award, and IUPAC Medal. He holds honorary doctorates from Comenius University and Charles University, and Woxsen University named its Chemistry Department after him. Key contributions include pioneering work in biohybrid microrobots, self-healing wearable devices, and sweat-based health monitoring systems. His lab’s work has been featured in Nature, Science, and The Economist. He co-authored influential books like Analytical Electrochemistry (4th ed.) and Nanomachines , and his research spans clinical applications, environmental sensing, and personalized medicine.
Julian Berger is a postdoctoral researcher at the Max Planck Institute for Human Development in the Center for Adaptive Rationality , where he explores how to enhance decision-making through hybrid human-AI systems. He is also a fellow of the Joachim Herz Foundation and has received funding from the Foundation of German Business and the Danish Data Science Academy. Education: M.A. Psychology in Business and Economics, Universidade Catolica Portuguesa (2021) B.A. Politics, Administration and International Relations, Zeppelin Universität (2018) His research spans human-AI collaboration , collective intelligence , and interpretable machine learning . A recurring theme in his work is developing methods to combine human expertise with AI capabilities for accuracy in domains like medical diagnostics , credit scoring , and football analytics . He has authored publications in high-impact venues such as PNAS , Nature Human Behavior , and Science and Medicine in Football . Scientific awards and funding include: Fellowship for interdisciplinary economics, Joachim Herz Foundation (2024) PhD funding from the Foundation of German Business (Stiftung der deutschen Wirtschaft) Research grant from the Danish Data Science Academy His recent article trends emphasize ensembling techniques that leverage complementary human and AI errors, algorithmic fairness, and practical heuristics like Hybrid Confirmation Trees. These works demonstrate significant improvements in diagnostic accuracy and decision cost-efficiency. Beyond academia, Berger works as a consultant and ML engineer with Simply Rational , focusing on interpretable models for financial and sports analytics. His work bridges theoretical research with real-world applications, prioritizing fairness, transparency, and human accountability in AI systems.
Tomohiro Nagashima is an Assistant Professor of Technology-Enhanced Learning at Saarland University in Germany. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University, with previous affiliations at Carnegie Mellon University's HCII program and Stanford Graduate School of Education. His work bridges learning sciences and human-computer interaction to co-design technology that supports human learning in STEM domains. Ph.D. in Human-Computer Interaction, Carnegie Mellon University M.S. in Human-Computer Interaction, Carnegie Mellon University M.A. in Learning, Design, and Technology, Stanford Graduate School of Education Nagashima collaborates with over 800 educators and school-aged students across the US, Europe, and East Asia to develop AI-driven learning technologies and instructional strategies. His research emphasizes stakeholder-inclusive design of educational tools and open educational practices, advocating for equity and accessibility in digital learning environments. As an open education advocate, he contributes to Creative Commons Japan and the Open Education Group, focusing on systemic challenges in sharing educational materials. His methodological approach combines participatory design and school-based empirical studies to create practical solutions for modern pedagogical needs.
D. Fox Harrell is a Professor of Digital Media and Artificial Intelligence at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), leading the Imagination, Computation, and Expression (ICE) Lab. He directs the MIT Center for Advanced Virtuality, pioneering computational media for social impact. His research bridges AI, cognitive science, and digital arts to explore imagination's intersection with technology. He holds a PhD and has authored the seminal book *Phantasmal Media* (MIT Press, 2013), earning an Emmy for his virtual reality initiatives. His work includes the Chimeria Platform (patented), which models social identity in games and media, and Project VISIBLE, using VR to teach behavioral ethics. Key awards include the NSF CAREER Award for identity representation research. His interdisciplinary collaborations span MIT's Institute for Data, Systems, and Society (IDSS) and international initiatives like the QCRI-CSAIL Alliance.
Paulo Blikstein is an Associate Professor of Communication, Media, and Learning Technologies Design at Teachers College, Columbia University. He holds affiliations with the Mathematics, Science & Technology department and the Communication, Media, and Learning Technologies Design program. His expertise spans curriculum design, digital innovation, science education, and educational technology. Dr. Blikstein earned a Ph.D. in Learning Sciences from Northwestern University (2009), M.Sc. in Media Arts & Sciences from MIT Media Lab (2002), and degrees in Engineering from the University of São Paulo (Brazil). His research focuses on leveraging technology to enhance learning through computational modeling, maker education, and tangible interfaces. He leads the Transformative Learning Technologies Lab and the FabLearn Program, which develop innovative tools like MoDa and PlayData, integrating computational thinking with real-world science experiments. His work emphasizes equitable access to technology-driven education, particularly in the Global South. Recent projects include deploying cloud labs for biology education, analyzing disinformation dynamics via agent-based models, and exploring how social media influences political radicalization. He critiques commercial education technology discourse through a critical pedagogy lens, advocating for culturally responsive, hands-on learning. Blikstein’s research bridges theory and practice, addressing systemic challenges in science education through participatory design with teachers and communities. His labs create sustainable educational technologies, such as DIY liquid handling robots and haptic feedback systems, to democratize STEM access. He also investigates computational identity formation in K-12 students and the role of making in fostering gender equity in STEM.
Carlos Toxtli is an Assistant Professor at Clemson University where he leads the Human-AI Empowerment Lab. His research applies Human-Centered AI to create fair workplace tools, focusing on NLP, computer vision, and crowdsourcing ethics. He holds a PhD in Computer Science from Northeastern University and previously worked at Google, Microsoft Research, and Snap Inc. Education: Ph.D. Computer Science, Northeastern University M.S. Innovation & Technological Entrepreneurship, Monterrey Institute of Technology MBA, IEDE Business School B.S. Computer Science, University of the Valley of Mexico B.S. Computer Engineering, National Autonomous University of Mexico Research Focus: Dr. Toxtli develops AI systems promoting workplace fairness through ethical frameworks. His work spans: 1) Human-AI collaboration for task management, 2) Bias mitigation in gig economies, 3) Multimodal interfaces for accessibility, and 4) Culturally adaptive systems. His lab explores how AI can augment human capabilities while ensuring transparency. Publication Trends: Recent works demonstrate strong focus on LLM reliability (7 papers), human-AI teaming (4 studies), and ethical AI frameworks (3 publications). Over 60% of 2024-2025 output addresses real-world deployment challenges. Awards: UNESCO IRCAI Global Top 100 project Google Apps Developer Challenge 1st Place Facebook Developers World Hack 1st Prize Intel Innovation Latin App 1st Prize NSF STIR Labs Research Grant Leadership: Founded the Human-AI Empowerment Lab securing $1.2M in NSF/industry grants. Supervises 8 PhD students in human-centered computing projects. Previously co-founded 5 tech startups including ComproPago (acquired by Coca-Cola FEMSA).
Dr. Andrea Grover is an Associate Professor in the Department of Information Systems and Quantitative Analysis at the University of Nebraska Omaha’s College of Information Science & Technology. Her research focuses on citizen science, technology design, and collaboration systems in data-intensive environments. She holds a Ph.D. in Information Science & Technology from Syracuse University, an MS in Information from the University of Michigan, and a BA in Mathematics from Alma College. Her research interests include organizational impacts of technology, open collaboration frameworks, and ethics in information systems. She teaches courses on management and IT ethics, employing ungrading techniques to enhance student engagement. Notable contributions include work on citizen science data quality, cyber-security tools leveraging crowdsourcing, and barriers in STEM education equity. Dr. Grover has been recognized with the 2022 Rising Star Distinguished Ecologist award and serves on editorial boards (e.g., Frontiers in Ecology) and conference committees (e.g., ACM CSCW DEI Co-chair). She has secured grants such as the NSF-funded “Streamlining Embedded Assessment to Understand Citizen Scientists' Skill Gains” (2017–2019) and contributed to media discussions on citizen science via National Public Radio. Her recent publications explore hybrid human-AI tools, agile citizen science methodologies, and systemic barriers in education. She actively participates in interdisciplinary initiatives, bridging technology, ecology, and social sciences to advance participatory research practices.
Forest Agostinelli is an Assistant Professor in the Department of Computer Science and Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina, where he is also affiliated with the AI Institute. His research focuses on designing AI algorithms for pathfinding problems, integrating deep learning, reinforcement learning, heuristic search, and formal logic. He holds a Ph.D. in Computer Science from the University of California, Irvine, an M.S. from the University of Michigan, and a B.S. in Electrical and Computer Engineering from The Ohio State University. Research Overview : Agostinelli’s work emphasizes solving pathfinding problems in domains like robotics, theorem proving, and molecular optimization. His group develops explainable AI methods to enable collaboration between humans and machines. Key projects include DeepCubeA (solving the Rubik’s Cube via deep reinforcement learning) and neural activation function research. Funding & Awards : He has secured grants from NSF, NASA EPSCoR, and South Carolina’s ASPIRE and MADE programs. Notable awards include the NSF Graduate Research Fellowship and the Graduate Education for Minority Students Fellowship. Teaching : He teaches courses in Artificial Intelligence (CSCE 580) and Deep Reinforcement Learning and Search (CSCE 790), mentoring over 15 students at undergraduate and graduate levels. Labs & Collaborations : Active in AI-driven education and interdisciplinary projects, his lab contributes to tools like ALLURE for children’s learning and Bioinformatics platforms like CircadiOmics.
Besiki Stvilia is a Professor in the School of Information at Florida State University's College of Communication and Information. He holds a Ph.D. and M.S. in Library and Information Science from the University of Illinois at Urbana-Champaign, along with an M.S. in Applied Mathematics from Tbilisi State University. His research focuses on data quality assurance, digital curation, social informatics, and knowledge organization. He has led projects on research data management, metadata frameworks, and collaborative data practices in scientific communities. Stvilia has taught courses including LIS 6205 (Information Behavior), LIS 5263 (Information Retrieval Theory), and LIS 5787 (Metadata Practices). His funded research includes grants on data quality infrastructure for repositories, researcher identity curation, and mobile wellness application behavior studies. His work emphasizes bridging theoretical models with practical applications in digital libraries and academic systems. His research spans topics like GenAI credibility assessment, ontology development for data repositories, and user engagement with social Q&A platforms. He has advised multiple collaborative projects involving interdisciplinary teams and has published extensively in journals like Journal of Documentation and Information Processing & Management .
