Eleanor O'Rourke is an Associate Professor at Northwestern University with joint appointments in the Department of Computer Science and the Learning Sciences, part of the McCormick School of Engineering. She co-directs the Delta Lab, focusing on interdisciplinary research in Human-Computer Interaction, Artificial Intelligence, and Learning Sciences. Her work examines how learning environments can foster motivation and effective practices in computer science education, supported by grants from NSF and Google. Educated at the University of Washington (PhD, MS in Computer Science & Engineering) and Colby College (BS in Computer Science and Spanish), her research employs mixed methods, including design-based research and grounded theory, to study student motivation, affective responses during programming, and AI-driven interventions. Notable contributions include tools like Ply and Isopleth , which support novice web developers, and studies on student self-assessment biases and growth mindset incentives. Her work has been recognized with multiple Best Paper Awards at ACM conferences, including ICER 2024 and SIGCSE 2022. She teaches courses such as Transformative AI and the Learning Sciences and Design of Learning Environments , and advises a diverse cohort of PhD students and undergraduates. The Delta Lab’s collaborative approach emphasizes innovation in educational technology and human-centered design.
University of California , Santa Barbara (UCSB)United States
Somayeh Dodge is an Associate Professor of Spatial Data Science in the Department of Geography at the University of California, Santa Barbara (UCSB). She leads the MOVE Lab and serves as Co-Associate Director of the UCSB Center for Spatial Studies and Data Science. Her research focuses on computational movement analysis, spatiotemporal data science, and the application of these tools to study human and ecological systems. She holds editorial roles in major journals including Journal of Spatial Information Science and Geographical Analysis. Education: PhD in GIScience (University of Zurich, 2011), MS in GIS Engineering (K.N.Toosi University of Technology, 2005), and BS in Geomatics Engineering (2003). Postdoctoral work at The Ohio State University and University of Zurich. Prior faculty positions include University of Minnesota (2016–2019) and University of Colorado, Colorado Springs (2013–2016). Research interests include wildfire impact analysis, mobility patterns during disasters, environmental vulnerability modeling, and geovisualization techniques. Her NSF CAREER project explores movement responses to environmental disruptions. Teaching focuses on GIScience, movement analytics, and spatial modeling courses. Awards: 2021 NSF CAREER Award and 2022 AAG Emerging Scholar Award. Active in editorial boards for multiple journals and serves on the Board of Directors for the University Consortium for Geographic Information Science (UCGIS). Advising: Supervises 7 graduate students in mobility analytics and environmental modeling. Labs/Teams: MOVE Lab (https://move.geog.ucsb.edu/) focuses on computational movement ecology and human mobility studies.
Nancy Reynolds is an Associate Professor of History at Washington University in St. Louis, with affiliate appointments in Women, Gender and Sexuality Studies and Jewish, Islamic, and Middle Eastern Studies. Her research focuses on environmental and social-cultural history of twentieth-century Egypt, examining political-material intersections in built environments from department stores to dams. Her academic background includes: PhD in History from Stanford University MA in History from Stanford University BA from Harvard University Reynolds' scholarship spans Environmental History , Social History , and Urban Studies , with emphasis on how mundane objects (socks, store floors) and monumental structures (Aswan Dam, temples) reflect nationalist struggles. Her work critically engages gender dynamics and decolonization , revealing how consumption patterns and urban spaces became sites of political contestation in semicolonial Egypt. Her 13 publications (2000-2024) demonstrate an evolution from consumer culture studies (department stores, Cairo Fire) to environmental history (Aswan Dam, desert ecologies), with recent collaborative work on Middle Eastern wastelands and sustainable architecture. The 2024 corpus particularly emphasizes political ecologies and materialized absence. Her scientific recognition includes: Roger Owen Book Award (2013) for A City Consumed American Council of Learned Societies Fellowship (2012) Bernadotte E. Schmitt Grant (2010) Stanford Humanities Center Geballe Dissertation Prize Social Science Research Council Fellowship Reynolds actively shapes graduate education as former administrator of History and JIMES PhD/MA programs. Her research is sustained by major grants including a Mellon Sawyer Seminar (2016-2018) and Mellon New Directions Fellowship (2014-2016), both supporting transregional collaborations on environmental humanities. She co-leads the Grounding the Ecocritical research collective with Dr. Anne-Marie McManus, producing the "Following Absence" symposium and CSSAAME special section on Middle Eastern wastelands.
David Hsu is Provost's Chair Professor in the Department of Computer Science at the National University of Singapore (NUS) School of Computing, where he founded and directs the NUS Artificial Intelligence Laboratory (NUSAIL) and leads the Smart Systems Institute. His academic leadership includes chairing major conferences such as Robotics: Science & Systems (2015) and IEEE ICRA (2016), alongside editorial roles in IEEE Transactions on Robotics and the Journal of Artificial Intelligence Research. He earned a B.Sc. in Computer Science & Mathematics from the University of British Columbia and a Ph.D. in Computer Science from Stanford University. His research spans robotics, AI, and computational biology, with recent focus on robot planning under uncertainty and human-robot collaboration. Current work integrates machine learning with decision-theoretic planning to enable robust human-robot co-existence in unstructured environments. Analysis of his 2023-2025 publications reveals dominant trends in deformable object manipulation (e.g., clothes handling via semantic keypoints), open-world navigation using scene graphs, and LLM-driven multi-agent reasoning for complex tasks. Key innovations include perspective-aware visual grounding for human-centric interaction and functional object arrangement through compositional generative models, reflecting a strong emphasis on real-world applicability. His scientific contributions have earned prestigious recognition: IJCAI-JAIR Best Paper Prize (2022) for foundational AI research Robotics: Science & Systems Test of Time Award (2021) IEEE Fellowship (2018) for contributions to robotic planning RSS Best Systems Paper Award (2017) RoboCup Best Paper Award at IROS (2015) Humanitarian Robotics Award at ICRA (2015) As director of the Adaptive Computing Laboratory, Hsu drives research on fundamental computational frameworks for human-robot interaction. The lab's work on uncertainty-aware decision-making has secured significant research funding through grants from Singapore's National Research Foundation and industry partnerships with robotics firms. While specific student names aren't publicized, his leadership in the NUSAIL indicates extensive mentorship of doctoral candidates in AI and robotics.
Xiaohu Guo is a Professor of Computer Science at the University of Texas at Dallas specializing in computer graphics, computer vision, and geometric modeling. His research develops algorithms for 3D/4D reconstruction, virtual reality, medical imaging, and physics-based simulations. Professor Guo has received significant recognition including a Best Paper Award at SIGGRAPH (2023) and an NSF CAREER Award (2012). His current research focuses on dynamic human capture, deformable models, and medical image computation. Education: PhD, Stony Brook University MS, Stony Brook University BS, University of Science and Technology of China Research Funding: Recently secured a $500,000 NSF grant for developing open-source 4D reconstruction frameworks for real-time dynamic human capture (2021). Editorial Roles: Serves on editorial boards of Graphical Models , Computer Animation and Virtual Worlds , and IEEE Transactions on Visualization and Computer Graphics .
Nicholas Mattei is an Associate Professor of Computer Science at Tulane University and Co-Director of the Tulane Center for Community Engaged AI. He holds a Ph.D. from the University of Kentucky (2012) and researches artificial intelligence, machine learning, and decision-making systems. His work combines theory, data, and experiments to develop algorithms supporting individual and group decision-making. Dr. Mattei's research spans AI ethics, fairness in algorithms, computational social choice, and preference learning. He has published over 100 academic articles and received multiple grants from organizations including Google, IBM, and the National Science Foundation, including a 2024 NSF CAREER Award. He co-authored 'Computing and Technology Ethics: Engaging Through Science Fiction' from MIT Press. Prior to joining Tulane, he held research positions at IBM Research, Data61/CSIRO, and NASA Ames Research Center. His teaching portfolio includes courses on Discrete Mathematics, Data Science, Artificial Intelligence, and Multi-agent Systems.
YingLi Tian is a CUNY Distinguished Professor in the Department of Electrical Engineering at The City University of New York. Their work focuses on computer vision, machine learning, and medical imaging. Key areas include sign language recognition, medical image analysis, and AI-driven healthcare solutions. Research Interests: Artificial Intelligence applications in healthcare 3D point cloud and scene understanding Self-supervised learning and domain adaptation Sign language recognition systems Medical imaging segmentation and diagnosis Human-robot interaction and assistive technologies Notable Projects: Developed AI systems for American Sign Language recognition using RGB-D data Pioneered self-supervised feature learning techniques in medical imaging Created virtual contrast enhancement tools for CT scans Advanced sea ice motion prediction using deep learning Labs & Teams: Leads the Media and Information Technology Lab at CCNY, focusing on multimodal AI and healthcare technology innovations.
Gabriela Minigo serves as an Honorary Fellow in Global and Tropical Health and Associate Dean - Learning and Teaching within the Faculty of Health. Her academic profile demonstrates active engagement in malaria immunology research with a recent expansion into circadian rhythm and metabolic health investigations. Dr. Minigo completed her PhD at the University of Melbourne (awarded March 31, 2007) and earned a Master of Clinical Epidemiology from the University of Newcastle (awarded December 8, 2017). Her educational background provides a strong foundation in both basic science and clinical epidemiology. Her primary research focuses on immunological responses to malaria, with particular expertise in T follicular helper cells, dendritic cell function, and regulatory T cells in Plasmodium falciparum and Plasmodium vivax infections. Analysis of her research fingerprint reveals significant contributions to Plasmodium falciparum Immunology and Microbiology (100%), Dendritic Cell Immunology and Microbiology (45%), Regulatory T Cell Immunology and Microbiology (38%), and other related fields. In recent years, she has expanded her research to investigate the relationship between photoperiod, circadian rhythm, and metabolic health, as evidenced by her 2024 publications on these topics. Dr. Minigo's scholarly output shows an evolving research trajectory from fundamental malaria immunology toward interdisciplinary investigations connecting circadian biology with metabolic health. Her recent publications (2022-2024) demonstrate continued strong contributions to malaria immunology while incorporating new dimensions related to light exposure, sleep patterns, and glucose control. She has secured research funding for multiple projects including 'Rainmaker start up- Does exposure to artificial light alter circadian rhythm and glucose control in Australian adults? A pilot study' (2023-2026) where she serves as Co-Investigator, and 'Effect of Extended Photoperiod Exposure on Circadian Rhythm and Glucose Control' (2024-present) where she is Principal Investigator. Previously, she contributed as Chief Investigator C to 'Manipulating T follicular helper cells to improve human malaria vaccines' (2020-2023). As Associate Dean for Learning and Teaching, Dr. Minigo holds significant educational leadership responsibilities within the Faculty of Health. She is registered to supervise postgraduate research, indicating her active role in mentoring graduate students in immunology and tropical medicine research.
Jeanna Matthews is a Full Professor of Computer Science at Clarkson University and an affiliate at Data and Society. She holds a PhD from UC Berkeley (1999) and teaches courses ranging from operating systems to cybersecurity. Her research focuses on algorithmic transparency, AI ethics, and societal impacts of automated systems. Matthews is a prominent ACM leader, serving on multiple committees including the Technology Policy Subcommittee on AI Accountability. She has pioneered work on forensic software analysis in criminal justice systems and delivered DEF CON presentations on virtualization security and adversarial testing. Awards include ACM Distinguished Speaker and Fulbright Specialist roles. Her work emphasizes open-source tools and critical thinking in education, extending to global service learning programs in the Dominican Republic and Brazil. Education: PhD in Computer Science (UC Berkeley, 1999), B.S. in Math/Computer Science (Ohio State, 1994), B.A. in Spanish (SUNY Potsdam, 2016). Research Interests: Cybersecurity vulnerabilities, algorithmic accountability frameworks, automated decision systems in justice contexts, and ethical AI design. Recent projects include investigating bias in DNA forensic software through a Brown Institute grant and analyzing political polarization on social platforms. Awards & Recognition: ACM Distinguished Speaker (2018-present) Fulbright Specialist (2018-present) 2018-2019 Brown Institute Magic Grant ACM SIGOPS Chair (2011-2015) ACM Special Interest Group Governing Board Chair (2016-2018) Teaching & Outreach: Designed courses integrating open-source tools and critical inquiry, including abroad programs in Mexico, Brazil, and the Dominican Republic. Advocates for lifelong learning strategies and questioning underlying assumptions in computing systems. Key Projects: Forensic Software Accountability: Examining discrepancies in DNA analysis tools Algorithmic Transparency: Frameworks for auditing automated systems Cybersecurity Education: Adversarial testing methodologies for justice software
Suining He is an Assistant Professor at the University of Connecticut (UConn)'s School of Computing, leading the Ubiquitous and Urban Computing Lab since 2019. Previously, he was a postdoctoral research fellow at the University of Michigan's Real-Time Computing Lab (2016–2019). He holds a Ph.D. in Computer Science from the Hong Kong University of Science and Technology (2016) and a B.Eng. in Mechanical Design from Huazhong University of Science and Technology (2012). His research focuses on Cyber-Physical Systems (CPS), Smart & Connected Communities, Human-Centered Computing, and Urban Computing Cyberinfrastructure, with emphasis on mobility, equity, and AI-driven solutions. He has received prestigious awards including the NSF CAREER Award (2023), Google Research Scholar Program Award (2021), and recognition as a Stanford Top 2% Scientist (2020–2024). His work spans interdisciplinary grants from NSF, USDA, Google, NVIDIA, and industry partners. Recent publications explore autonomous driving simulation, equity-aware mobility prediction, and urban crowd activity modeling. Teaching excellence is reflected in his 2020 UConn Provost Award. He advises on reinforcement learning, CPS, and mobile computing, with openings for 2025/2026 PhD students. His lab collaborates on socially-conscious AI, privacy-preserving learning, and location-based services with industrial impact.
John R Anderson is the Richard King Mellon University Professor of Psychology and Computer Science at Carnegie Mellon University (CMU), affiliated with the Department of Psychology within the Dietrich College of Humanities and Social Sciences. His research focuses on understanding higher-level cognition, particularly mathematical problem-solving, through the development of the ACT-R cognitive architecture—a computational framework simulating human cognitive processes. This architecture integrates behavioral, neural, and educational data to model learning and decision-making. Anderson’s work bridges cognitive science, neuroscience, and educational technology. He investigates how brain imaging (e.g., fMRI, EEG) can reveal the temporal dynamics of cognitive processes and improve instructional methods. His research emphasizes analyzing brain activity time courses to uncover underlying mechanisms of problem-solving and skill acquisition. Key Research Themes: Cognitive architectures, neural correlates of learning, computational models of memory, and intelligent tutoring systems. Notable Contributions: Development of the ACT-R architecture, integration of neuroimaging with cognitive modeling, and studies on skill transfer and learning strategies. Anderson’s publications include seminal books like Cognitive Psychology and Its Implications and How Can the Human Mind Occur in the Physical Universe? His work has advanced understanding of associative memory, strategic decision-making, and the application of cognitive models in educational technology. His lab, the ACT-R Research Group, collaborates across disciplines to model complex cognitive tasks and their neural foundations. Current projects analyze real-time brain activity to refine educational interventions and improve human-machine interaction.
Marcelo Mattar is an Assistant Professor of Psychology and Neural Science at New York University, leading the Mattar Lab. His research focuses on the neural computations underlying memory, decision-making, and reinforcement learning. He holds a Ph.D. in Psychology from the University of Pennsylvania and has held academic positions at NYU, UC San Diego, and postdoctoral roles at Princeton University and the University of Cambridge. His work bridges computational neuroscience and artificial intelligence, aiming to model how the brain uses internal models for planning and decision-making. Education: Ph.D. in Psychology (Computational and Cognitive Neuroscience), University of Pennsylvania, 2016 M.A. in Statistics, University of Pennsylvania, 2016 B.A. in Electronics Engineering, Instituto Tecnologico de Aeronautica, Brazil, 2010 Research Interests: The lab develops mathematical models of learning and decision-making, leveraging reinforcement learning, Bayesian statistics, and neural networks. Experiments involve human behavioral studies and neuroimaging, with collaborations in animal electrophysiology and computational psychiatry. Key Contributions: His work explores how episodic memory and hippocampal replay support flexible decision-making. Recent studies highlight parallels between human cognition and AI systems, such as language models' metacognitive abilities and brain-inspired algorithms. Awards: Newton International Fellowship, Royal Society (2018–2019) Lab Team: The lab includes postdocs, PhD students, and undergraduates from diverse fields like cognitive science, neuroscience, and computer science. Current members are listed on the lab's website. Lab Location: Meyer Hall, 6 Washington Place, New York, NY 10003.
Mads Albertsen is a Professor in the Department of Chemistry and Life Sciences at the Faculty of Engineering and Science, Aalborg University, Denmark. He leads the Albertsen Lab and is a key member of the Center for Microbial Communities. His research focuses on high-throughput DNA sequencing methods to explore uncultivated microbes and populate the tree of life. He is actively involved in major interdisciplinary projects such as NanoEat , Microflora Danica , and DarkScience , funded by the European Research Council, Villum Foundation, and Poul Due Jensen Foundation. His research interests span metagenomics , long-read sequencing , bioinformatics , microbial ecology , and environmental biotechnology . He develops cutting-edge methods to improve throughput in microbial genome recovery and applies them to diverse areas including wastewater treatment, human microbiome studies, and infectious disease diagnostics. His work has significant implications for public health and sustainability. The recent publications highlight a strong trend in long-read sequencing (Oxford Nanopore), metagenome-assembled genomes (MAGs) , and microbial dark matter . His team has published high-impact papers in Nature , Nature Methods , and Nature Communications , with applications in environmental systems and clinical diagnostics, including SARS-CoV-2 and bloodstream infections. His scientific awards include: The Grundfos Prize (2021) The Fritz Kaufmann Prize (2021) The Rising Star Award by IWA & ISME (2016) Research Result of the Year in Denmark (2015) The Spar Nord Fond Research Prize (2015) Mads Albertsen advises numerous PhD students, leads externally funded research projects, and is involved in technology transfer through his co-founding of DNASense ApS (2014–2020). He also serves on scientific advisory boards and contributes to public policy, including as a member of the Danish SARS-CoV-2 variant risk-assessment group. He teaches courses in Data Science, Bioinformatics, Genomics, and Environmental Microbiology at Aalborg University. His lab, the Albertsen Lab , is part of the Center for Microbial Communities , a leading research center focused on microbial systems biology and environmental applications. The lab collaborates extensively with national and international partners in academia, industry, and public health institutions.
Teresa Bonacci is an Associate Professor in the Department of Biology, Ecology and Earth Sciences at the University of Calabria (UNICAL), where she conducts research and teaches in zoology with a focus on entomology. She is also the Scientific Director of the Zoology Museum within the university's museum system (SIMU). Her academic affiliations include membership in the PhD School of Life Science and Technology and leadership roles in degree program coordination. Laurea in Natural Sciences, University of Calabria PhD in Animal Biology, University of Calabria Socrates/Erasmus Scholarship, University of Kiel, Germany Research Grant (Assegno di ricerca), SSD BIO/05, University of Calabria National Scientific Qualification for Full Professor (I fascia) Her research spans applied and medico-veterinary entomology, forensic entomology, and conservation biology. She investigates saproxylic beetles (e.g., Cucujus spp.), pollinators (bees, flies, beetles), and insect behavior, especially in forensic contexts such as post-mortem interval estimation and myiasis. Her work integrates taxonomy, morphology, ecology, and chemical signaling, often in collaboration with chemists, legal experts, and conservation agencies. She has published extensively in high-impact journals, with over 80 scientific publications and strong citation metrics. The most recent articles reflect a multidisciplinary trend, combining taxonomy, forensic science, biodiversity monitoring, and veterinary entomology. Topics include the discovery of new insect species in Italy, the role of beetles in decomposition, insect damage in cultural heritage, and myiasis in domestic and wild animals. These works highlight her expertise in both fundamental zoological research and practical applications in forensics and conservation. Scientific Contributions: Over 80 scientific publications Scopus h-index: 15; Google Scholar h-index: 20 Key researcher in saproxylic beetle conservation Pioneer in forensic entomology studies in Southern Italy Active collaborator with legal and medical institutions She supervises numerous PhD and master's students and has directed over 90 theses. Her teaching responsibilities include courses in Zoology, Entomology, Forensic Entomology, and Medical-Veterinary Entomology. She is deeply involved in student mentorship, thesis supervision, and academic service, including examination boards and curriculum development. She also leads biodiversity monitoring projects in Calabrian national parks and has contributed to the development of machine learning tools for insect identification. Her research team collaborates with national and international institutions, including the CNR, University of Milan, and forensic pathology units. She leads projects on bioindicators, insect-plant interactions, and the impact of climate change on mountain species. The Zoology Museum under her direction supports both research and public outreach.
Adam Jatowt is a Professor and Head of the Data Science group at the Department of Computer Science, University of Innsbruck. He also serves as Deputy Head of the Digital Science Center and Research Center for Digital Humanities. His academic career spans roles at Kyoto University (2010-2020), National Institute of Advanced Industrial Science and Technology (AIST), and visiting positions at Karlsruhe Institute of Technology, University of La Rochelle, and University of California Berkeley. Research interests focus on temporal aspects of NLP/IR, computational history, large language models, and future forecasting. He leads projects combining digital humanities with advanced AI techniques, including temporal validity assessment and hint generation systems. Recent publications (2025) emphasize LLM applications in temporal analysis, QA systems, and energy sector digitalization. His work has been recognized through awards like the Friedrich Wilhelm Bessel Research Award (2024) and top-cited paper distinction in Information Sciences. He actively organizes conferences like ECIR 2026 and Text2Story workshops. Key contributions include developing WikiHint dataset, PlausibleQA framework, and tools like Rankify. His research also addresses societal challenges through ESG rating prediction and medical LLM applications.
