David Williamson Shaffer is the Sears Bascom Professor of Learning Analytics and Vilas Distinguished Achievement Professor of Learning Sciences at the University of Wisconsin-Madison's Department of Educational Psychology. He is also a Data Philosopher at the Wisconsin Center for Education Research. His work focuses on merging statistical and qualitative methods to model complex human collaboration. Shaffer holds an AB in History and East Asian Studies from Harvard University (1987), and MS/PhD in Media Arts and Sciences from MIT (1996/1998). Before academia, he was a teacher, curriculum developer, and game designer. His research emphasizes Quantitative Ethnography —a methodology combining big data analysis with cultural interpretation. Key contributions include Epistemic Network Analysis (ENA) and over 250 publications, including influential books like How Computer Games Help Children Learn (2006) and Quantitative Ethnography (2017). Awardees of the EU Marie Curie Fellowship (2008) and Spencer Foundation Fellowship (2003), Shaffer's work has been presented globally at conferences like Learning Analytics & Knowledge and Computer Supported Collaborative Learning. His interdisciplinary approach bridges education, data science, and humanities, addressing challenges in authentic STEM experiences, collaborative learning analytics, and culturally responsive pedagogy.
Eytan Adar is a Professor of Information and Computer Science at the University of Michigan, holding dual appointments in the School of Information and the College of Engineering's Electrical Engineering and Computer Science department. His work sits at the intersection of human-computer interaction and artificial intelligence, focusing on large-scale systems analysis and novel interface design. Adar's research spans multiple domains including social media analysis (Twitter, Reddit), academic citation networks, meme propagation, information extraction, and political networks. His methodological expertise includes data mining, data visualization, and graph-based network analysis. His work often operates at internet scale, examining language, creativity, social network dynamics, and text production. His recent publications reveal a strong focus on AI-human collaboration, with particular attention to generative AI interfaces, visualization techniques for complex data, and ethical considerations in AI systems. His work shows a consistent pattern of bridging theoretical insights with practical system implementations. Best Paper Award at ProtoAI: Model-Informed Prototyping for AI-Powered Interfaces, IUI'21 Honorable Mention Award at CHI'24 for feminist interaction techniques research Best Paper Award at ICWSM'18 for Wikipedia language edition analysis Best Paper Award at ICML 2016 Workshop for neural language model visualization Best Student Paper at WSDM'09 for web dynamics research Best of CHI at CHI 2008 for web revisitation patterns analysis Adar has advised numerous PhD students who have gone on to prominent positions at organizations including Google, Apple, RAND, Northwestern University, and Stanford. His research is generously supported by the NSF, IARPA, NIH, the Education Department, and major technology companies including Adobe, Microsoft, Facebook, Google, and Yahoo. He is also a founder of the International Conference on Web and Social Media (ICWSM) and has served as Co-General Chair for WSDM and Co-Program Chair for UIST.
Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).
Cathryn Carson is a Professor in the Department of History at the University of California, Berkeley. Her work bridges the philosophical, cultural, and political dimensions of 20th-century science, with a focus on theoretical physics, nuclear history, and the integration of social sciences and humanities into engineering education. Education: AB in History and Philosophy of Science from University of Chicago (1990) AM in Physics from Harvard University (1993) PhD in History of Science from Harvard University (1995) Her research explores the interplay between science and philosophy, particularly in Germany and the U.S., alongside the institutionalization of data science. She teaches graduate and undergraduate courses, including Berkeley’s Data Science major’s Human Contexts and Ethics of Data course. Scientific Awards: Berkeley Collegium Award for Excellence in Undergraduate Education (2017) Distinguished Service Award, Division of Social Sciences (2014) Carol D. Soc Distinguished Graduate Student Mentoring Award (2014) Fellow of the American Association for the Advancement of Science Fellow of the American Physical Society Mellon New Directions Fellowship NSF CAREER Award Alexander von Humboldt Foundation Research Fellowship Member, Institute for Advanced Study, Princeton Carson has served in multiple leadership roles, including Associate Dean of Social Sciences, founding Interim Director of the D-Lab (Social Science Data Laboratory), and Faculty Lead of Berkeley’s Data Science Education Program. She is currently accepting students for advising and contributes to campus governance through roles in the Academic Senate.
Joydeep Biswas is an Associate Professor in the Computer Science Department at the University of Texas at Austin, where he serves as the Director of the Autonomous Mobile Robotics Laboratory (AMRL). He is also affiliated with Texas Robotics, the UT Machine Learning Laboratory, and UT Good Systems. Previously, he was an Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst. Dr. Biswas earned his PhD in Robotics from Carnegie Mellon University in 2014 and his B.Tech in Engineering Physics from the Indian Institute of Technology Bombay in 2008. His educational background has provided him with a strong foundation in both theoretical and applied aspects of robotics and artificial intelligence. Dr. Biswas's research focuses on enabling long-term autonomy for mobile robots operating in human environments. His work spans robot perception, motion planning, control systems, and AI, with the ultimate goal of creating self-sufficient autonomous mobile robots that can perform tasks accurately and robustly in real-world settings. He is particularly interested in perception, planning, and failure recovery for autonomous mobile robots, which supports his vision of having autonomous service mobile robots deployed at campus-to-city scale, both indoors and outdoors, performing assistive tasks over deployments spanning years. His IJCAI 2019 Early Career Spotlight talk summarizes much of his research to date and ongoing interests. His recent research has shown a strong trend toward social navigation, human-robot interaction, and the application of machine learning techniques to robotics problems. There's a clear progression from fundamental robotics research toward more complex, real-world applications that require robots to understand and navigate human social spaces effectively. His work increasingly integrates large language models and other advanced AI techniques with traditional robotics approaches, as evidenced by his recent publications on topics like preference-conditioned navigation, social navigation benchmarks, and instruction-following navigation systems. Dr. Biswas has received numerous prestigious awards including the NSF CAREER Award (2021), J.P. Morgan Faculty Research Award (2019), Amazon Research Award (2019), and a grant from Northrop Grumman Mission Systems (2018). These awards recognize his innovative contributions to the field of robotics and autonomous systems. As a dedicated educator and mentor, Dr. Biswas actively supervises PhD and master's students, with his PhD student Sadegh Rabiee winning the student poster award at the Northrop Grumman University Symposium 2019. He has secured significant grant funding from the National Science Foundation for projects including 'Introspective Perception and Planning for Long-Term Autonomy' and 'Interactive Synthesis and Repair For Robot Programs,' demonstrating his ability to secure competitive research funding and his commitment to advancing the field. Dr. Biswas leads the Autonomous Mobile Robotics Laboratory (AMRL), which serves as a hub for interdisciplinary research in mobile robotics. The lab has developed notable resources such as the UT Campus Object Dataset (CODA) for 3D perception research and SOCIALGYM, a framework for benchmarking social robot navigation. His team regularly deploys robots on the UT Austin campus and in urban environments to test and refine their approaches in realistic settings, bridging the gap between simulation and real-world application.
John Gallagher is Associate Professor in English and Information Sciences at UIUC. His research examines how writers adapt to participatory audiences in digital environments, including social media interactions and AI writing tools. Using case studies and computational methods, he explores algorithmic audiences, ethical implications of AI, and technical communication in institutional contexts. He teaches courses in professional writing, digital rhetoric, and research methodologies. Recent projects analyze content creators' narratives about platform algorithms, inclusive emoji design, and academic integrity challenges posed by generative AI.
Douglas D. Ready is an Associate Professor of Education and Public Policy at Teachers College, Columbia University , where he serves as Director of the Consortium for Policy Research in Education (CPRE-TC). His research focuses on the intersections of education policy, social policy, and educational equity, particularly how policies influence socio-demographic disparities in cognitive development. Research Interests: Ready’s work examines the structural determinants of educational equity, including school choice architecture, personalized learning, early childhood education, and the impacts of technology on instruction. He has published extensively in journals such as Educational Evaluation and Policy Analysis and Sociology of Education . Editorial Roles: Ready contributes to the academic community as a member of the editorial boards of Educational Evaluation and Policy Analysis and American Educational Research Journal . Key Projects: He has led analyses of programs like Teach to One: Math and Pre-K for All , exploring their effects on student outcomes and equity.
Qian Yang is an Assistant Professor in Information Science at Cornell University, with a faculty appointment in Computer Science. Her research focuses on human-AI interaction, designing AI applications for healthcare, autonomous systems, and UX design. She holds a PhD in Human-Computer Interaction from Carnegie Mellon University and has industry experience in design consultancy (2007–2014). Yang co-directs the Cornell Digital and AI Literacy Initiative and is a Senior Fellow at the Cornell Brooks Tech Policy Institute. Her work emphasizes bridging AI technologies with societal needs, supported by awards like the Schmidt Futures AI2050 Fellowship. She leads the DesignAI research group, focusing on AI-driven design methods and tools for practitioners. Education: PhD in HCI (Carnegie Mellon), M.S. in HCI (CMU), M.Des in Design, B.Eng in Industrial Design (Shanghai Jiao Tong University). Research interests include AI ethics, healthcare decision support systems, and context-aware mobile services. Notable contributions include: Developing AI systems for life-critical healthcare decisions (e.g., artificial heart implants) Innovating UX design methods for integrating AI into practice Advancing human-centered AI evaluation frameworks Awards include the SIGCHI Outstanding Dissertation Award and AI2050 Fellowship. She actively collaborates across disciplines, with work published in top HCI venues like CHI and ACM Transactions.
Professor Kay O'Halloran serves as Chair Professor and Head of Department of Communication and Media within the School of the Arts at the University of Liverpool since August 2019. She concurrently holds the position of Co-Director for the Digital Media and Society Institute (DMSI), demonstrating significant leadership across academic and research domains. Her career spans prestigious institutions including Curtin University (2013-2019) and National University of Singapore (1998-2013), where she directed the Multimodal Analysis Lab and served as Deputy Director of the Interactive & Digital Media Institute. PhD from Murdoch University (1996) Postdoctoral position at Martin Luther University (1997-1998) Visiting Distinguished Professor at Shanghai Jiaotong University (2017-2020) Professor O'Halloran's research focuses on multimodal discourse analysis, particularly the interaction of language with visual and mathematical resources. Her pioneering work in systemic functional multimodal discourse analysis (SF-MDA) has significantly impacted mathematics education and digital communication studies. Current research emphasizes digital tools for multimodal analysis and mixed methods approaches to big data analytics, addressing contemporary challenges in misinformation and public health communication. Her recent publications reveal strong thematic concentration in pandemic-related communication analysis, misinformation resistance mechanisms, and multimodal argumentation across social and cultural contexts. The 15 most recent articles demonstrate consistent application of multimodal frameworks to urgent societal issues including public health crises, political discourse, and digital literacy challenges. Founding editor of Routledge Studies in Multimodality book series (57+ volumes) Over 150 publications in leading international journals 50+ plenary/keynote presentations globally Competitive funding from National Research Foundation, MOE Singapore, US Air Force, ARC, NHMRC, and others Professor O'Halloran has directed interdisciplinary research teams comprising social scientists, computer scientists, and designers. Her leadership extends to developing commercial multimodal analysis software (Multimodal Analysis Image and Video) adopted internationally. Current projects include Eurovision 2023 wellbeing evaluation and COVID-19 misinformation immunity development, demonstrating continued relevance to contemporary societal challenges.
Prof. Dr. Nicole Ondrusch is a Professor at Heilbronn University (HHN) within the Faculty of Computer Science. She specializes in teaching methodological fundamentals of software engineering, including ERP systems, Design Thinking, Change Management, and digital transformation. Her research focuses on educational concepts for computer science technologies and future-relevant skills. Key Roles and Projects: Member of BW-CAR doctoral center Organizer of Barcamp Heilbronn, an unconference teaching project fostering student teamwork Principal investigator in funded projects like DigiTrans (digital transformation education) and DEV:GAMES (educational game development) SAP Academic Board DACH spokesperson since 2021 Research Interests: Her work emphasizes innovative teaching methods such as Design Thinking, agile project implementation, and digital experimentation. She explores ethical AI education, interdisciplinary collaboration, and the societal impact of digital transformation. Nicole also develops practical teaching tools like virtual escape rooms and game-based learning frameworks. Grants & Partnerships: Funded by DAAD (DigiTrans), Stiftung Innovation, and others Collaborates with industry partners like SAP and local IT organizations (ConnectIT) Labs & Teams: She leads the Lab:D initiative, developing digital teaching platforms, and co-organizes the Barcamp, a student-led event integrating real-world project management and community building.
Ying Xu is an Assistant Professor at the Harvard Graduate School of Education (HGSE), specializing in the design of AI technologies to support children's language, literacy, STEM learning, and well-being. Her research emphasizes creating AI systems that act as interactive learning companions and language partners for children while fostering human-AI collaboration with educators and families. She holds a Ph.D. in Language, Literacy, and Technology from the University of California, Irvine, and previously served as an Assistant Professor at the University of Michigan from 2022 to 2024. Her work focuses on understanding how AI can complement human interactions, particularly through conversational agents integrated into media like books and educational TV programs. Collaborations include partnerships with PBS KIDS, GBH Education, and Sesame Workshop. Funded by organizations such as the National Science Foundation and Schmidt Futures, her research bridges developmental psychology, education, and human-computer interaction. Xu's studies highlight AI's potential for personalized learning while addressing ethical considerations like AI literacy and social impact. Key achievements include numerous best paper awards and recognition as an Early Career Interdisciplinary Scholar by SRCD. Her interdisciplinary approach involves designing technologies that reflect community values and linguistic/cultural diversity, ensuring equitable access to AI-driven educational tools. Xu advocates for balanced AI integration in children's lives, emphasizing the need for transparency about AI's limitations and the importance of maintaining human connections. She explores how AI can empower stakeholders (e.g., educators, parents) to co-create technologies tailored to their needs, ensuring AI serves as a complement—not replacement—for human interaction. Current projects investigate conversational AI's design principles, children's perceptions of AI, and strategies for fostering critical evaluation of AI-generated content. She also examines how AI affects social interactions and developmental processes, advocating for ethical guidelines to maximize benefits while mitigating risks.
Michael S. Horn is a Professor of Learning Sciences and Computer Science at Northwestern University, serving as Program Coordinator for Learning Sciences. He holds a PhD in Computer Science from Tufts University and a ScB in Computer Science from Brown University. His research focuses on the intersection of human-computer interaction and learning, emphasizing the use of emerging technologies in museums, classrooms, and informal settings. Notable projects include multi-touch tabletops in natural history museums, tangible programming languages for early education, and the TIDAL Lab’s innovative exhibits like Build-a-Tree and DeepTree. Education background includes: PhD in Computer Science (Tufts University, 2009) MS in Computer Science (Tufts University, 2006) ScB in Computer Science (Brown University, 1997) Research interests span tangible interaction design, computational literacy, and museum-based learning. He has led projects such as the ‘Energy Monsters’ board game and the TunePad music-coding platform. His work integrates technology with pedagogical practices to foster collaborative and exploratory learning environments. Active collaborations include the Computer History Museum and the California Academy of Sciences. Advising contributions include mentoring doctoral students like Dr. Mmachi Obiorah and Pei-Yi. His lab, TIDAL, explores interactive technologies for education, with grants from NSF and industry partnerships. Recent articles highlight innovations in computational thinking integration, music-coding hybrid practices, and AI-driven qualitative analysis.
Mizuko (Mimi) Ito is a cultural anthropologist and learning scientist at the University of California, Irvine, serving as Director of the Connected Learning Lab and holder of the John D. and Catherine T. MacArthur Foundation Chair in Digital Media and Learning. She previously held research appointments at Keio University and the University of Southern California. Ito earned dual PhDs in Education and Anthropology from Stanford University and a BA in East Asian Studies from Harvard University. Education: PhD in Education, Stanford University PhD in Anthropology, Stanford University Bachelor's Degree in East Asian Studies, Harvard University Research Interests: Ito's work focuses on leveraging youth interests and digital media to foster equitable, socially connected learning. Her research spans mobile media culture in Japan, youth social media engagement in the US, and global adoption of children's media. She developed the connected learning framework, emphasizing youth-centered, equity-oriented approaches to education in the digital age. Grants & Partnerships: Ito has secured funding from major organizations including the MacArthur Foundation, Bill and Melinda Gates Foundation, National Science Foundation, and Microsoft Research. She co-founded the Connected Learning Alliance to advance research and impact in technology and learning. Awards: Recipient of the Jan Hawkins Award for Early Career Contributions (AERA) Labs & Initiatives: Directs the Connected Learning Lab at UC Irvine, which explores opportunities and risks of digital media in education. The Lab collaborates with global networks to design inclusive learning ecosystems.
Cecilia O. Alm is a Professor in the Department of Psychology within the College of Liberal Arts at Rochester Institute of Technology (RIT), where she serves as the Artificial Intelligence Program Director. She holds multiple leadership roles including Director of the Center for Human-aware AI and Director of the Computational Linguistics and Speech Processing Lab (CLaSP). Her institutional affiliations span the School of Information, Ph.D. Programs in Cognitive Science and Computing and Information Sciences, Department of Computer Science, and MS in Data Science program. Dr. Alm earned her Ph.D. from the University of Illinois at Urbana-Champaign. Her research focuses on human-centered artificial intelligence with particular emphasis on linguistic and multimodal sensing, affective computing, and natural language processing. She investigates how AI systems can better understand and respond to human communication through multimodal dialogue processing, with applications in accessibility, education, and healthcare. Her recent publications demonstrate a strong trend toward developing inclusive AI systems, particularly through projects addressing Deaf community needs (MULTICOLLAB-ASL), subtle emotion recognition (FUSE corpus), and bias mitigation in NLP. The work consistently integrates multimodal data streams (speech, gaze, gesture) to create more responsive human-AI interaction frameworks. Current research directions emphasize diversity in AI education, visual prosody in sign languages, and human-in-the-loop AI development. Dr. Alm leads several significant NSF-funded initiatives including the AWARE-AI program, IRES AI-PROWIL international research experience, and collaborative projects with Gallaudet University focused on Deaf scientist-centered AI research. She has secured over $2.5 million in external funding for her work on human-aware AI systems. She directs the CLaSP lab which provides research opportunities for PhD, MS, and undergraduate students, with graduates employed at major technology companies including Amazon, Apple, Microsoft, and Facebook. The lab focuses on real-world AI applications in accessibility, human-robot interaction, and multimodal communication systems.
Dr. Zara Ersozlu is a Senior Lecturer in Mathematics Education within the School of Education at the University of Newcastle, Australia. With a distinguished international career spanning multiple continents, she has held academic positions at prestigious institutions including North Carolina State University (USA), Gazi and Gaziosmanpasa Universities (Turkey), National Taiwan Normal University (Taiwan), The University of Western Australia, Murdoch University, and Deakin University. Her academic journey includes tenured positions as an Associate Professor and leadership roles as Department Head and Chair in teacher education disciplines. Currently, she teaches undergraduate and postgraduate courses in mathematics education, including Effective Pedagogies in Primary Mathematics, K-6 Mathematics, K-6 Numeracy, and Digitally Supported Learning. Dr. Ersozlu earned her Doctor of Philosophy from Firat University in Turkey and her Master of Art from Sakarya University. Her extensive academic preparation is complemented by five years of practical teaching experience in public schools prior to entering academia. This blend of theoretical knowledge and practical classroom experience informs her approach to teacher education and educational research. At the broadest level, Dr. Ersozlu's research investigates solutions to real-life problems impacting people's well-being, success, and capacity to achieve. Her scholarly work spans primary and secondary mathematics education, the psychology of mathematics (including metacognition, self-regulation, and anxiety), cross-cultural educational studies, teacher education, virtual simulated learning environments, and educational assessment. She has increasingly focused on the transformative potential of AI and machine learning in education, exploring how these technologies alter teaching, learning, and research processes. Her methodological expertise encompasses both quantitative and qualitative approaches, allowing her to effectively analyze both small and large educational datasets. Analysis of Dr. Ersozlu's recent publications reveals a strong emphasis on mathematics anxiety, teacher education, and the integration of technology in learning environments. Her work demonstrates a consistent focus on practical applications of educational research to address real-world challenges in mathematics education. The interdisciplinary nature of her research connects educational psychology, technology integration, and cross-cultural perspectives, with particular attention to how these elements intersect in teacher preparation and student learning outcomes. 2023 ATEA Research Recognition Award from the Australian Teacher Education Association 2021 Fellow of the Higher Education Academy (Advance HE, UK) 2010 Fellowship Program for Postdoctoral Researchers from the Council of Higher Education of Turkey Dr. Ersozlu is deeply committed to mentoring the next generation of scholars, currently supervising four PhD students and having successfully guided ten students to completion. Her grant portfolio includes significant funding for projects such as Best Practice Guidelines for RPL in Initial Teacher Education Programs ($60,000), Exploring the Reciprocal Relationship Between Mathematics Anxiety and Mathematical Resilience ($2,599), and multiple conference travel awards. She serves as an Associate Editor for several prominent journals including the International Electronic Journal of Mathematics Education and as Editor for Interdisciplinary STEM Education. Her editorial work reflects her standing as a respected voice in mathematics education research. Dr. Ersozlu's academic leadership extends to her role in developing innovative teaching approaches that integrate virtual simulation technology and learning analytics. Her work with TeachLivE™, a mixed-reality classroom simulation platform, demonstrates her commitment to creating authentic learning experiences for teacher education students. Through these initiatives, she bridges the gap between educational theory and classroom practice, preparing future educators to effectively implement evidence-based teaching strategies in diverse learning environments.
