William S. Horton (Sid) is an Associate Professor in the Department of Psychology at Northwestern University , where he has taught since 2005 and directed the Cognition and Communication Lab (Cresap 108). Starting in September 2025, he will serve as Chair of the Department of Linguistics . His research focuses on socio-cognitive mechanisms in language use, particularly discourse pragmatics , perspective-taking , and non-literal language processing . Education: B.S. in Psychology/German from Duke University (1991), M.A. and Ph.D. in Cognitive Psychology from University of Chicago (1994/1999) Previous roles: Postdoctoral research at SUNY-Stony Brook, Cognitive Aging at Georgia Tech Research trends from his 20+ years of publications include common ground , memory processes , figurative language , and age-related communication changes . His work increasingly incorporates computational text analysis and real-time digital communication studies. Awards : Fellow, Society for Text and Discourse Students : Supervised Ph.D. theses on conversational alignment, common ground activation, and digital communication. Undergraduate honors projects explore inhibitory deficits, speech internalization, and perspective-taking in bilingualism. Cognition and Communication Lab investigates language processing in spoken/written contexts using experimental methods and computational models.
Professor Heather Ferguson is a distinguished cognitive psychologist at the University of Kent's School of Psychology, where she has built an impressive academic career since her appointment as Lecturer in 2009. Promoted to Professor in 2018, she leads groundbreaking research examining the cognitive basis of social communication across the lifespan. Her work bridges cognitive psychology, neuroscience, and social cognition, with particular expertise in perspective-taking, theory of mind, and the interface between cognitive processes and social interaction. Her research primarily investigates how we access and represent other people's perspectives during communication, using methodologies including eye-tracking, EEG, and reaction time measurements. Key questions driving her work include: How do people understand and predict events based on others' mental states? What happens when these conflict with our own knowledge? How do social abilities relate to cognitive skills like memory and inhibitory control? How does aging affect social cognition? Her work has significant implications for understanding autism spectrum disorder, social development, and cognitive aging. Professor Ferguson's recent publications reveal a strong focus on perspective-taking across the lifespan, social cognition in autism, the cognitive effects of fiction reading, and the neural mechanisms underlying empathy. Her research demonstrates consistent methodological rigor through pre-registered studies and meta-analyses, with particular attention to developmental trajectories from adolescence through older adulthood. Psychonomic Society Early Career Award (2019) Open Science Framework Pre-registration Challenge award (2018) Cognitive Neuroscience Society Postdoctoral Fellow Award (2018) University of Kent Prize for Research (2016) Kent Union Teaching Award for 'Best Teacher' (2012) Professor Ferguson actively supervises multiple PhD students and has secured substantial research funding, including a €1.5 million ERC Starting Grant and multiple Leverhulme Trust grants. Her work with the Cognitive basis of Social Communication and Ageing (COGSOCOAGE) research group has produced influential findings on social cognition across the lifespan. She serves as Associate Editor for the Journal of Experimental Psychology: Learning, Memory & Cognition and on the editorial board of Cognition, while also mentoring early-career researchers through the Eastern Arc Mentoring Scheme.
Erik Willcutt is a Professor in the Department of Psychology and Neuroscience at the University of Colorado Boulder. His research focuses on the genetic and neurobehavioral underpinnings of ADHD, learning disabilities, and developmental psychopathologies. He holds positions at the Institute for Behavioral Genetics and the Center for Neuroscience. Education: PhD in Psychology from the University of Denver (1998). Research Interests: Etiology and assessment of ADHD, reading disabilities, and developmental psychopathologies. His work integrates behavioral genetics, neuroimaging, and longitudinal twin studies to understand cognitive and psychiatric disorders. Key topics include neuroanatomical correlates of ADHD, genetic influences on dyslexia, and comorbidity between learning disabilities and psychiatric conditions. Publications highlight advanced methods like genome-wide association studies (GWAS) and phenotype harmonization (e.g., Rosetta method). His work bridges molecular genetics with clinical psychology, emphasizing translational research. Lab/Affiliations: Active in the Institute for Behavioral Genetics and collaborates with interdisciplinary teams studying neurodevelopmental disorders. Office located at Muenzinger D451B.
Ricardo Gutierrez-Osuna is a Professor in the Department of Computer Science and Engineering at Texas A&M University, part of the College of Engineering. He leads the PSI Lab and focuses on machine learning, speech processing, and digital health applications. His research spans topics like wearable sensors, foreign accent conversion, and physiological monitoring. Education: Ph.D. (Computer Engineering, NC State, 1998), M.S. (Computer Engineering, NC State, 1995), B.S. (Electrical Engineering, Universidad Politécnica de Madrid, 1992). Research interests include intelligent sensors, speech processing, machine learning, neuromorphic computation, and mobile robotics. His work bridges computer science and biomedical engineering, with applications in health monitoring and human-computer interaction. Awards: NSF CAREER Award (2002) Ramón y Cajal Award (2005-2010) Texas A&M Barbara and Ralph Cox Fellow (2009) Multiple teaching awards (2009-2010) His lab develops innovative technologies like stress-detecting wearables, biofeedback games, and systems for non-native speech improvement. He collaborates on projects involving voice conversion, glucose prediction algorithms, and multi-modal sensing devices.
Alison J. Mackey is Professor and Chair of the Department of Linguistics at Georgetown University, College of Arts and Sciences. She is a leading scholar in second language acquisition (SLA), with a focus on interaction, feedback, research methodology, and language learning across the lifespan. Her research interests include second language acquisition , task-based language teaching , research methodology , interaction and corrective feedback , and language learning in children and adults . She has published extensively in top-tier journals and book series, shaping methodological standards in the field. Her recent publications reflect a strong trend in methodological rigor , interactionist approaches , and practical applications of SLA research. Themes include data elicitation , stimulated recall , task design , and pragmatic development , spanning both theoretical and classroom-based inquiry. Mildenberg Prize (2012) for The Handbook of Second Language Acquisition American Association for Applied Linguistics Distinguished Scholarship and Service Award International Association of Task-based Language Learning and Teaching Distinguished Achievement Award CHOICE Outstanding Academic Title (2012) Alison Mackey has advised numerous scholars through co-authorship and editorial leadership. She is Editor-in-Chief of Cambridge University Press Annual Review of Applied Linguistics and Editor of the Routledge Second Language Research series, guiding the publication of cutting-edge research. While specific grants are not listed, her editorial work and high citation count (>35,000) reflect significant research impact and funding support. She leads and contributes to major research initiatives such as the IRIS Repository , promoting open-access research instruments in SLA. Her work fosters collaboration across institutions and supports methodological transparency and replication in the field.
Georgia Zellou is an Associate Professor in the Department of Linguistics at the University of California, Davis, where she co-directs the Phonetics Lab and conducts award-winning research at the intersection of phonetics, speech perception, and human-AI interaction. Her work investigates how phonetic detail is cognitively represented through variations in speech production, with significant contributions to understanding speech alignment with voice assistants, face-masked speech intelligibility, and cross-linguistic perception of synthetic voices. Her academic credentials include a Ph.D. in Linguistics from the University of Colorado at Boulder (2012), an M.A. in Linguistics from Stony Brook University (2007), and a B.A. in Linguistics & Anthropology from the University of Florida (2005, Cum Laude, Phi Beta Kappa). Ph.D., Linguistics, University of Colorado at Boulder (2012) M.A., Linguistics, Stony Brook University (2007) B.A., Linguistics & Anthropology, University of Florida (2005) Professor Zellou's research program centers on laboratory phonology approaches to real-world communication challenges, examining how acoustic-phonetic details influence speech perception across contexts. Her studies span speech alignment with voice-AI systems (e.g., Amazon Alexa), sociophonetic variation in bilingual speech, and the cognitive mechanisms underlying perceptual compensation for coarticulation. She employs experimental methods including eye-tracking, acoustic analysis, and perceptual testing to uncover how phonetic variation functions pragmatically in human communication and human-machine interaction. Analysis of her 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) human-AI voice interaction dynamics, including prosodic alignment and social evaluation of TTS voices; (2) intelligibility optimization in challenging contexts (face masks, clear speech for diverse listeners); and (3) cross-linguistic phonetic variation in vowelless words and consonant clusters. These works consistently bridge theoretical phonology with applied speech technology, demonstrating how fine-grained phonetic detail influences communication effectiveness in both human-human and human-machine contexts. Her scientific recognition includes: Fulbright Scholar (2022) for research in France Chancellor’s Award for Excellence in Undergraduate Mentoring (2019) Fellow of the Linguistic Society of America (2020) Amazon Faculty Research Award (2019) for Alexa-related speech studies Dean’s Fellow designation at UC Davis (2020-2023) Professor Zellou maintains an active mentoring practice recognized with the Chancellor’s Award, supervising undergraduate researchers in the Phonetics Lab while teaching core linguistics courses from introductory to advanced graduate levels. Her research program is supported by competitive grants including NSF funding, Amazon Research Awards, and UC Davis internal grants (Hellman Foundation, ISS Junior Faculty Grant), reflecting the translational value of her work for speech technology development. She has co-directed major initiatives including the 2019 LSA Linguistic Institute. The Phonetics Lab she co-leads serves as a hub for experimental phonetics research, focusing on speech production-perception relationships through projects investigating vocal accommodation to voice assistants, nasal coarticulation dynamics, and cross-linguistic prosody. Current collaborations with industry partners aim to implement human speech adaptation principles into voice assistant design to enhance naturalness and engagement.
Elaine Treharne serves as the Roberta Bowman Denning Professor of Humanities at Stanford University, holding primary appointment in the Department of English with courtesy appointments in German Studies and Comparative Literature. She concurrently acts as Senior Associate Vice Provost for Undergraduate Education and Director of Curriculum, while directing Stanford Text Technologies—a major initiative exploring textual transmission across historical periods. Her leadership extends to co-directing SILICON and spearheading NEH-funded projects that redefine digital approaches to manuscript studies. Her academic foundation includes a B.A. in English Language and Literature (First Class Honors) from the University of Manchester (1986), a Master of Archive Administration from the University of Liverpool (1987), and a Ph.D. in English from the University of Manchester (1992). This archival training underpins her dual expertise in traditional manuscript scholarship and digital innovation. Treharne's research pioneers intersections between medieval materiality and contemporary technology, investigating the haptic experience of medieval books, AI applications for manuscript analysis, and the long history of text technologies. She challenges conventional periodization through projects like 'Disrupting Categories, 1050-1250' while developing computational frameworks for fragmentology and textual distortion. Her work consistently bridges paleography with digital methodology to examine how writing systems shape cultural memory. Recent publications reveal a decisive shift from foundational medieval scholarship toward integrative digital-humanities frameworks, with increasing emphasis on phenomenological approaches to both physical and digital texts. This trajectory culminates in current projects applying machine learning to manuscript transmission patterns and developing ethical guidelines for digital archival tools. Her scientific recognition includes: Fellow of the Society of Antiquaries Fellow of the Royal Historical Society Honorary Lifetime Fellow of the English Association (former Chair and President) Fellow of the Learned Society of Wales American Philosophical Society Franklin Fellow Princeton Procter Fellow Fellow of the Stanford Clayman Institute for Gender Studies Treharne actively supervises graduate students in early literature, Book History, and Digital Humanities while securing major grants including NEH funding for Stanford Global Currents, AHRC support for the Production and Use of English Manuscripts project, and Stanford Impact Labs fellowship for archival tool development. She maintains commitment to ethical scholarly environments through her leadership in VPUE initiatives and digital pedagogy. She directs the Stanford Text Technologies initiative hosting the annual Collegium series, co-directs SILICON for internet longevity research, and leads specialized projects including 'Digital Ker' for Anglo-Saxon manuscript cataloging and 'Medieval Networks of Memory' analyzing mortuary rolls. These interconnected efforts form a comprehensive ecosystem for advancing textual scholarship across temporal and technological boundaries.
Tan Chuan Hoo is an Associate Professor (tenured) and Deputy Head of the Department of Information Systems and Analytics at the National University of Singapore's School of Computing. With a distinguished academic career spanning multiple continents, he brings expertise in digital transformation, healthcare informatics, and enterprise systems to his teaching and research. His educational background includes: B.Sc. (1st Class Honours, National University of Singapore) M.Sc. (Accelerated, National University of Singapore) Ph.D. (National University of Singapore) Professor Tan's research focuses on digital transformation, particularly designing, deploying, and evaluating technological innovations. His work centers on two critical areas: digital commerce (provision of digital services such as online shopping aids) and digital organization (ensuring operational efficiency and performance). His research has significant implications for healthcare institutions, corporations, and crisis preparedness and response organizations. He conducts comprehensive analyses using various scientific methodologies including field experiments and mixed methods to understand how digital technologies reshape business operations and enhance societal well-being. His publication record shows a consistent focus on information systems, with recent articles (2020-2025) emphasizing healthcare informatics, digital transformation, and open innovation. His work demonstrates a clear trajectory toward understanding how technology intersects with organizational effectiveness and societal implications, with increasing attention to healthcare applications and digital crisis management. Professor Tan has received numerous prestigious awards for his contributions to the field: Faculty Teaching Excellence Award, NUS (2024, 2017) Information Management Research Award, China Information Economics Society (2023) Reviewer Hall of Fame, Journal of AIS (2020) Outstanding Associate Editor Award, MIS Quarterly (2016) Best Reviewer Award, Journal of AIS (2016) INFORMS ISS Design Science Award (2013) Honorable Mention, Journal of AIS (2015) He has successfully advised PhD students and collaborated with public and private entities on research projects. His editorial service as Associate Editor for Information Systems Research and MIS Quarterly, along with board memberships at other leading journals, demonstrates his significant influence in the field. Professor Tan has secured research grants supporting projects on digital crisis preparedness, disaster response technology, and healthcare digitalization. His research group focuses on understanding how technology can be designed and implemented to support organizations in crisis situations, enhance healthcare services, and improve digital commerce. Current projects include examining digital crisis management, technology for disaster response, and the digital transformation of healthcare services.
Kevyn Collins-Thompson is an Associate Professor at the University of Michigan with joint appointments in the School of Information and College of Engineering. As Academic Director of the Master of Applied Data Science program, his research bridges information retrieval, machine learning, and educational technology. Research focuses on: Readability prediction and text difficulty assessment Search as learning frameworks Adaptive educational systems Risk-aware information retrieval Human-centered AI for education Publications demonstrate innovation in educational technology, including gaze-tracking systems for learning optimization and conversational AI for technical reading support. Recent work explores large language models for educational applications.
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.
Dr. Chunyan Mu serves as a Senior Lecturer in the School of Natural and Computing Sciences at the University of Aberdeen, actively contributing to both academic instruction and cutting-edge research in computing science while currently accepting new PhD students. Her research program centers on Trustworthy AI and Safe Autonomy, with specialized expertise in formal verification of responsibility, accountability, and privacy mechanisms within multi-agent systems. She investigates resilience frameworks for autonomous intelligent systems and develops advanced methodologies for information flow security analysis, bridging theoretical computer science with practical security implementations. Analysis of her publication trajectory (2014-2025) reveals consistent innovation in applying formal methods to security-critical systems. Key thematic developments include probabilistic strategy logic for observability analysis, quantitative verification of opacity properties, and game-theoretic approaches to security verification, demonstrating increasing sophistication in handling multi-agent accountability and system resilience challenges. Dr. Mu currently supervises PhD candidates and offers a fully funded doctoral position focused on formal verification of safety properties in autonomous systems, providing comprehensive financial support including tuition coverage, £20,780 annual stipend, and dedicated research funding for candidates with strong backgrounds in formal methods and artificial intelligence.
Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University. He holds multiple affiliations including membership in Bio-X, Faculty Affiliate status at the Institute for Human-Centered Artificial Intelligence (HAI), and membership in both the Wu Tsai Human Performance Alliance and Wu Tsai Neurosciences Institute. Dr. Wu earned his Ph.D. and S.M. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology before joining Stanford. Dr. Wu's research program focuses on creating AI systems that understand and interact with the physical world through the integration of computer vision, machine learning, robotics, and cognitive science. His work emphasizes physics-based modeling combined with deep learning to develop systems capable of perceiving, reasoning about, and predicting physical interactions. Key research areas include 3D scene understanding, neurosymbolic AI approaches, multimodal perception (combining vision, sound, and language), and embodied intelligence for robotics applications. His lab develops novel frameworks that bridge the gap between neural networks and symbolic reasoning to create more interpretable and robust AI systems. Analysis of Dr. Wu's recent publications reveals a strong trajectory toward integrated multimodal understanding for embodied AI. His work increasingly combines vision, sound, and language processing with physical reasoning to create systems that can interact meaningfully with the physical world. There's a clear progression from foundational computer vision research toward practical robotics applications, with significant emphasis on foundation models for robotics, sim2real transfer techniques, and creating comprehensive datasets for embodied AI research. Dr. Wu's exceptional contributions have been recognized with numerous prestigious awards including the NSF CAREER award (2024), Young Investigator Programs from ONR (2024) and AFOSR (2023), the Okawa research grant (2024), and being named to IEEE Intelligent Systems' 'AI's 10 to Watch' (2024). He has received multiple best paper awards at leading conferences including ICRA (2024), SIGGRAPH Asia (2023), and CoRL (2023). Dr. Wu actively mentors a large cohort of students across multiple levels, serving as primary advisor for doctoral candidates, master's students, and numerous independent researchers. His research is supported by substantial funding from major technology companies including Google, Meta, Amazon, Samsung, and J.P. Morgan, as well as government agencies like NSF, ONR, and AFOSR, reflecting the significance and impact of his work in physical AI and multimodal perception systems. Dr. Wu leads a dynamic research group at Stanford that collaborates extensively with the Wu Tsai Neurosciences Institute and Institute for Human-Centered AI. Current projects include developing neurosymbolic models for computer graphics, creating multisensory datasets like OBJECTFOLDER 2.0 for sim2real transfer in robotics, and building foundation models for embodied intelligence that can understand and manipulate objects with human-like physical intuition.
Allison Newton is an Instructor in the Department of Curriculum and Instruction at the University of Alabama at Birmingham (UAB), School of Education. Her roles include teaching courses such as Disciplinary Literacy P-12, Teaching Development of Reading Comprehension, and supervision of internships. She has served as a Dissertation Committee Member for Jawaher Fahad Alghofaili (2024). Her education includes a Ph.D. in Early Childhood Education (2016), M.Ed. in Reading Teacher Education (2012), and M.S. in English Literature (2007), all from UAB. She holds certifications in Class A Reading Specialist (P-12) and Secondary Education (6-12). Postgraduate training includes a Graduate Certificate in Teaching Multilingual Learners (2020). Research interests focus on early childhood education, media/technology integration in learning, literacy development, and culturally inclusive pedagogy. Notable works include studies on media exposure in preschoolers, ESL teaching strategies, and global perspectives on technology in education. Her publications span peer-reviewed journals and international conferences, emphasizing practical classroom applications and cross-cultural insights. Teaching activities total 92 courses, emphasizing internships and educational seminars. No grants or labs are explicitly listed, though her involvement in curriculum development and teacher training reflects active engagement in educational practice.
Julian Jara-Ettinger is an Associate Professor of Psychology and Computer Science at Yale University. He holds a Ph.D. from MIT (2016). His research focuses on understanding the cognitive and computational mechanisms underlying human social behavior, including fairness, linguistic communication, gesture, moral reasoning, and pedagogy. He employs interdisciplinary methods such as computational modeling, eye-tracking, cross-cultural studies, and developmental research to bridge psychology and artificial intelligence. Key research areas include the development of social cognition in children, the integration of theory of mind with communication, and the application of cognitive science principles to build socially intelligent machines. His work emphasizes how humans infer others' knowledge, intentions, and desires, with implications for AI safety and ethical systems design. Publications span topics like epistemic inference, moral judgments, and the computational foundations of social interaction. His lab's research often intersects with evolutionary simulations, neural modeling, and cultural psychology. No scientific awards are explicitly mentioned in the provided text. Collaborations involve cross-disciplinary teams addressing challenges in developmental science, AI ethics, and cognitive robotics. His work has practical applications in educational strategies, social policy, and human-AI collaboration frameworks.
Yuuko Uchikoshi Tonkovich is a Professor at the School of Education, University of California, Davis, where she has served since 2004, advancing from Assistant to Associate and then to full Professor. Her work centers on language and literacy development in young dual language learners, with a focus on bilingualism, early literacy, and the role of family and media in language acquisition. Her research interests include: Early Childhood Development Multilingual Learners and Bilingual Education Language Acquisition and Literacy Parent-Child Interaction and Home Language Environment Quantitative Analysis of Educational Outcomes Educational Television and Multimedia Her recent publications span topics such as cognitive distancing in parent-child reading, morphological awareness in bilingual readers, and the impact of teacher language use in multilingual classrooms. The research consistently emphasizes longitudinal, cross-cultural, and interdisciplinary approaches, particularly focusing on Chinese American and Mexican American immigrant families. Her scientific awards include: AERA Vocabulary SIG Notable Vocabulary Researcher Award (2025) Foundation for Child Development Young Scholars Program Grant International Reading Association Dissertation Fellowship and Finalist Award Harvard Graduate School of Education Fellowships She has advised numerous research projects and secured significant funding from NIH/NICHD, the Foundation for Child Development, and other organizations. She teaches courses such as Language Development, Early Literacy, and Research on Text Comprehension. She is actively involved in national initiatives, serving on the Technical Advisory Group for the First 5 California Dual Language Learner Study and as Associate Editor of Applied Psycholinguistics . She leads the Language & Literacy Development Lab at UC Davis, which investigates the cognitive, linguistic, and socio-emotional development of dual language learners.
