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Danny Poo Chiang ChoonView profile

Associate Professor

• Healthcare Informatics
• Data Science
• Business Analytics
• +6 more

Danny Poo Chiang Choon is a tenured Associate Professor at the School of Computing (SOC), National University of Singapore (NUS). As Curriculum Chair of the Department of Information Systems and Analytics, he plays a key role in designing and implementing Information Systems and Computer Science curriculum at NUS. Dr. Poo earned his BSc (Honours), MSc and PhD in Computation from the University of Manchester Institute of Science and Technology (UMIST), United Kingdom. His academic journey has established him as a leader in health informatics and information systems at NUS. His research spans multiple domains with strong focus on Healthcare Informatics , where he investigates mobile health interventions, health analytics, and systems for improving patient care. His work in Data Science & Business Analytics explores knowledge management, information sharing, and effective search strategies. In Intelligent Systems , he examines software engineering approaches, object-oriented systems, and knowledge classification frameworks. His recent publications demonstrate a clear trajectory toward mobile health applications, particularly in coronary heart disease prevention and diabetes management. Dr. Poo's work consistently bridges technical computing with practical healthcare applications, focusing on user-centered design and evidence-based interventions. His research shows strong interdisciplinary integration between computer science, healthcare systems, and behavioral science, with emphasis on practical implementation in Singapore's healthcare context. Dr. Poo has served in numerous leadership roles including as the founding Director of the Centre for Health Informatics at NUS (2012-2015) and as a member of the Steering Committee of the Asia Pacific Software Engineering Conference (APSEC) since 1994, serving as Vice-Chairman from 2003-2005. He has been invited to speak at international forums including the Japanese Government's "USA, Kyushu and Asia International Exchange Project" and as a keynote speaker at the 2009 Arabic Scripts Second Symposium in Abu Dhabi. His expertise is recognized through invitations to speak on knowledge management topics at conferences in Singapore. Dr. Poo has authored five books in the Information Technology area: "Enterprise JavaBeans for Students" (2014), "Object-Oriented Programming and Java" (1998, 2007), "Learn to Program Enterprise JavaBeans 3.0" (2009), "Learn to Program Java" (2009), and "Learn to Program Java User Interface".

Charles PerinView profile

Assistant Professor

• Information Visualization
• Human-Computer Interaction
• Personal Visualization
• +5 more

Charles Perin is an Assistant Professor of Computer Science at the University of Victoria, leading the UViz research group. He holds a PhD from Université Paris-Sud (2014) and has held roles including Post-doc at the University of Calgary and Lecturer at City, University of London. His research focuses on information visualization, personal visualization, human-computer interaction, and sports visualization. Education: PhD in Computer Science (2014), Université Paris-Sud; Post-doc at University of Calgary (InnoVis lab); MS and earlier studies in Computer Science and HCI in France. Research interests include designing interactive visualization tools for personal data reflection, health data communication, and sports analytics. He emphasizes authoring tools for non-experts and physical/tangible visualization systems. Recent work explores embedded data physicalizations and mobile visualization design. His articles span topics like data storytelling, patient-generated health visualizations, and soccer data analysis, often appearing in top venues like IEEE VIS, CHI, and Eurovis. He has advised over 20 students across PhD, MSc, and undergraduate levels. Teaching includes courses on Information Visualization and HCI at UVic, City, and other institutions. He co-organized workshops on topics like Personal Visualization and Sports Data at IEEE VIS. His UViz lab collaborates internationally with institutions like Monash University and the National Archives (UK).

Katrine EldegardView profile

Professor

• Conservation Biology
• Behavioural Ecology
• Population Ecology
• +7 more

Katrine Eldegard is a Professor at the Norwegian University of Life Sciences (NMBU), Faculty of Environmental Sciences and Natural Resource Management (MINA), Department of Ecology and Natural Resource Management (INA). She leads BatLab Norway and contributes extensively to national and international conservation science policy. Institution: Norwegian University of Life Sciences School: Faculty of Environmental Sciences and Natural Resource Management Department: Department of Ecology and Natural Resource Management Position: Professor Her research centers on understanding how human activities and land use affect natural ecosystems and species across taxa and spatial scales. She specializes in the behavioral, population, and community-level responses of mammals, birds, and insects to anthropogenic pressures such as energy infrastructure, transport networks, and forestry. A major focus is on bat ecology and conservation, pollination dynamics, and biodiversity monitoring in boreal and agricultural landscapes. Her recent publications reveal strong trends in climate change impacts on bat morphology and distribution, pollinator-plant interactions under environmental change, and the ecological consequences of infrastructure development. These works integrate field ecology with advanced modeling and policy-relevant assessments. She has played leading roles in key scientific committees: Chair, Mammal Committee, Norwegian Red List for Species (2021) Chair, Mammal Committee, Norwegian Alien Species List (2023) Member, Norwegian Scientific Committee for Food and Environment (VKM), CITES Expert Panel Norway’s representative, UNEP/Eurobats Advisory Committee Eldegard has supervised numerous research projects and collaborated with government agencies and private partners on applied ecology. She teaches courses including NATF200 Vern og forvaltning av norsk natur and the upcoming NATF300 Conservation Science. Her work is supported by extensive fieldwork, interdisciplinary collaboration, and integration of ecological theory with practical conservation. She leads BatLab Norway, a research group dedicated to advancing knowledge on bat ecology, behavior, and conservation through innovative methods including telemetry, acoustic monitoring, and landscape analysis.

April NowellView profile

Professor

• Paleolithic Archaeology
• Cognitive Archaeology
• Neanderthal Studies
• +7 more

Dr. April Nowell is a Professor of Anthropology in the Department of Anthropology at the University of Victoria's Faculty of Social Sciences, specializing in Paleolithic archaeology, cognitive archaeology, and the archaeology of children. Currently on leave, she leads internationally recognized research projects across Europe, the Levant, Australia, and Africa while actively accepting graduate students. She earned her PhD from the University of Pennsylvania and has developed expertise in Neanderthal lifeways, Paleolithic art, and hominin life histories. Her academic journey reflects deep engagement with both theoretical frameworks and fieldwork across diverse geographical contexts. Nowell's research examines how prehistoric societies structured knowledge transmission, childhood development, and symbolic expression. Her groundbreaking work on finger flutings in Australian caves reveals children's roles in Paleolithic storytelling traditions, while her analysis of Levantine wetland ecosystems demonstrates how Pleistocene humans adapted to environmental shifts. She challenges conventional narratives about Neanderthal cognition and has pioneered methodologies for reconstructing prehistoric childhood experiences through skeletal and material evidence. Her recent publications show consistent innovation in archaeological methodology, particularly in digital documentation of rock art and interdisciplinary approaches to human development. Key trends include integrating bioarchaeological data with cognitive models, examining material culture as evidence of social learning, and analyzing environmental archives to understand human dispersal patterns. Her scientific recognition includes: 2023 EAA Book Prize for Growing Up in the Ice Age: Fossil and Archaeological Evidence of the Lived Lives of Plio-Pleistocene Children Nowell secures major research funding including Social Sciences and Humanities Research Council grants supporting her Azraq Basin project in Jordan and Koonalda Cave research in Australia. She mentors graduate students in Paleolithic theory while collaborating with Indigenous communities and international scholars on field projects spanning five continents. Her work bridges academic research and public engagement through TEDx talks and media appearances examining science communication. She directs field programs at Jordan's Azraq Basin wetlands and Australia's Koonalda Cave, working with multidisciplinary teams including geochronologists, bioarchaeologists, and Traditional Owners to investigate Pleistocene human adaptation and cultural transmission.

ChanMin KimView profile

Professor

• Educational Technology
• Computer Science Education
• Science Writing
• +3 more

ChanMin Kim is a Professor in the Learning and Performance Systems department at Penn State College of Education. With over 80 publications and 2553 citations, their work focuses on integrating artificial intelligence , robotics , and educational technology into science and computer science education. Research interests: Science writing, AI-human partnerships, robotics in education, equity-focused technology design Key methodologies: Natural Language Processing, learning analytics, scaffolding strategies Recent work explores large language models in education, debugging processes in pre-service teacher training, and automated assessment systems for science explanations. While the provided data doesn't show specific scientific awards or student advisees, their publications in venues like British Journal of Educational Technology and Journal of Science Education and Technology demonstrate significant contributions to learning sciences. Kim collaborates extensively with researchers in AI, educational technology, and equity-focused domains.

Roummel F. MarciaView profile

Professor

• Optimization
• Signal Processing
• Data Science
• +5 more

Roummel F. Marcia is a Professor and current Chair of the Department of Applied Mathematics at the University of California, Merced, within the School of Natural Sciences. He received his Ph.D. from UC San Diego under Professor Philip Gill and previously held postdoctoral positions at the San Diego Supercomputer Center and University of Wisconsin-Madison, as well as a research scientist position in electrical engineering at Duke University. His research spans multiple areas in optimization and its applications, with a focus on signal processing, data science, machine learning, linear algebra, and mathematical biology. Dr. Marcia's work has significant interdisciplinary impact, particularly in biomedical imaging, computational biology, and quantum computing applications. His research methodology often combines theoretical optimization approaches with practical applications in data-intensive fields. Dr. Marcia's recent publications demonstrate a strong trend toward integrating optimization theory with deep learning architectures, particularly in applications requiring sparse data handling, biomedical imaging, and quantum computing. His work shows increasing focus on developing novel optimization algorithms specifically designed for machine learning contexts, including quasi-Newton methods adapted for deep learning and specialized techniques for handling non-convex optimization problems. School of Natural Sciences Faculty Award for 'Developing or Improving Academic Programs and Tracks' (2021-22) Leadership roles in SIAM Activity Group on Applied Mathematics Education Recognition as a Math Alliance Mentor for supporting underrepresented students Dr. Marcia has successfully mentored numerous doctoral students to completion, with graduates moving to positions at Meta, Johns Hopkins University Applied Physics Laboratory, Lawrence Livermore National Laboratory, and other prestigious institutions. His research has been consistently funded by major agencies including NSF (with grants IIS 1741490, DMS 1840265, DMS 2229495, CCF 2343610), DARPA, and ARPA-E. As the current graduate chair of the Applied Math Graduate Program, he plays a key role in shaping the next generation of mathematical scientists. His work with the SMaRT (Scientific Mathematics Research and Training) team demonstrates his commitment to collaborative, interdisciplinary research.

Cecilia R. AragonView profile

Professor

• Human-Centered Data Science
• Human-Centered Artificial Intelligence
• Human-Computer Interaction
• +5 more

Cecilia R. Aragon is a Professor in the Department of Human Centered Design & Engineering at the University of Washington, where she also serves as an Adjunct Professor in Computer Science & Engineering, Electrical and Computer Engineering, and the Information School. She is additionally a Senior Data Science Fellow at the eScience Institute. Aragon directs the Human-Centered Data Science Lab and has made significant contributions at the intersection of human-computer interaction and data science. Her research interests focus on human-centered data science, human-centered artificial intelligence, human-centered machine learning, human-computer interaction (HCI), computer-supported cooperative work (CSCW), visual analytics, aviation and astronautics sociotechnical systems, and emotion in informal text communication. Aragon's work bridges technical and social aspects of data science, particularly examining how humans interact with and gain insight from large datasets through both quantitative and qualitative methods. Aragon's recent publications demonstrate a strong focus on understanding online communities, sentiment analysis, distributed mentoring systems, and the ethical implications of AI. Her work spans multiple disciplines including social computing, data visualization, and astrophysics data analysis, showing her interdisciplinary approach to human-centered data science. Presidential Early Career Award for Scientists and Engineers (PECASE) 2008 Fulbright Fellowship 2017-18 HCDE Faculty Innovator in Research Award, University of Washington, 2015 Distinguished Alumni Award, Computer Science, University of California, Berkeley, 2013 Top 25 Women of the Year, Hispanic Business Magazine, 2009 Aragon has secured over $28 million in research funding from organizations including the National Science Foundation, National Institute of Standards and Technology, Department of Energy, Gordon and Betty Moore Foundation, Alfred P. Sloan Foundation, Washington Research Foundation, and industry partners like Microsoft and Intel. Her educational background includes a Ph.D. in Computer Science from UC Berkeley (2004), an M.S. in Computer Science from UC Berkeley, and a B.S. with Honors in Mathematics from Caltech. She leads the Human-Centered Data Science Lab and is affiliated with the eScience Institute, the Nearby Supernova Factory, and various research groups focused on data-intensive scientific collaborations. Her work on collaborative visual analytics systems like Sunfall has had significant impact in both academic and applied settings.

Lan GuanView profile

Professor

• Membrane transport
• Membrane proteins
• Solute transport mechanisms
• +6 more

Lan Guan is a Professor at Texas Tech University Health Sciences Center in the Department of Cell Physiology and Molecular Biophysics within the School of Medicine. He also serves as Co-Director of the Center for Membrane Protein Research. His research focuses on membrane proteins, which constitute approximately 30% of all eukaryotic proteins and play crucial roles in many aspects of cell function. Dr. Guan's research seeks to understand the mechanisms of solute transport and lay the foundation for advances in disease treatment and human health. He employs an integrated approach including cryo-EM single-particle analysis, X-ray crystallography, ligand binding, molecular dynamics simulations, thermodynamics, genetic engineering, novel amphiphiles, and many other biochemical & biophysical analyses. His current research focuses on cation-coupled bacterial and human transporters. Dr. Guan is currently supported by an NIGMS MIRA R35 Award (2024). His publication record demonstrates expertise in membrane protein structure and function, particularly with melibiose transporters (MelB) and their mechanisms. His work spans structural biology, biochemistry, and biophysics, with significant contributions to understanding membrane transport mechanisms. His research has led to important insights into membrane protein structure-function relationships, particularly in sugar transporters. Dr. Guan's work has implications for understanding fundamental biological processes and potential therapeutic applications related to membrane transport. NIGMS MIRA R35 Award 2024 Dr. Guan actively collaborates with researchers across disciplines and institutions, as evidenced by his extensive publication record with numerous co-authors. His work bridges structural biology, biochemistry, and biophysics to advance our understanding of membrane protein function. He is affiliated with the Center for Membrane Protein Research, where he contributes to advancing methodologies for studying these challenging but critically important biological molecules. His work on novel amphiphiles and detergent design has helped overcome technical barriers in membrane protein research.

Dina El-ZanfalyView profile

Assistant Professor

• Computational Design
• Human-Computer Interaction
• Embodied Interaction
• +5 more

Dina El-Zanfaly serves as an Assistant Professor in the School of Design at Carnegie Mellon University (CMU), where she directs the hyperSENSE: Embodied Computations Lab. Her work bridges computational design and human-centered interaction, focusing on how physicality shapes sensory experiences and cognitive processes through intelligent systems. Education: PhD in Design and Computation, Massachusetts Institute of Technology (MIT) Master of Science in Design and Computation, MIT (Fulbright scholar) Her research critically examines computational methods for augmenting sensory perception, with emphasis on embodied sense-making in hybrid environments. She investigates co-creative interactions between humans and intelligent systems, exploring how computational tools empower designers and non-designers to shape products, social spaces, and interconnected technologies. Key questions address mutual learning between humans and machines through improvisation and creative production. Analysis of her 2022-2025 publications reveals dominant themes in mixed reality interfaces, AI-augmented skill acquisition (particularly in crafts and welding), and tangible co-creation with generative AI. Her work consistently integrates physical computing with mindfulness applications and privacy-aware smart environments, demonstrating interdisciplinary reach across education, manufacturing, and therapeutic contexts. Scientific Awards: Fulbright Scholarship As lab director, El-Zanfaly mentors students in computational making and embodied interaction projects. Her research is supported through initiatives like Fab Lab Egypt and collaborations with MIT, where she co-founded the Computational Making Group. She chairs major conferences including Fab15 in Egypt and serves on the DESFORUM program committee, indicating significant leadership in maker education and design research communities. She founded and leads the hyperSENSE Lab at CMU, which investigates computational embodiment through projects like Origami Sensei and Sand-in-the-loop. Previously, she co-established the Computational Making Group at MIT and co-founded Fab Lab Egypt (the first community maker space in North Africa/Arab world), demonstrating sustained commitment to global maker ecosystems and interdisciplinary team building.

Hemant K. BhargavaView profile

Professor

• Technology Management
• Management Information Systems
• Economics of Information Technology
• +12 more

Hemant K. Bhargava is a Distinguished Professor at the Graduate School of Management, University of California Davis, where he holds the Jerome and Elsie Suran Chair in Technology Management. He serves as Associate Dean for Academic Affairs and Director of the Center for Analytics and Technology in Society (CATS), and previously served as Associate Dean for Instructional Programs (2010–2013) and Faculty Chair. He co-founded and was the first Academic Director of the UC Davis Master of Science in Business Analytics (MSBA) program. His educational background includes: Ph.D. in Decision Sciences, The Wharton School, University of Pennsylvania (1989) MBA, Indian Institute of Management Bangalore (1986) B.S. in Mathematics, University of Delhi (1984) Bhargava is a leading scholar in technology management, information systems, and decision analytics. His research focuses on the economics of digital goods and platforms, pricing strategies, AI in business, healthcare IT, and platform ecosystems. He builds economic models to study operations, marketing, and competitive strategy in tech-driven markets, with applications in healthcare, media, electric vehicles, and generative AI. His recent publications reveal a strong trend toward platform business models, data sharing, AI’s impact on research and education, and healthcare cost transparency. He explores how digital platforms shape competition, how data can be leveraged across markets, and how real-time decision tools can reduce prescription drug costs. His work bridges theory and practice, often involving collaboration with industry and policy makers. His scientific awards include: INFORMS Journal on Computing Test of Time Award (2023) INFORMS CIST Best Paper Award (2021) Google Research Excellence Gift (2017–18) Distinguished Alumni Award, IIM Bangalore (2024) INFORMS ISS President's Service Award (2023) Global 100 Top Academic Data Leaders (2020) Bhargava has played a pivotal role in academic leadership and program development. He co-founded the Theory in Economics of Information Systems (TEIS) workshop and has served on editorial boards of top journals including Management Science (where he is Department Editor for Information Systems), Operations Research, and Marketing Science. He has advised numerous campus initiatives, including the UC Davis Data Lab and Religions of India Initiative. His grants and collaborations include work with Google and healthcare organizations on real-time price transparency tools. He leads the Center for Analytics and Technology in Society (CATS), which focuses on the societal implications of data and AI. He also co-founded the MSBA program and continues to shape the future of business education in the age of AI through strategic planning committees.

Jeff ZhangView profile

Assistant Professor

• Deep learning
• Computer architecture
• Embedded systems
• +5 more

Jeff Zhang is an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. He joined ASU in January 2023 after completing a postdoctoral fellowship at Harvard University. His research spans deep learning, computer architecture, embedded systems, and EDA, with particular emphasis on energy-efficient and fault-tolerant design for AI/ML systems and hardware accelerators. Education: Ph.D., New York University M.Eng., B.Eng., Hunan University Dr. Zhang's research bridges theoretical machine learning with practical hardware implementation, developing novel architectures that optimize performance, power consumption, and reliability. He has pioneered approaches for hardware acceleration of large language models, efficient sparse matrix operations, and novel memory technologies for AI workloads. His work has received multiple awards including IEEE Top Picks in Test and Reliability (2023) and IEEE Micro Best Paper Award (2022). His recent publications demonstrate a strong trend toward heterogeneous computing, with significant work in chiplet-based AI accelerators, photonic computing for AI, and 2.5D/3D integration techniques. The research spans from high-level compiler frameworks to circuit-level innovations, with a consistent theme of co-designing algorithms and hardware for optimal AI performance. His work on the SODA toolchain has been particularly influential in bridging Python to silicon. Scientific Awards: IEEE Top Picks in Test and Reliability, IEEE ITC, 2023 Best Paper Award, IEEE Micro, 2022 Best Paper Award Candidate, IEEE DATE, 2022 Best Presentation Award Nomination, ACM SIGDA DATE PhD Forum, 2020 Best Paper Award Nomination, IEEE VLSI Test Symposium, 2018 Ernst Weber Ph.D. Fellowship, New York University, 2015, 2016 Dr. Zhang actively mentors a diverse group of graduate and undergraduate students, with several alumni now working at leading technology companies including Apple, TSMC, and Ansys. His research is supported by prestigious grants from NSF, Sandia National Labs, and industry partners. He serves on technical program committees of numerous top conferences and has organized special sessions on emerging topics like Gen AI for Chip Design and LLM-Aided Design. Dr. Zhang leads a vibrant research group that collaborates extensively with industry partners and national laboratories. Current projects focus on next-generation AI hardware, including chiplet-based systems, photonic accelerators, and novel memory technologies for large language models. His group has developed several open-source tools and frameworks, including the SODA toolchain for bridging Python to silicon.

Bill HamiltonView profile

Assistant Professor

• Live Media Design
• Human Computer Interaction
• Computer Supported Collaborative Work and Play
• +3 more

Dr. Bill Hamilton is an Assistant Professor in the Department of Computer Science at New Mexico State University. His research focuses on live media design, online communities, and digital game culture. He holds a Ph.D. in Human Computer Interaction from Texas A&M University (2018), and has collaborated with industry partners like Microsoft Research and Motorola Mobility. Education: Ph.D. in Human Computer Interaction, Texas A&M University (2018) Bachelor’s degree in Computer Science, Texas A&M University Research Interests: Bill explores how live media supports societal participation in education, politics, work, and play. His work employs qualitative methods like ethnographic inquiry to study collaborative digital environments. Recent projects include designing wearable interfaces for human-drone teams and analyzing YouTube’s content policies' impact on free speech. Awards: 2018 Texas A&M Distinguished Graduate Research Award 2016 Best Paper at ACM Interactive Experiences for TV/Online Video Advising & Grants: Mentors students like Preeti De Maurya and Cassandra Palmer, with a focus on inclusive education technologies and collaborative tools for emergency response. Active in conference organization including ACM CHI’s Games and Play Subcommittee (2019). Labs: His research is conducted through the PlexLab, exploring playful interactions and live media systems.

Li YinView profile

Associate Professor

• Urban Planning
• Spatial Modeling
• Geographic Information Systems (GIS)
• +9 more

Li Yin is an Associate Professor in the Department of Urban and Regional Planning at the School of Architecture and Planning, University at Buffalo. Her research integrates spatial modeling, GIS, and simulation methods to study urban systems, with applications in environmental planning, urban design, and sustainable development. She actively collaborates across disciplines to develop strategies for smart urban growth. Her educational background includes a Ph.D. in Design and Planning from the University of Colorado, an M.S. in Urban Planning from the Asian Institute of Technology, and a B.S. in Architecture from Kunming University of Science and Technology. Ph.D., University of Colorado, Design and Planning M.S., Asian Institute of Technology, Urban Planning, Land and Housing Development B.S., Kunming University of Science and Technology, Architecture Dr. Yin's research focuses on applying innovative analytical methods to urban planning and design, particularly through the use of GIS, 3D modeling, and simulation tools. She explores how amenities influence urban growth patterns and location choices, aiming to enhance planning efficiency and communication. Her work emphasizes data-driven approaches to understanding urban dynamics and supports sustainable community development. She teaches courses in computing for environmental analysis, GIS applications, and planning support systems, reflecting her commitment to technological integration in planning education. Dr. Yin is also engaged in public service, particularly in examining the relationship between public health and the built environment in the Buffalo-Niagara region. She leads the Urban Analytics Lab, a research group focused on leveraging data and technology to improve urban planning outcomes. Dr. Yin has played a key role in several multi-million-dollar funded research projects, collaborating with researchers from engineering, medicine, science, and public health. These interdisciplinary efforts have focused on the interactions between technology, society, and urban planning, contributing to smarter and more resilient urban communities. The Urban Analytics Lab, which she is affiliated with, brings together researchers passionate about applying advanced data methods to urban challenges. The lab benefits from recent advancements in data availability and computational tools to deepen understanding of how cities function and are planned.

Yuko MunakataView profile

Professor

• Developmental Psychology
• Cognitive Neuroscience
• Executive Functions
• +5 more

Yuko Munakata is a Professor in the Department of Psychology at the University of California, Davis, and Director of the Cognition in Context Lab. She holds affiliations with the Center for Mind and Brain. Her education includes a PhD in Psychology from Carnegie Mellon University and dual BS/BA degrees in Symbolic Systems and Psychology from Stanford University. Her research integrates behavioral experiments, computational modeling, neuroimaging (ERP/fMRI), and cross-cultural studies to investigate how thinking varies across developmental stages and environmental/social contexts. Core interests include executive functions, developmental trajectories, cognitive control mechanisms, and interventions to enhance adaptive thinking. Her work highlights the role of cultural habits, social influences, and proactive control in shaping decision-making and self-regulation. Recent work explores the impact of environmental predictability on cognitive control development, the link between procrastination in adults/children, and the efficacy of executive function training programs. She advocates for contextual frameworks in understanding individual differences and educational inequality. Awards: American Psychological Association Boyd McCandless Early Career Award Outstanding Mentor Award (UC Boulder) Fellowships in Association for Psychological Science and APA Grants: NIH funding since 1998, supporting studies on child development and executive functions. Labs: Cognition in Context Lab (UC Davis), Center for Mind and Brain collaborations.

Elise LavouéView profile

Professor

• Technology Enhanced Learning
• Human-Computer Interaction
• Gamification
• +12 more

Elise Lavoué is a full Professor in Computer Science at iaelyon School of Management, Jean Moulin Lyon 3 University, and a key researcher at the LIRIS laboratory (CNRS). She leads the SICAL research team and holds leadership roles including Editor-in-Chief of the STICEF journal, member of Labex ASLAN’s management committee, and member of the University of Lyon’s Research Ethics Evaluation Committee (CER-UdL). She is also affiliated with the ATIEF association. Her research focuses on enhancing motivation and engagement in digital learning environments through adaptive gamification, learning analytics, and human-computer interaction. She explores how tailored game elements, emotional awareness tools, and immersive technologies like virtual reality can support self-regulated learning, critical thinking, and skill development in complex digital contexts. Her recent publications span top journals such as IEEE Transactions on Learning Technologies, International Journal of Human-Computer Studies, Computers & Education, and CHI PLAY. These works reflect a strong trend in adaptive and personalized learning technologies, emotion-aware systems, and immersive training environments, particularly in educational and professional settings. Honorable Mention Award at ACM CHI PLAY 2019 (top 4%) Best Industrial Paper award at CSEDU 2020 Elise Lavoué actively supervises PhD students and post-doctoral researchers and leads multiple funded projects including LudiMoodle+, RENFORCE, Lex.gaMe, BODEGA, and Emoviz. These projects involve collaborations with institutions across France and focus on gamification, VR training, emotional dashboards, and vocabulary acquisition. She has secured funding from ANR, Labex ASLAN, CNRS, and other national bodies. Her work emphasizes interdisciplinary collaboration between computer science, education, and social sciences. She is involved in several research teams and labs, primarily the SICAL team within the LIRIS laboratory, a major interdisciplinary research unit in computer science, images, and information systems. Her projects often involve industry partners such as SpeakPlus and Woonoz, and she contributes to both scientific advancement and practical educational innovation.