Jackson G. Lu is the General Motors Associate Professor of Management and an Associate Professor of Work and Organization Studies at the MIT Sloan School of Management. His scholarly work bridges cultural psychology with organizational behavior, examining how cultural differences manifest in AI adoption, creativity, and leadership dynamics. He serves as senior editor for Organization Science and Management and Organization Review , and associate editor for Journal of Personality and Social Psychology . Dr. Lu earned his PhD from Columbia Business School in 2018 and received tenure at MIT in 2023. His research has been published in top-tier journals across psychology, management, and general science domains, including Nature Human Behaviour , Psychological Bulletin , and Annual Review of Psychology . His work has garnered over 300 media mentions globally. Cross-Cultural Psychology AI Ethics and Creativity Leadership Emergence Stereotype Research Technological Adoption Workplace Diversity Recent research focuses on cultural tendencies in generative AI , AI's impact on creativity , and structural barriers faced by Asian professionals . He has received numerous accolades from professional societies including the Wegner Theoretical Innovation Prize and multiple Best Senior Editor Awards. 40 Best Business School Professors Under 40 Thinkers50 Radar Class of 2021 Academy of Management Award Outstanding Dissertation Award (2019) SAGE Early Career Award Dr. Lu teaches through MIT Sloan Executive Education's 5-day program Leading the AI-Driven Organization , and his findings have been featured in The New York Times , BBC , and The Economist . His editorial leadership spans multiple journals, reflecting his influence across academic networks.
Professor Ioannis Katakis is a Faculty Member at the University of Nicosia, where he is affiliated with the School of Sciences and Engineering and the Department of Computer Science. He has held various academic positions across multiple institutions including Aristotle University of Thessaloniki, University of Cyprus, Cyprus University of Technology, Open University of Cyprus, Hellenic Open University, Athens University of Economics and Business, and National and Kapodistrian University of Athens. His educational background includes a PhD in Machine Learning for Automated Text Classification (2005-2009), a Master's in Information Systems (2005-2007), and a Bachelor's in Computer Science (2000-2004), all from Aristotle University of Thessaloniki. Professor Katakis specializes in several cutting-edge areas of computer science and data analysis. His primary research interests include Mining Social, Web and Urban Data , Sentiment Analysis and Opinion Mining , Data Streams , and Multi-label Learning . His work bridges theoretical machine learning approaches with practical applications in social media analysis, healthcare informatics, privacy protection, and smart city technologies. He has published extensively in top venues including CIKM, ECML/PKDD, IEEE TKDE, and ECAI. His recent publications demonstrate a clear trend toward applying machine learning techniques to real-world problems with societal impact. He has focused on areas such as GDPR compliance in smart devices, sentiment analysis in crowd-sourced content, healthcare applications including drug reaction classification and brain disease monitoring, and privacy protection in wearable technologies. His work often involves multi-modal data analysis and addresses challenges in data streams and multi-label classification. Professor Katakis has made significant contributions to his field, with his research cited over 4,200 times. He serves as an Editor for the journal Information Systems and has edited four special issues in journals such as DAMI and InfSys. He regularly contributes to the academic community by serving on program committees for major conferences including ECML/PKDD, WSDM, DEBS, and IJCAI, and by reviewing for prestigious journals like TPAMI, DMKD, TKDE, TKDD, JMLR, TWEB, and ML. He has been actively involved in European research projects, notably serving as Quality Assurance Coordinator and Senior Researcher for projects such as VAVEL (www.vavel-project.eu) and INSIGHT (www.insight-ict.eu). His grant activities demonstrate a strong focus on collaborative, interdisciplinary research with practical applications in urban data management, social media analysis, and healthcare informatics. He has organized three workshops at major conferences (ICML, ECML/PKDD, EDBT/ICDT) and has extensive experience translating research into practical applications through his involvement in European projects.
Andréanne Sharp, PhD, is Assistant Professor at Université Laval’s Faculty of Medicine, Department of Rehabilitation, where she leads the Clinical and Cognitive Neuroscience research axis. Her program explores auditory and multisensory processing across the lifespan, with emphasis on music perception, hearing loss, cochlear implants and vibrotactile technologies. Research interests: Auditory-vibrotactile interactions and sensory substitution Music cognition and neural plasticity in musicians Aging, hearing impairment and rehabilitation Temporal processing and EEG correlates of perception Clinical translation toward improved prosthetic and therapeutic devices Recent work (2023-2025) combines psychophysics, electrophysiology and qualitative methods to understand how musical experience protects perceptual skills in older adults with hearing loss, how frequency cues modulate auditory illusions, and how COVID-19 public-health measures affected communication in the hearing-impaired community. Sharp’s output appears in high-impact journals including Brain Research , Cerebral Cortex , Ear & Hearing , JSLHR and Psychological Research , demonstrating a trajectory that bridges basic cognitive neuroscience and clinical audiology. She maintains an active interdisciplinary laboratory, mentoring numerous graduate students and collaborating with engineering and rehabilitation teams to develop vibrotactile gloves and other sensory-augmentation devices. Grant and funding details are not disclosed in the supplied text.
Sylvain Kahn is a Tenured Lecturer at the Centre for History (CHSP) at Sciences Po , specializing in the history and geography of European integration. He holds a PhD in Geography, the agrégation (highest state teaching qualification) in History, and a degree in Geopolitics. Education : PhD in Geography, agrégation in History, Ecole Normale Supérieure (Fontenay-Saint-Cloud/Lyon), Geopolitics degree. Teaching : European integration and geopolitics at Sciences Po since 2001; leads 'History of European integration' class in the Master of European Affairs program. Research interests center on the role of nation-states in European integration, the territoriality of the European Union, and the Europeanization of higher education. His work bridges historical analysis with geopolitical frameworks, examining paradoxes in EU territorial governance. Recent publications include analyses of EU crises (e.g., Brexit, pandemic responses), geopolitical dynamics (e.g., Franco-German leadership), and cultural studies (e.g., 'La Reine Margot' as feminist critique). He has also explored the interplay between EU territorial policies and national sovereignty. Professional contributions extend to media production: he created the MOOC 'Geopolitics of Europe' (available in French and English) and hosted the radio program 'Planète Terre' on France Culture (2006-2016). He has served on examination juries (ENA) and as an expert for the European University Association.
Patrick C. Shih is an Associate Professor of Informatics in the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington, where he also serves as the Director of Graduate Studies for Data Science and Co-Director of the Animal Informatics MS and PhD track. He directs the Societal Computing Lab (SoCo Lab) and is a core faculty member of the Health Informatics PhD track. Dr. Shih's research focuses on how to better support health and wellbeing, specifically that of underserved and vulnerable populations, through the design, development, and evaluation of sociotechnical systems and community-based mechanisms. His work also designs technologies to amplify human and animal capabilities in animal-assisted interventions, improve animal welfare, and cultivate empathy for others. His research spans human-computer interaction, social media, collective intelligence, crowdsourcing, and online and geographic communities, with a particular emphasis on leveraging awareness of individual and community activities embedded in social media for civic engagement platforms. His recent publications reveal a strong trend toward health equity research, particularly focused on African American/Black communities, Alzheimer's disease and related dementias, breast cancer survivorship, and autism spectrum disorder. His work increasingly integrates generative AI, mobile health applications, and community-based participatory design approaches to address health disparities in vulnerable populations. ACM Senior Member (2020) NSF CAREER Award recipient Indiana University Trustees Teaching Award (2018-19) IU Groups Scholars Program STEM Mentor of the Year (2018-19) Multiple best paper awards at top-tier conferences Dr. Shih has successfully secured significant funding for his research, including a $3.7 million award to investigate inequities in environmental stressors and cognitive decline in urban and rural older adults. He serves on numerous editorial boards and program committees for leading HCI and computing conferences. His teaching portfolio includes courses on usable AI, mobile and pervasive design, and social computing. He leads the Societal Computing Lab, which focuses on developing technologies that address societal challenges through community engagement and participatory design.
Rada Savic is a Professor in the Department of Bioengineering and Therapeutic Sciences at the University of California San Francisco (UCSF), with a focus on computational pharmacology and precision medicine. She serves as Codirector of the Pharmaceutical Sciences and Pharmacogenomics Graduate Program (PSPG) and is affiliated with the Quantitative Biosciences Institute (QBI). PhD, Pharmacometrics, Uppsala University (2008) MS, Biomedical Sciences, Uppsala University (2004) BSc, Pharmacy, University of Belgrade (2003) Her research integrates computational methods to study drug-disease interactions across molecular to whole-body scales, particularly in tuberculosis, HIV, malaria, and pediatric pharmacology. Key areas include pharmacometrics, systems pharmacology, precision dosing, and translational modeling. Recent work examines drug penetration in tuberculosis lesions, regimen optimization for drug-resistant infections, and pregnancy-related pharmacodynamic models for malaria. She has published extensively in journals like Nature Communications , Clinical Infectious Diseases , and Antimicrobial Agents and Chemotherapy . Leon I. Goldberg Early Investigator Award (2021) UCSF KL2 Career Award (2013) PhRMA Foundation Research Grant (2013) She leads NIH-funded tuberculosis consortia and contributes to global health initiatives through malaria and HIV pharmacology studies. Her collaborations span institutions including University of Belgrade, Uppsala University, and CDC Tuberculosis Trials Consortium.
Dr. Lauren Emberson (she/her/hers) is an Associate Professor in the Department of Psychology at the University of British Columbia, Faculty of Arts. She directs the Baby Learning Lab, which is part of UBC's Early Development Research Group, a consortium focused on infant and child development. Prior to her position at UBC, Dr. Emberson was an Assistant Professor at Princeton University where she co-founded and co-directed the Princeton Baby and Princeton Kid Labs. Education: Postdoctoral Associate, University of Rochester (PI Aslin) Ph.D, Cornell University (PIs Amso, Goldstein, Spivey) B.Sc, University of British Columbia Dr. Emberson's research focuses on learning, perception (audition, vision, crossmodal or multisensory), language development, face/object perception, and attention in infants. She investigates these capacities using behavioral and neuroimaging techniques, particularly fNIRS (functional near infrared spectroscopy), working primarily with very young infants (birth through 1 year) and preterm/premature infants. Her work examines how infants' learning capacities contribute to rapid development of perception in ecological contexts, with implications for understanding how early life experiences affect later outcomes. Analysis of Dr. Emberson's recent publications reveals a consistent focus on infant perception, learning mechanisms, and neuroimaging methodology. Her work increasingly incorporates advanced fNIRS techniques while maintaining focus on fundamental questions about how infants learn from their environment. There's a growing emphasis on individual differences, cross-cultural comparisons, and applications to infants facing developmental challenges. Dr. Emberson serves on the editorial board of Infancy (journal of the International Congress of Infancy Studies) and is a consulting editor for the Journal of Cognitive Neuroscience . Her research has been published in top journals including PNAS, Current Biology, Psychological Science, Cognition, Developmental Science, and the Journal of Neuroscience. Dr. Emberson has secured significant research funding from prestigious organizations including the Bill and Melinda Gates Foundation, James S. McDonnell Foundation, Natural Sciences and Engineering Research Council (NSERC), Canadian Institutes of Health Research (CIHR), and the National Institutes of Health (NIH). She collaborates with clinicians at BC Women's and Children's Hospitals to understand how different early life experiences impact learning and brain development. Dr. Emberson is currently accepting graduate students into her research program. The Baby Learning Lab, under Dr. Emberson's direction, is part of UBC's Early Developmental Research Group and collaborates with multiple institutions. The lab strives to provide interactive research experiences for infants and families while advancing scientific understanding of early cognitive development. The lab acknowledges that it operates on the traditional, ancestral, and unceded territory of the xʷməθkʷəy̓əm (Musqueam) people.
Dr. Victoria C. P. Chen is a Professor in the Industrial, Manufacturing, and Systems Engineering (IMSE) department at The University of Texas at Arlington (UTA), where she has served since 2002. She previously held positions at the Georgia Institute of Technology from 1993-2001. Dr. Chen has held several leadership roles at UTA, including Interim Department Chair (2012-2014), Director of the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS) (2008-2012, and again from 2017-present), and Director of Doctoral Studies (2019-present). She was also the George & Elizabeth Pickett Professor from 2015-2017 and was inducted into the UT Arlington Academy of Distinguished Teachers in 2019. Dr. Chen is actively involved with INFORMS (Institute for Operations Research and the Management Science), where she currently serves as Secretary on the Executive Board. Dr. Chen earned her B.S. in Mathematical Sciences from The Johns Hopkins University, and her M.S. and Ph.D. in Operations Research and Industrial Engineering from Cornell University. Her academic journey includes visiting professorships at the University of Genoa, Italy, and Iowa State University. Dr. Chen's research utilizes statistical perspectives to create new methodologies for operations research problems appearing in engineering and science. Her expertise includes the design of experiments, statistical modeling, and data mining, particularly for computer experiments and stochastic optimization. Through her statistics-based approach, she has developed computationally-tractable decision-making methods for many high-dimensional complex systems. Her work spans multiple domains including sustainability, energy, water management, healthcare, and law enforcement. Specific application areas include inventory forecasting, airline optimization, water reservoir networks, wastewater treatment, air quality monitoring, green building design, nurse assignment systems, and pain management programs. Her recent publications demonstrate continued innovation in mixed integer programming for electric vehicle charging stations, vacuum ultraviolet spectroscopy prediction, and sustainable building education. Senior Member, Institute for Operations Research and the Management Sciences (INFORMS) (2024) Data Mining Prize (Lifetime Achievement Award), INFORMS Society on Data Mining (2023) College of Engineering Teaching Award, UT Arlington (2021) Third Place Award, C3.ai COVID-19 Grand Challenge (2020) Academy of Distinguished Teachers, University of Texas at Arlington (2019) George & Elizabeth Pickett Professorship (2015-2017) As an educator and mentor, Dr. Chen has advised over 25 doctoral students across diverse research topics in operations research and systems engineering. She has secured substantial research funding from multiple sources including the National Science Foundation (over $1.5 million in active projects), Environmental Protection Agency, National Institute of Justice, and industry partners like Luminant and Dallas-Fort Worth International Airport. Her current research projects focus on decision analytics for sustainable urban environments, optimization for Texas water management, and statistical methods for pain management programs. She has served as Principal Investigator or Co-PI on more than 20 externally funded research projects totaling over $3 million in funding. Dr. Chen co-founded the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS) at UTA with Dr. H. W. Corley. This research center brings together faculty and students from multiple disciplines to address complex problems through advanced statistical and optimization methods. She also leads interdisciplinary research teams working on projects related to sustainable infrastructure, energy systems, and healthcare optimization, frequently collaborating with researchers from civil engineering, environmental science, and medical fields.
Dr. Jatin P. Ambegaonkar is a Professor in the School of Kinesiology, College of Education and Human Development at George Mason University, where he serves as Associate Dean for Research. He holds a PhD from the University of North Carolina Greensboro and is a Certified Athletic Trainer and Occupational Therapist. His translational research bridges laboratory science and community engagement to enhance performance, reduce injury risk, and improve health outcomes across populations. Research Focus: Dr. Ambegaonkar's work centers on interdisciplinary approaches to human movement, with emphasis on: Performing artists' health and injury epidemiology Biosensor applications in sports and dance Neuromechanical assessment and concussion management Falls prevention and quality of life in older adults Community-based health interventions for underserved populations His research vision— "Arts and Health for the Physically Active, Physical Activity for Health and Artists" —drives initiatives like the SMART Laboratory (co-founded in 2006) and the SHARe Consortium. Publications: His 80+ articles demonstrate consistent focus on injury mechanisms, dance science, and aging research, with recent emphasis on kinesiophobia (2024), multifactorial fall interventions (2024), and longitudinal dancer fitness (2023). Methodologies span systematic reviews, RCTs, biomechanical analyses, and community trials. Leadership & Grants: As founding co-director of the SMART Laboratory, he leads projects including: ACHIEVES: Free athletic healthcare for underserved students POISED: Falls prevention in older adults SHARe Consortium: Multidisciplinary injury prevention for artists He has secured $6.4M across 30 grants from the National Endowment for the Arts, Potomac Health Foundation, and others. Editorial Roles: Editor-in-Chief of the Journal of Dance Medicine & Science ; Editorial Board member for the Journal of Athletic Training ; reviewer for 25+ scientific journals.
Allen L. Robinson is a Professor and Dean of the Walter Scott, Jr. College of Engineering at Colorado State University (CSU). Previously, he held leadership roles at Carnegie Mellon University, including Head of the Department of Mechanical Engineering (2013-2021) and Director of the EPA-funded Center for Air, Climate, and Energy Solutions (CACES, 2016-2022). He also served as Director of CMU-Africa (2021-2023) and President of the American Association for Aerosol Research (2016-2017). Education: Ph.D. in Mechanical Engineering, University of California, Berkeley (1996) B.S. in Civil and Environmental Engineering, Stanford University (1990) Research Interests: Focuses on emissions from energy systems, air quality, climate change, and public health. Explores policy analysis and decision-making, with teaching experience in thermodynamics, atmospheric chemistry, and air quality engineering. Awards: 2020 David Sinclair Award, American Association of Aerosol Research 2020 University Professor, Carnegie Mellon 2020 Distinguished Professor of Engineering Award, Carnegie Mellon 2015 ASCENT Award, American Geophysical Union Advising & Grants: Led major initiatives like CACES and contributed to global programs like CMU-Africa. His work bridges academia and policy, addressing environmental equity and urban pollution. Labs & Teams: Spearheads the Atmospheric Science and Chemistry mEasurement NeTwork (ASCENT), advancing ground-based air quality monitoring.
Mustafa Bilgic is a Professor and Chair of the Computer Science Department at Illinois Institute of Technology, where he also directs the Master of Artificial Intelligence program and the Machine Learning Laboratory. His research focuses on machine learning, active learning, explainable AI, and probabilistic graphical models, with applications in healthcare, social media analysis, and biomedical engineering. He has received funding from NSF, NIH, and Samsung, among others. Education: PhD in Computer Science, University of Maryland at College Park (2010) M.S. in Computer Science, University of Maryland at College Park (2006) B.S. in Computer Science, University of Texas at Austin (2004, with High Honors and Special Honors) Research Highlights: Dr. Bilgic's work emphasizes AI ethics, algorithm transparency, and interactive machine learning systems. Notable projects include analyzing political news engagement dynamics and developing frameworks for eliminating explanation noise in AI models. His lab explores tools like OrganoID for tracking organoid growth and IDGI for improving model interpretability. Awards: NSF CAREER Award (2014) ACM SIGKDD Best Student Paper Award (2008) Illinois Tech College of Computing Teaching Excellence Award (2021) Teaching and Leadership: Bilgic teaches advanced courses in AI, machine learning, and data mining. He leads initiatives to bridge AI theory and practical applications, emphasizing interdisciplinary collaboration. His administrative roles include overseeing the AI master’s program and fostering innovation in computing education.
Dr. Steven Manson is a Professor in the Department of Geography, Environment, and Society at the University of Minnesota's College of Liberal Arts, where he also served as Associate Dean for Research and Graduate Programs. He directs the Human-Environment Geographic Information Science (HEGIS) laboratory and leads major data science initiatives like the National Historical Geographic Information System (NHGIS) and IPUMS Terra. PhD in Geography, Clark University (2002) BA Honours in Geography, University of Victoria (1995) His research focuses on geographic information science and human-environment systems , using agent-based modeling and big data to analyze land use change, urban dynamics, and sustainability challenges. Recent work explores spatiotemporal data harmonization and geospatial cyberinfrastructure . The articles reveal trends in GIScience methodology , urbanization analysis , and data-intensive sustainability research . Key contributions include self-organizing map applications for health data and hybrid statistical-GIS techniques for environmental policy. Scientific accolades include: Ecological Society of America Sustainability Science Award NASA Earth System Science Fellow McKnight Land Grant Professorship As Principal Investigator for NHGIS and IPUMS Terra, he secured over $40M in NSF, NIH, and DOJ grants for spatiotemporal data infrastructure. Outreach initiatives include developing open geospatial textbooks adopted globally and collaborating with Twin Cities K-12 programs.
Professor Roy Pea is the David Jacks Professor of Education & Learning Sciences at Stanford University, with a courtesy appointment in Computer Science. He served as Director of the H-STAR Institute (2007-2021) and founded Stanford’s PhD program in Learning Sciences and Technology Design. His research focuses on technology-enhanced learning, social foundations of human learning, and interdisciplinary applications of digital tools. Stanford University, School of Education Graduate School of Education Department Courtesy appointment in Computer Science His work spans complex domains like concussion education, climate change learning, and AI-driven mental health interventions. He co-authored the 2010 National Education Technology Plan and co-edited key texts including Video Research in the Learning Sciences and AI in Education . His NSF-funded LIFE Center (2004-2014) advanced learning science theories. Recent publications address: (1) linguistic framing of concussions and reporting behavior, (2) AI chatbots for mental health, (3) "engineering fiction" to reduce climate change abstractness, and (4) immersive AR/LLM learning experiences. His research integrates data science, psychology, and educational technology. Fellow, American Academy of Arts and Sciences (2019) Inaugural Fellow, International Society of the Learning Sciences (2018) Honorary Doctorate, The Open University (2018) Best Bridging Paper, EDM 2014 LAK13 Best Paper Award (2013) Roy mentors doctoral and master’s students in learning sciences, advising on topics related to technology, cognition, and equity. He contributes to digital education policy through roles on advisory boards for organizations like NSF, NIH, and the Joan Ganz Cooney Center. His patents include methods for digital video analysis and collaborative learning systems.
LEE Mong Li is a Professor of Computer Science at the National University of Singapore (NUS) and serves as Director of the NUS Centre for Trusted Internet and Community. She holds a Ph.D., M.Sc., and B.Sc. (First Class Honours) in Computer Science from NUS, where she was awarded the IEEE Singapore Information Technology Gold Medal as the top Computer Science student in 1989. Her academic career includes a visiting fellowship at the University of Wisconsin-Madison (1999) and consultancy with QUIQ USA (2000). Her research spans Data Management, Spatio-temporal Databases, Biomedical Informatics, and Retinal Image Analysis . She has pioneered work in data cleaning, data fusion, and analysis of semistructured data, with applications in social media analytics and healthcare. Her recent publications demonstrate strong interdisciplinary focus, particularly in AI-driven medical diagnostics including diabetic retinopathy screening and chronic kidney disease detection from retinal images. She co-authored foundational books on 'Designing Semi-structured Database' and 'Temporal and Spatio-Temporal Data Mining'. Her 150+ publications in major database conferences and journals reflect leadership in both theoretical and applied research. Recent work shows significant emphasis on Medical AI applications (retinal analysis, kidney disease prediction) Temporal fact verification systems Misinformation detection in multimodal environments Privacy challenges in large language models Key honors include: Singapore's President Technology Award (2014) for co-inventing an AI system screening eye conditions IEEE Singapore Information Technology Gold Medal (1989) She actively contributes to government-funded multidisciplinary projects building practical deployable systems. Her leadership extends to program committees of prestigious database conferences and directing the NUS Centre for Trusted Internet and Community. She teaches BT5110 Data Management and Warehousing and has co-developed an AI system for diabetic retinopathy screening deployed in Singapore's national teleophthalmology program.
Abel Valenzuela Jr. is the Dean of Social Sciences and Professor of Labor Studies, Urban Planning, and Chicana/o and Central American Studies at the University of California, Los Angeles (UCLA). A faculty member since 1994, he has held leadership roles including chair of Chicana/o and Central American Studies, director of the Center for the Study of Urban Poverty, and special advisor to the chancellor on immigration policy. Currently, he leads UCLA’s Institute for Research on Labor and Employment (IRLE), overseeing units like the Labor Center, Labor Occupational Safety and Health Program (LOSH), and Human Resources Round Table (HARRT). Education PhD in Urban and Regional Studies, Massachusetts Institute of Technology (1993) MCP, Massachusetts Institute of Technology (1988) BA in Social Science, UC Berkeley (1986) His research focuses on precarious labor markets, immigrant workers, urban poverty, inequality, and the socio-economic implications of day labor. He has shaped national policy discussions on low-wage and immigrant labor through extensive publications. Valenzuela’s publications span topics like cosmopolitan politics, informal economy regulation, and comparative vulnerability studies. His work emphasizes intersections between migration, urban planning, and labor rights, with a geographic focus on Los Angeles and cross-national contexts. As director of IRLE, he has led initiatives integrating research, policy, and community engagement to address labor and employment challenges in Los Angeles and beyond.
