جست‌وجوی استاد و پژوهشگر

Tom Zickمشاهده پروفایل

پژوهشگر ارشد

• AI Governance
• Privacy
• Generative AI
• +۴ مورد دیگر

Tom Zick serves as Director of Responsible AI at Charles Schwab and holds an academic affiliation as a Research Fellow at Harvard University's Berkman Klein Center for Internet & Society. Her work bridges technical AI development and legal frameworks, focusing on governance mechanisms for emerging technologies. She has advised organizations from startups to Fortune 500 companies while collaborating with frontier AI labs and public institutions like the City of Boston on AI deployment and data governance initiatives. Her educational foundation includes a JD from Harvard Law School and a PhD in Astrophysics from UC Berkeley, providing interdisciplinary expertise critical to her research. This dual background enables rigorous analysis of complex technology-policy intersections. Zick's research centers on creating accountable AI systems through technical oversight frameworks and regulatory compliance strategies. She investigates generative AI's societal impacts, reinforcement learning risks, and privacy-preserving identity solutions like personhood credentials. Her work emphasizes red teaming, model alignment, and global regulatory harmonization, addressing both immediate implementation challenges and long-term existential risks through law-technology integration. Analysis of her publication trajectory reveals escalating focus on governance scalability as AI capabilities advance. Early work examined foundational risks in reinforcement learning, while recent publications address generative AI's disruption of education systems and the urgent need for cross-jurisdictional regulatory frameworks. Her taxonomy development for AI regulation demonstrates systematic approaches to navigating fragmented global policy landscapes. As an advisor, Zick has guided corporate and municipal entities through AI implementation challenges, notably helping Boston operationalize data governance frameworks. Her Berkman Klein fellowship involved direct collaboration with major AI labs on alignment research and red teaming exercises. She contributes to industry-wide initiatives including Twitter's decentralized social media project (bluesky), focusing on protocol-level solutions for content integrity. Zick's collaborative ecosystem spans frontier AI companies, academic researchers, and public sector innovators. Her current work with the City of Boston demonstrates practical governance implementation, while ongoing personhood credentials research addresses AI-generated content verification challenges. These partnerships reflect her commitment to translating theoretical frameworks into operational systems across multiple sectors.

Martin Henzمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Artificial Intelligence
• +۸ مورد دیگر

Martin Henz is an Associate Professor at the National University of Singapore , affiliated with the School of Computing and its Department of Computer Science . His academic journey includes an M.Sc. in Computer Science from Stony Brook University (1993) and a Dr.rer.nat. in Computer Science from Saarland University (1997). He has also worked as a Research Scientist at the German Research Centre for Artificial Intelligence. Research Focus : Scalable Experiential Learning, Systems for Teaching/Learning, AI in Education, Programming Languages, Algorithms, and Constraint Programming. Key Projects : Source Academy (immersive programming environment), Deep Teaching (LMS enhancements), and NUS Seafarers (maritime experiential learning). Publications span education technology, programming languages, and sustainable engineering, with recent works focusing on JavaScript-based pedagogy, automated question generation, and electric vehicle conversions. He supervised Rahul Singhal 's PhD, leading to the educational startup Cerebry, and co-founded Workforce Optimizer Pte Ltd with Alan Sevugan. Awards : NUS Annual Digital Education Award (2021) NUS Annual Teaching Excellence Award (2016/17) Fulbright Scholarship (1990) Startup @ Singapore Champion (2001)

Seth Kaplanمشاهده پروفایل

استاد

• Industrial/Organizational Psychology
• Employee Well-being
• Emotions at Work
• +۴ مورد دیگر

Seth Kaplan is a Professor in the Department of Psychology at George Mason University. His research focuses on employee well-being, team effectiveness, virtual work, and occupational health through projects like NSF-funded emotion regulation interventions and Army Research Institute collaborations on affective forecasting. He directs the KA-Lab, studying team resilience, metaperceptions, and statistical methodologies. Recent publications analyze job boredom, cognitive reappraisal interventions, and personality measurement innovations. His book Crisis-Ready Teams (2024) synthesizes data from high-risk environments. Courses taught include Occupational Health, Organizational Change, Psychometrics, and Multivariate Statistics. Grants: National Science Foundation (Co-PI): Just-in-Time Adaptive Interventions for Emotion Regulation Army Research Institute (PI): Affective Forecasting Errors Recent Presentations: Personality and generative AI use at work (SIOP 2025) Work situation identification via NLP (SIOP 2025) Helicopter helping in teams (SIOP 2025)

Yang Wangمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Domain Adaptation
• +۳ مورد دیگر

Dr. Yang Wang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on computer vision and machine learning, with a particular emphasis on domain adaptation, meta-learning, and privacy-preserving techniques. He actively advises prospective graduate students through a dedicated webpage outlining application procedures. Research interests include few-shot learning, test-time adaptation, and cross-modal applications such as handwritten text recognition and gaze estimation. His work explores how models can adapt dynamically to new domains using limited labeled data, with applications in crowd counting, medical data analysis, and cybersecurity. He also investigates privacy-preserving methods for deep learning models to protect user attributes and sensitive information. Recent publications highlight advancements in meta-auxiliary learning frameworks and efficient user adaptation techniques. His contributions span journals and conferences, showcasing innovations in both foundational machine learning methodologies and real-world applications.

David S. Marchمشاهده پروفایل

استادیار

• Social Psychology
• Implicit Cognition
• Threat Perception
• +۳ مورد دیگر

David S. March is an Assistant Professor in the Department of Psychology at Florida State University's College of Arts and Sciences. His research focuses on implicit cognition and threat processing, particularly how subconscious threat evaluation influences attitudes, prejudice, and behavioral responses. He actively recruits graduate students for Fall 2026 and oversees the March Research Laboratory. His research integrates social cognition, cognitive neuroscience, and behavioral psychology to challenge dual process models by introducing a speed-strength distinction between threatening and nonthreatening stimuli. Key areas include automacity of threat responses, racial bias mechanisms, and methodological advancements in mouse-tracking analysis. Dr. March's publications examine threat perception in contexts ranging from snake fear to police bias, contributing to understanding how implicit threat evaluations shape social behaviors and policy compliance. His work bridges evolutionary psychology with modern social issues like racial prejudice and pandemic health behaviors. Scientific Awards: Student Publication Prize by the Society for Personality and Social Psychology (2017)

Dinh Phungمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Generative AI
• +۸ مورد دیگر

Professor Dinh Phung is the Head of the Department of Data Science & AI at Monash University. His research focuses on machine learning, deep learning, generative AI, and robust AI systems. He has authored over 250 publications, with applications in NLP, computer vision, digital health, and cybersecurity. Phung holds a PhD and BSc(Hons) in Computer Science from Curtin University. He leads major projects like 'Can Machines Unlearn?' and 'Trustworthy Generative AI', funded by the Australian Research Council and the Department of Defence. Education: Doctor of Philosophy, Computer Science, Curtin University (2005) Bachelor of Science (Honours), Computer Science, Curtin University (2001) Research Interests: Machine learning, deep learning, and generative models Optimal transport and Bayesian methods Robust and trustworthy AI Applications in digital health, cybersecurity, and autism research Key Projects (2023–2029): Can Machines Unlearn? (2025–2029): Safety in AI Trustworthy Generative AI (2024–2026): Foundation models Robust Machine Learning via Optimal Transport (2023–2025) Awards and Grants: Australian Research Council grants for AI safety and robustness Department of Defence funding for robust learning systems Collaborations: Global partnerships in AI ethics, cybersecurity, and healthcare. Active advisory roles, including with the Victorian Parliamentary Library.

Bashir M. Al-Hashimiمشاهده پروفایل

استاد

• Energy-efficient mobile computing systems
• Low-power test and test-data compression of digital integrated circuits
• Energy-harvesting computing
• +۱ مورد دیگر

Professor Sir Bashir M. Al-Hashimi is currently Vice President (Research & Innovation) at King’s College London and holds the ARM Professorship in Computer Engineering there. He is also a Visiting Professor in Electronics and Computer Science at the University of Southampton. Prior to academia, he worked in the electronics design industry for eight years before joining the University of Southampton in 1999, where he became a personal Chair holder in 2004. His research focuses on energy-efficient computing systems, low-power testing, and energy-harvesting technologies, with a strong emphasis on smart city applications and wearable computing. He has led numerous interdisciplinary projects funded by the EPSRC and industry, including the PRiME Programme Grant and the EPSRC-funded Spatial Computational Learning consortium. He has supervised 45 PhD students and authored/co-authored nearly 400 technical papers, earning eight best paper awards and contributing to five books. His honors include a CBE (2018), knighthood (2025), Fellowship of the Royal Society (2023), and roles on the Research Excellence Framework panels. He founded the Arm-ECS industry-academia center in 2008, promoting energy-efficient computing research.

• Science Education
• Environmental Sociology
• Public Engagement with Science
• +۴ مورد دیگر

Noah Weeth Feinstein is an Associate Professor in the Department of Curriculum & Instruction and the Department of Community & Environmental Sociology at the University of Wisconsin–Madison's School of Education. He also serves as Director of the Robert E. and Jean F. Holtz Center for Science and Technology Studies. His research explores how people engage with science in personal, social, and political contexts, with a focus on educational platforms like museums and schools. Feinstein holds a PhD in Science Education from Stanford University (2008) and an MS in Biological Sciences (2006). His work bridges Science and Technology Studies (STS) with education, examining issues such as environmental sociology, equity in science museums, climate change adaptation, and responses to the 'post-truth' era. He contributed to a National Academies report on science literacy and has studied how museums can become more equitable institutions. His recent publications emphasize equity in science education, climate adaptation strategies, and public engagement frameworks. Notable works include discussions on community-level environmental literacy, the paradox of public knowledge in sociology, and the role of education in addressing climate change. Feinstein frequently presents at conferences like the American Educational Research Association, focusing on topics such as racial equity in museums and structural racism in science centers. Feinstein’s research integrates theoretical frameworks from sociology, education, and STS to address practical challenges in science communication and institutional change. His work highlights the need for education systems to foster collective sensemaking rather than individual truth-seeking in a polarized society.

Laura Wynnمشاهده پروفایل

استادیار

• Nursing Education
• Undergraduate Nursing Education
• Clinical Judgment
• +۱ مورد دیگر

Laura Wynn is an Assistant Professor at the Moffett & Sanders School of Nursing within Samford University. With a background in perinatal nursing and nursing education, she specializes in simulation-based pedagogy and clinical judgment development. Her work bridges hands-on clinical experience with innovative teaching methods. MSN from the University of West Georgia BSN from the University of Alabama at Birmingham Certified Nurse Educator Her research focuses on nursing education innovations, particularly the use of escape room simulations to enhance clinical judgment and adapt teaching during crises like the COVID-19 pandemic. She emphasizes maternal-child health and undergraduate training. Laura's publications highlight her work in simulation technology and curriculum design. These include escape room adaptations for renal impairment training, pandemic-era educational modifications, and maternal-newborn clinical workshops. Her methods often integrate interdisciplinary collaboration and critical thinking. Professional Affiliations Sigma Theta Tau International Alabama League of Nursing National League of Nursing Beyond academia, Laura mentors students through a Christian lens, aligning professional and personal values in nursing practice.

• Marketing Analytics
• Artificial Intelligence in Marketing
• Algorithmic Pricing
• +۵ مورد دیگر

Kannan Srinivasan is the H.J. Heinz II Professor of Management, Marketing and Business Technology at Carnegie Mellon University's Tepper School of Business, a position he has held since 1999. Prior to joining CMU, he taught at the business schools of the University of Chicago and Stanford University. His academic career spans over three decades with significant contributions to marketing science and data analytics. His educational background includes: Ph.D. in Management from University of California Los Angeles (1986) MBA in Marketing/Finance from Xavier School of Management, Jamshedpur, India (1980) BA in Engineering from University of Madras, Chennai, India (1978) Srinivasan's research focuses on advanced data analytics models applied to marketing problems, with particular expertise in internet-generated large-scale data analysis. His work bridges the gap between theoretical marketing models and practical business applications, especially in the areas of algorithmic pricing, consumer behavior analysis, and AI-driven marketing strategies. He has pioneered research in dynamic pricing systems, location-aware marketing technologies, and the economic implications of AI in consumer markets. Analysis of his recent publications reveals a strong trend toward examining the intersection of artificial intelligence, consumer welfare, and market dynamics. His work increasingly focuses on ethical implications of AI in marketing, algorithmic bias, and the socioeconomic impacts of digital platforms across various sectors including real estate, social media, and e-commerce. His scientific achievements include: Elected Fellow of the Informs Society of Marketing Science (2013) for lifetime contribution to the field Served as President of the Informs Society of Marketing Science Holds multiple patents related to time and location aware dynamic push content, dynamic pricing, and online advertising Srinivasan has advised numerous doctoral students whose careers have led them to faculty positions at top institutions including Duke, Harvard, Columbia, Yale, University of Chicago, Wharton, University of Michigan, and Indian Institute of Management Bangalore. He has extensive consulting experience with large firms and startups, translating academic research into practical business applications. His professional service includes editorial roles at prestigious journals including Management Science, Marketing Science, and Quantitative Marketing and Economics, as well as significant committee service within CMU including the Elliott D. Smith Award Committee and various Dean's Advisory committees. His research is organized around several key initiatives focused on applying advanced analytics to solve complex marketing problems, with particular emphasis on developing interpretable AI models that balance business objectives with consumer welfare considerations.

Oliver P. Johnمشاهده پروفایل

استاد

• Personality Psychology
• Social-Cognitive Processes
• Self-Perception Accuracy
• +۵ مورد دیگر

Oliver P. John is a Distinguished Professor at the University of California, Berkeley, directing the Berkeley Personality Lab . His research focuses on personality psychology, self-perception accuracy, emotion regulation, and life span development. Ph.D. from University of Oregon Developed the Big Five Inventory-2 (BFI-2) and its variants Research interests include: Self-concept and self-perception biases Personality development across adolescence and adulthood Cultural differences in personality expression Emotion experience, expression, and regulation strategies Recent publications emphasize cross-cultural validation of the BFI-2, personality development in childhood, emotion regulation dynamics, and social-emotional skills in educational contexts. Collaborations span global teams, with translations into 39 languages. Scientific contributions : Recipient of the L&S Distinguished Teaching Award in the Social Sciences (2002-03) Co-developer of the Emotion Regulation Questionnaire (ERQ) with James Gross Key publications on the Big Five taxonomy and developmental psychology Students and collaborators include researchers like Yi-Ke, Deb, Conrad, and Rosalinda, with alumni now leading studies in emotion, personality, and social psychology.

Scott Moffatمشاهده پروفایل

استاد

• Spatial Cognition
• Navigation
• Cognitive Aging
• +۲ مورد دیگر

Scott Moffat is a Professor of Psychology at Georgia Institute of Technology, affiliated with the School of Psychology. He holds a Ph.D. in Psychobiology & Clinical Neuropsychology from the University of Western Ontario (1998). His research focuses on the cognitive neuroscience of aging, particularly the interplay between hormonal systems (e.g., cortisol, testosterone, insulin) and spatial cognition, navigation, and brain aging. He employs neuroimaging (fMRI/PET), behavioral assessments, and biochemical assays to study these topics. A key innovation is his use of virtual reality environments to evaluate spatial memory in older adults. Research interests emphasize stress physiology, including cortisol’s role in hippocampal atrophy and Alzheimer’s risk, testosterone’s impact on cognitive aging, and insulin’s effects on neural function. His work highlights individual differences in cognitive aging and the biological mechanisms underlying such variability. He has published extensively on spatial navigation strategies, age-related neural changes, and the application of virtual technologies for cognitive assessment. Labs/Teams: Director of the Cognitive Neuroscience of Aging Lab at Georgia Tech’s Center for Advanced Brain Imaging. His lab investigates brain-behavior relationships in aging using multimodal neuroimaging and endocrine measures.

Lynn Carol Millerمشاهده پروفایل

استاد

• Health Communication
• Virtual Environments
• Behavioral Neuroscience
• +۷ مورد دیگر

Lynn Carol Miller is a Professor of Communication at the University of Southern California’s Annenberg School for Communication and Journalism. Her research focuses on leveraging virtual environments, AI agents, and computational models to address health-related social behaviors, particularly in HIV/AIDS prevention and mental health. Funded by NIH, CDC, and DARPA (over $20M), her work integrates neuroscience, behavioral science, and technology. She pioneered interventions like SOLVE (Socially Optimized Learning in Virtual Environments) and Systematic Representative Design. Education: PhD in Personality Psychology from University of Texas at Austin. Key areas include health communication, gaming for behavior change, and computational modeling of social processes. She has supervised 17 doctoral students and collaborators across universities globally. Research emphasizes scalable interventions using fMRI-compatible tools and virtual reality. Notable contributions include reducing shame in HIV prevention games and analyzing neural correlates of risk-taking behaviors. Awards include the Early Career Award (2003) and ICA’s Outstanding Contribution to Communication Science (2020). Labs/Teams: Active in multidisciplinary teams at USC and collaborating institutions, focusing on virtual environment design, AI-driven interventions, and neurobehavioral studies. Current projects explore AI for public health and inclusive avatar representations in social VR.

Andrew Thomas Campbellمشاهده پروفایل

استاد

• Ubiquitous Computing
• Machine Learning
• Human-Computer Interaction
• +۳ مورد دیگر

Andrew Thomas Campbell is a Professor and Albert Bradley 1915 Third Century Professor in the Department of Computer Science at Dartmouth College. His research focuses on ubiquitous computing, machine learning, and mental health, particularly using mobile and wearable sensors to assess and manage mental illnesses. He leads the StudentLife project, which tracks college students' mental health over four years, and co-directs the HealthX Lab. Campbell's work has received prestigious awards, including the ACM UbiComp 10-Year Impact Award for pioneering mobile sensing in mental health. He previously held tenure as an Associate Professor at Columbia University and has industry experience at Google and Verily. His research spans $42M in grants from NIH, NSF, and corporate partners, emphasizing technology-driven solutions for mental health challenges. Education: B.Sc. from Aston University, M.Sc. from City University, Ph.D. from Lancaster University. He teaches CS 1 Introduction to Programming and mentors numerous students. Awards include the Dean of the Faculty Award for Mentoring (2025) and multiple ACM Test of Time Awards. His lab collaborations involve跨学科 teams addressing mental health through AI and sensing technologies.

Sarah Masud Preumمشاهده پروفایل

استادیار

• Human-AI Interaction
• Natural Language Processing
• Applied Machine Learning
• +۴ مورد دیگر

Sarah Masud Preum is an Assistant Professor of Computer Science at Dartmouth College, with adjunct roles in the Department of Biomedical Data Science at Geisel School of Medicine and as Faculty Affiliate at the Center for Technology and Behavioral Health (CTBH). She also serves as Technical Associate Director of the Dartmouth Center for Precision Health and Artificial Intelligence. Her work focuses on machine learning for computational health, including natural language processing, temporal modeling, and human-AI interaction to develop personalized decision support systems in healthcare. Education includes a B.Sc. from Bangladesh University of Engineering and Technology, followed by M.Sc. and Ph.D. degrees from the University of Virginia. Previously, she was a postdoctoral research scholar at Carnegie Mellon University's School of Computer Science, recognized as a Rising Stars in EECS (2020) for her academic excellence and contributions to equity in STEM. Her research interests span Human-AI Interaction, Natural Language Processing, Mobile Health, and Cyber-Physical Systems. Over 2020–2023, her publications emphasize AI-driven solutions for healthcare challenges like conflict detection in health information and cognitive assistants for emergency response. Earlier work includes behavioral prediction models (MAPer) and spatial database optimizations (Maximum Visibility Queries). Awards: Rising Stars in EECS (2020) In teaching, she offers courses like Transforming Healthcare through Machine Learning and Machine Learning and Statistical Data Analysis. Her affiliations with multidisciplinary centers reflect her commitment to bridging technology and healthcare.