جستجوی استاد راهنمای دانشگاهی

Mark Y. Liberman is the Christopher H. Browne Distinguished Professor of Linguistics and Trustee Professor at the University of Pennsylvania. He holds a joint appointment in the Department of Linguistics and the Department of Computer and Information Science. His roles include Director of the Linguistic Data Consortium (LDC), Faculty Director of Ware College House, and former Director of the Institute for Research in Cognitive Science. Education: A.B. in Linguistics and Applied Mathematics from Harvard University (1965–1969), M.S. (1972) and Ph.D. (1975) in Linguistics from MIT. Research focuses on corpus-based phonetics, clinical linguistics applications, tonal phonology, formal models for linguistic annotation, and computational linguistics. He explores speech production, prosody, and interdisciplinary topics like language evolution and neurobiology of speech. Recent articles highlight advancements in speech biomarkers for neurodegenerative diseases, autism analysis, and computational linguistics. Awards include Fellowships from the AAAS and Linguistic Society of America. He advises graduate students and leads large-scale language resource initiatives like LDC, contributing to open-access linguistic datasets. Labs/Teams: Linguistic Data Consortium (LDC), Institute for Research in Cognitive Science (IRCS), and collaborations in computational linguistics and neuroscience.

• Corpus Linguistics
• Speech and Language Technology
• Clinical Linguistics
• +۴ مورد دیگر

Russell Epstein is a Professor and Director of Graduate Studies in the Department of Psychology at the University of Pennsylvania. He is affiliated with the Center for Cognitive Neuroscience and Goddard Labs. His research focuses on neural mechanisms underlying visual scene perception, spatial navigation, and memory. Epstein holds a BA in Physics from the University of Chicago and a PhD in Applied Mathematics from Harvard University. Epstein’s research interests include high-level vision, spatial cognition, and the neural basis of environmental representations. His lab uses functional MRI and cognitive neuroscience techniques to study how scenes, objects, landmarks, and spaces are encoded in brain systems such as the parahippocampal place area and retrosplenial cortex. Recent work explores cognitive maps, grid-like neural representations, and the role of multisensory cues in navigation. His articles emphasize spatial navigation strategies, hierarchical cognitive maps, and the interplay between perception and memory. Notable contributions include investigations into hippocampal spatial metrics, olfactory navigation, and the neural underpinnings of environmental learning. Epstein teaches courses on cognitive neuroscience, including PSYC 149 and PSYC 600. He advises two graduate students in Psychology and has no listed scientific awards. His work is supported by grants (unspecified) and conducted within collaborative teams at the Center for Cognitive Neuroscience. Epstein’s research extends to labs focused on spatial cognition and neuroimaging, advancing understanding of how humans mentally map environments through visual and sensory integration.

• Cognitive Neuroscience
• Behavioral Neuroscience
• Spatial Navigation
• +۴ مورد دیگر

Olga Russakovsky is an Associate Professor of Computer Science at Princeton University and Associate Director of the Princeton Laboratory for Artificial Intelligence. Her research focuses on computer vision , machine learning , human-computer interaction , and fairness, accountability, and transparency in AI systems. Princeton University faculty member since 2025 Affiliated with Princeton's Center for Statistics and Machine Learning and Center for Information Technology Policy Scientific Recognition: Presidential Early Career Award for Scientists and Engineers (2025) PAMI Young Researcher Award (2022) AnitaB.org Emerging Leader Abie Award (2020) CRA-WP Anita Borg Early Career Award (2020) MIT Technology Review 35-under-35 Innovator (2017) PAMI Everingham Prize (2016) As a co-founder and current Board Chair of AI4ALL , she drives initiatives to expand diversity in AI. Her recent publications demonstrate expertise in vision-language models , deepfake detection , and ethical AI systems .

• Computer Vision
• Machine Learning
• Human-Computer Interaction
• +۷ مورد دیگر

Shahram Ghiasinejad is a Senior Lecturer in the Department of Psychology at the University of Central Florida (UCF), affiliated with the College of Sciences. He joined UCF in 2007 and specializes in education technology, student engagement, and equity in academic settings. Dr. Ghiasinejad holds a B.A. in Computer Science from the University of Texas at Austin, and an M.S. and Ph.D. in Cognition and Neuroscience from the University of Texas at Dallas. Bachelor of Arts: Computer Science, University of Texas at Austin Master of Science: Applied Cognition and Neuroscience, University of Texas at Dallas Doctor of Philosophy: Cognition and Neuroscience, University of Texas at Dallas His research focuses on leveraging experimental and computational methods to understand human language comprehension, alongside innovative approaches to support underrepresented students through multimedia tools and undergraduate research initiatives. Recent work emphasizes equity and engagement in higher education, including strategies for transfer students and first-generation learners. Publications highlight themes such as JoVE video integration for marginalized students, the role of undergraduate research in fostering equity, and creative solutions for academic challenges faced by underrepresented groups. While no formal awards are listed, his work underscores a commitment to inclusive education and student success.

• Education Technology
• Student Engagement
• Equity in Education
• +۳ مورد دیگر

Antonio Rangel is the Bing Professor of Neuroscience, Behavioral Biology, and Economics at the California Institute of Technology (Caltech), where he also serves as Head Faculty in Residence. He is a faculty member in the Division of Humanities and Social Sciences (HSS) with research focusing on the computational and neurobiological basis of value-based decision-making. Dr. Rangel received his educational training at prestigious institutions: B.Sc. from Caltech in 1993 M.S. from Harvard University in 1996 Ph.D. in 1998 Professor Rangel's research lies at the intersection of neuroscience, economics, and psychology, with a focus on understanding how the brain makes decisions. His work investigates the neural mechanisms underlying value computation, choice processes, self-control, and social decision-making. Using a multidisciplinary approach that combines functional magnetic resonance imaging (fMRI), eye-tracking, computational modeling, and behavioral experiments, his lab has made significant contributions to the field of neuroeconomics. His research has revealed how value signals are represented in the brain, how attention influences choice, and the neural basis of self-control failures. Professor Rangel has pioneered methods for studying decision processes with high temporal resolution using eye-tracking data, demonstrating how fixation patterns relate to value computations and choice outcomes. His work spans from theoretical frameworks of value-based decision-making to practical applications in behavioral public economics. Professor Rangel's work has been recognized with prestigious awards: 2019 NOMIS Distinguished Scientist Award 2018 Fellow of the Association for Psychological Science As an academic leader, Professor Rangel has mentored numerous students and researchers who have gone on to make their own contributions to neuroscience and economics. His lab, the Rangel Neuroeconomics Laboratory at Caltech, serves as a hub for interdisciplinary research, bringing together students and scholars from neuroscience, economics, psychology, and computer science. The lab has received significant funding to support its research on the neural basis of decision-making, including support from the NOMIS Foundation. The Rangel Neuroeconomics Laboratory is equipped with state-of-the-art facilities including fMRI analysis capabilities, eye-tracking systems, and computational resources for modeling decision processes. The lab fosters a collaborative environment where researchers apply methods from experimental economics and cognitive neuroscience to unravel the complexities of human decision-making.

• Neuroeconomics
• Decision Neuroscience
• Behavioral Economics
• +۴ مورد دیگر

Marina Agranov is Professor of Economics at the California Institute of Technology (Caltech), affiliated with the Division of Humanities and Social Sciences. She directs research through the Ronald and Maxine Linde Institute of Economic and Management Sciences, Center for Social Information Sciences (CSIS), and Center for Theoretical and Experimental Social Sciences (CTESS), and serves as Research Associate at the National Bureau of Economic Research (NBER). Her academic credentials include a B.A. from St. Petersburg State Technical University (1999), M.A. from Tel Aviv University (2004), and Ph.D. from New York University (2010). She joined Caltech as Assistant Professor in 2010 and was promoted to full Professor in 2017. Agranov's research pioneers experimental and behavioral economics, focusing on strategic decision-making in bargaining games, social learning environments, network interactions, and information dynamics. Her work examines how individuals form beliefs and navigate tensions between personal goals and collective outcomes, often using controlled laboratory experiments to test theoretical predictions about human behavior under uncertainty. Her recent publications reveal a consistent methodological approach: blending game-theoretic models with experimental validation to investigate communication effects, randomization preferences, and institutional design. Key trends include analyzing how uncertainty impacts committee negotiations, how complexity influences egalitarian outcomes in legislative bargaining, and how information structures shape social learning on networks. Her scientific recognition includes: Associated Students of Caltech (ASCIT) Teaching Award (2017-18) Professor Agranov's research has secured significant institutional support through Caltech centers and NBER affiliation, with findings featured in major economics journals and Caltech news coverage including "Decision by Committee: How Uncertainty Shapes Negotiations" (December 2024) and "Experimental Economics in Theory and Practice" (July 2023). Her work on committee decision-making under uncertainty has direct implications for institutional design in political and corporate governance. She actively contributes to Caltech's research ecosystem through CSIS and CTESS, which facilitate interdisciplinary collaborations in social sciences and experimental methodology development.

• Experimental Economics
• Behavioral Economics
• Political Economy
• +۳ مورد دیگر

Natalie H. Brito is an Associate Professor of Applied Psychology at New York University (NYU), affiliated with the Steinhardt School of Culture, Education, and Human Development. Her research focuses on how early social and cultural contexts shape neurocognitive development in infants and toddlers, particularly in areas of attention, memory, and socio-emotional skills. Prior to NYU, she completed a postdoctoral fellowship at Columbia University Medical Center and was a Robert Wood Johnson Health and Society Scholar. Dr. Brito’s work bridges developmental psychology, neuroscience, and public policy, emphasizing the need for equitable environments that support healthy child development. She has received prestigious awards such as the APS Rising Star Award and NIH grants, reflecting her impactful contributions to understanding developmental trajectories. Her research also extends to policy implications, such as the effects of paid maternal leave on infant brain function and the role of structural inequities in maternal mental health. Key themes include early life stress, gut microbiome influences, and the neurobiological underpinnings of cognitive development. Dr. Brito has published extensively in journals like Child Development , Developmental Cognitive Neuroscience , and JAMA Psychiatry , with a focus on innovative methodologies (e.g., the OWLET gaze-tracking tool). She teaches courses on developmental psychology and the principles of applied psychology, fostering interdisciplinary approaches to human development. Her scientific accolades include recognition from the International Society of Developmental Psychobiology and the American Psychological Association, underscoring her leadership in advancing developmental science and equity-focused research.

• Developmental Psychology
• Neurocognitive Development
• Early Childhood Development
• +۳ مورد دیگر

Richard E. Mayer is a Distinguished Professor of Psychology at the University of California, Santa Barbara, affiliated with the College of Letters & Science. His work bridges cognition, instruction, and technology to advance understanding of how people learn and how to design effective educational interventions. Research focuses on multimedia learning , computer-supported learning environments , and computer games for learning Current projects examine immersive virtual reality, generative learning strategies, and social cues in online instruction Recipient of top honors: Thorndike Award, Scribner Award, and APA’s Distinguished Contribution Award Principal Investigator on grants from the Office of Naval Research , Institute of Education Sciences , and National Science Foundation He leads the Mayer Lab for Research on Learning and Instruction, which emphasizes learning for transfer —ensuring learners apply knowledge in new contexts. His research has established 12 instructional design principles for online learning environments.

• Educational Psychology
• Multimedia Learning
• Instructional Design
• +۴ مورد دیگر

Lyle Ungar is a Professor at the Department of Computer and Information Science at the University of Pennsylvania . He is affiliated with multiple graduate groups, including Genomics and Computational Biology in the School of Medicine , Operations, Information and Decisions in the Wharton School , and Psychology in the School of Arts and Sciences . His research focuses on explainable machine learning , deep learning , and natural language processing for psychology and medical research , analyzing social media and sensor data to understand well-being, empathy, and stress. His work spans bioinformatics , applied economics , and group decision-making . Recent publications examine LLM-based tutoring , cross-cultural translation , and AI in palliative care , showing trends in reinforcement learning , mobile health , and health data analytics . He has contributed to Google Scholar , PubMed , and DBLP with over 15 papers since 2023. Scientific Awards : 2019 Alan I. Leshner Leadership Institute Public Engagement Fellow His students include Vitoria Aquino Guardieiro , Yihao Li , and co-advised researchers like Shreya Havaldar with Eric Wong. He leads projects at interdisciplinary centers such as the Annenberg Public Policy Center , Center for Cognitive Neuroscience , and Institute for Translational Medicine .

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۱۵ مورد دیگر

Robert Wilson is an Associate Professor in the School of Psychology at Georgia Institute of Technology. His research focuses on computational cognitive neuroscience, reinforcement learning, decision making, and their applications in psychiatry and aging. Wilson leads a lab integrating computational modeling with behavioral experiments, neuroimaging, and neurostimulation to explore the algorithms underlying human cognition. He holds a Ph.D. in Bioengineering from the University of Pennsylvania (2009). Education: Ph.D. in Bioengineering, University of Pennsylvania, 2009 Research Interests: Wilson’s work spans computational models of decision making, reinforcement learning dynamics, and the neural mechanisms of explore-exploit trade-offs. His lab investigates phishing detection cognition, navigation strategies, and perceptual decision making, with recent studies on aging-related cognitive decline and psychiatric disorders. Publications: His recent work includes studies on computational models of exploration strategies, phishing susceptibility (PEST task), and aging effects on decision-making. Articles often bridge neuroscience and AI, such as applying reinforcement learning to large language models. Awards & Grants: While no formal awards are listed, his research has been supported by grants exploring computational psychiatry and neuroimaging. Labs & Teams: Wilson directs a multidisciplinary lab at Georgia Tech, collaborating with experts in AI, neuroscience, and clinical psychology to advance computational theories of the mind-brain relationship.

• Computational Cognitive Neuroscience
• Reinforcement Learning
• Decision Making
• +۷ مورد دیگر

Dima Amso is a Professor of Psychology at Columbia University , affiliated with the Department of Neuroscience & Behavior . Their research focuses on human brain and cognitive development , particularly the sophisticated attention, learning, and memory systems in infants. Ph.D. from New York University (2005) Director of the Developmental Cognitive Neuroscience Lab Key themes: neural plasticity in infancy , adaptive cognitive development , global cross-cultural research (NYC, Jordan, Ghana, South Africa, Malawi) Their lab investigates how interactive attention and learning systems in early childhood enable adaptation to environmental risks and opportunities, with findings applied to partnerships with local and global nonprofit organizations to improve children's programming. Current projects explore the intersection of experience and cognitive plasticity , leveraging novel discoveries about infant learning mechanisms.

• Developmental Psychology
• Developmental Cognitive Neuroscience
• Infant Brain Development
• +۳ مورد دیگر

Dr. Katerina Marcoulides is an Associate Professor in the Quantitative and Psychometric Methods Program at the University of Minnesota's Department of Psychology. She is affiliated with the Minnesota Population Center and serves as Co-Chair of the Structural Equation Modeling Special Interest Group (SEM SIG) for the American Educational Research Association. Her research focuses on advanced data mining and modeling techniques for complex longitudinal data, particularly applied to developmental processes in economically disadvantaged immigrant children. She holds a PhD in Quantitative Psychology from Arizona State University, an MA from UC Davis, and a BA from UC Santa Barbara. Education: PhD: Quantitative Psychology, Arizona State University MA: Quantitative Psychology, University of California, Davis BA: Psychology (minor in Education), University of California, Santa Barbara Research Interests: Dr. Marcoulides develops and applies statistical methods such as structural equation modeling (SEM), Bayesian synthesis, and data fusion to study developmental and educational processes. Her work emphasizes longitudinal data analysis, item response theory, and multilevel modeling. Recent projects include NIH-funded research on parenting, marginalization, and well-being during the pandemic. Awards: APS Rising Star Award (2021) NIH Grant Award Teaching & Collaboration: She teaches courses on SEM, multilevel modeling, and data analysis at the University of Minnesota. Previously at the University of Florida, she contributed to workshops on educational data mining and served as an APA Advanced Training Institute presenter. Her interdisciplinary collaborations span population studies, health inequities, and workforce research. Labs & Groups: She leads the Data Analytics and Visualization Lab and actively participates in the Minnesota Population Center, integrating computational and statistical innovations with real-world applications.

• Data Mining
• Structural Equation Modeling
• Longitudinal Data Analysis
• +۳ مورد دیگر

Dr. Kenneth Joseph is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo , part of the School of Engineering and Applied Sciences . He serves as Associate Director of the Institute for Artificial Intelligence and Data Science and leads the Computation and Equity Lab (cubelab) , focusing on social inequality through computational measures and models. Education: PhD, MS, and BS in Societal Computing from Carnegie Mellon University (2016, 2012, 2010) Research Interests: Computational Social Science, Network Science, Gender Studies, and AI for Social Good Notable Work: Gender disparities in academia, predictive modeling for foster care and urban policy, and social media rumor analysis Awards: UB Exceptional Scholar—Young Investigator Award (2021) Advising: Mentored students like Yuhao Du, Jason Yan, Arjunil Pathak, and Navid Madani on projects spanning Twitter bios, foster youth services, and algorithmic fairness.

• Computational Social Science
• Social Inequality
• Network Science
• +۳ مورد دیگر

Susan J. Simkins is a Professor of Psychology at The Pennsylvania State University, where she serves as Lead of the CTSI-Team Science Core and is based in Moore Building at University Park. Her contact details include email sxm40@psu.edu and phone (814) 863-7387. Education Ph.D., Ohio State University, 1996 Research Interests Dr. Simkins' research centers on effective teamwork and performance through three interconnected streams: team composition/diversity (examining demographic, cognitive, and personality-based diversity within contingency frameworks), team cognition/mental models (focusing on shared understanding of tasks and teamwork dynamics), and temporal integration in teams (investigating time-based diversity, temporal leadership, and pacing styles). Her work emphasizes individual differences, cognitive processes, and temporal dynamics as critical determinants of team effectiveness in organizational contexts. Publication Trends Her 2013-2017 publications reveal a strong focus on temporal dimensions of teamwork, including polychronicity diversity, temporal conflict in specialized teams (e.g., culinary environments), and time-sensitive mental models. Key methodological approaches involve multilevel analysis and contingency frameworks, with applications spanning leadership theory, decision-making diversity, and climate interactions. Work appears consistently in top organizational psychology journals like Journal of Applied Psychology and Organizational Behavior and Human Decision Processes. Scientific Awards No scientific awards were documented in the provided text. Advising and Grants While the text confirms her faculty role and research leadership, specific details about graduate student advising, grant funding, or sponsored projects were not included in the source material. Labs and Teams Dr. Simkins leads the CTSI-Team Science Core, an initiative dedicated to advancing methodologies for studying team-based research structures and improving collaborative effectiveness in scientific and organizational settings.

• Teamwork and Team Performance
• Leadership
• Decision Making
• +۳ مورد دیگر

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.

• Early Childhood
• Multilingual Learners
• Bilingualism and Bilingual Education
• +۱۲ مورد دیگر