جستجوی استاد راهنمای دانشگاهی

Elaine Francis is a Professor of English and Linguistics at Purdue University's College of Liberal Arts, where she serves as Associate Head of the Department of English and directs the Experimental Linguistics Lab. She holds additional affiliations as an Affiliate Faculty Member in the Department of Linguistics and a Courtesy Faculty Member in the Department of Speech, Language, and Hearing Sciences. Ph.D. in Linguistics, University of Chicago (1999) B.A. in Linguistics, College of William and Mary (1993) MA in Linguistics, University of Chicago (1995) Former Assistant Professor at the University of Hong Kong (1999-2002) Professor Francis's research focuses on syntax and its interfaces with semantics, discourse information structure, and language processing in production and comprehension. She employs experimental methods to investigate syntactic, semantic, discourse-pragmatic, and cognitive factors underlying complex sentence structures. Her primary research areas include word order alternations, filler-gap dependencies, resumptive pronouns, and grammatical acceptability. She examines how various factors contribute to grammatical alternations in language use and explores how processing pressures in production and comprehension contribute to grammatical conventions. Her recent publication record shows consistent output across multiple linguistic subfields, with a strong emphasis on experimental syntax and psycholinguistics. Her 2022 book, Gradient Acceptability and Linguistic Theory , represents a significant contribution to understanding acceptability judgment tasks in relation to syntactic theory. Her work spans theoretical syntax, experimental linguistics, second language acquisition, and cross-linguistic comparison, often bridging the gap between theoretical frameworks and empirical evidence. Regularly teaches short courses at Linguistic Society of America Linguistic Institutes Member of Linguistic Society of America Ethics Committee Editorial board member of Glossa Psycholinguistics Co-editor of Polymorphous Linguistics: Jim McCawley's Legacy (2005) Co-editor of Mismatch: Form-Function Incongruity and the Architecture of Grammar (2003) Professor Francis actively supervises graduate students in linguistics, though she has indicated she will be unable to take on new graduate students for the 2025-2026 academic year. She has received research support for her experimental work, particularly for investigating syntactic phenomena through controlled experiments and corpus analysis. Her collaborative work extends across multiple institutions and disciplines, including collaborations with researchers in computational linguistics, cognitive science, and clinical linguistics. She directs the Experimental Linguistics Lab at Purdue University, which conducts research on syntactic processing using various experimental methodologies. The lab investigates how speakers produce and comprehend complex sentence structures, with particular attention to how grammatical knowledge interacts with processing constraints. Current projects include research on relative clauses, syntactic islands, and acceptability gradient phenomena across multiple languages.

• Syntax
• Psycholinguistics
• Relative Clauses
• +۶ مورد دیگر

Jackie Chit Kit Cheung is an Associate Professor in the School of Computer Science at McGill University, where he co-directs the Reasoning and Learning Lab. He holds the Canada CIFAR AI Chair and serves as an Associate Scientific Co-Director at the Mila Quebec AI Institute. He is also a consulting researcher at Microsoft Research Montreal. Academic Background: Ph.D. in Computer Science, University of Toronto (2010–2014) M.Sc. in Computer Science, University of Toronto (2008–2010) B.Sc. (Honours) in Computer Science, minors in Linguistics and German, University of British Columbia (2004–2008) Research Interests: Jackie Cheung's research lies at the intersection of natural language processing, machine learning, and cognitive science. He focuses on natural language generation , automatic summarization , commonsense and pragmatic reasoning , and the evaluation of NLP systems . His work aims to build language models that reflect real-world structure and reasoning, with applications in health, education, and language revitalization. He is particularly interested in how implicit meaning is processed in context, a core concern in linguistic pragmatics. Publication Trends: His recent publications (2024–2025) show a strong emphasis on evaluation methodologies (e.g., COSMIC, ECBD), hallucination and factuality in language models, coreference and reasoning , and long-context modeling . He frequently collaborates across institutions and integrates insights from linguistics and psychology into NLP system design and analysis. Scientific Awards: Best Paper Award, ACL 2018 Outstanding Paper Award, NAACL 2018 Student Research Workshop SAC Award, ACL 2024 (for COSMIC) Best Poster Award, CMDO AI-Health Symposium 2024 Advising and Grants: He advises a large and diverse group of graduate students, including PhD and Master’s candidates, often in co-supervision with other faculty. His group has received support from major AI and health research initiatives, including CIFAR and Mila. He has trained alumni who have gone on to faculty and industry research positions. He has served in leadership roles in top NLP conferences, including as Senior Area Chair, Workshop Chair, and Program Chair of Canadian AI 2018. Labs and Teams: He co-directs the Reasoning and Learning Lab at McGill and is deeply involved with Mila – Quebec AI Institute . He founded the NLP Reading Group at McGill, which brings together researchers from computer science, linguistics, and information studies to discuss theoretical and applied NLP topics.

• Natural Language Processing
• Natural Language Generation
• Automatic Summarization
• +۱۲ مورد دیگر

Dean Eckles is an Associate Professor of Marketing at MIT Sloan School of Management and serves as an Associate Director of the MIT Institute for Data, Systems, and Society (IDSS). He is also affiliated with the MIT Schwarzman College of Computing through the Institute for Data, Systems & Society and its Statistics and Data Science Center. Additionally, he leads the analytics research area at the Initiative on the Digital Economy and organizes the annual Conference on Digital Experimentation (CODE@MIT). His educational background includes a BA in philosophy, BS and MS in cognitive science, MS in statistics, and PhD in communication, all from Stanford University. Prior to joining MIT, Eckles worked as a scientist at Facebook, where he contributed to areas including News Feed, messaging, advertising, tools for randomized experiments, and survey methods. He previously held research positions at Nokia and Yahoo. Eckles's research primarily focuses on social influence mediated by interactive technologies, examining how communication technologies mediate, amplify, and direct social influence. His work spans multiple specific areas including social interactions, contagion, and interventions in networks; experimental design and inference in networks; and methods for causal inference. His research often combines social science with advanced statistical methods. His notable publications include research on long ties in social networks and their relationship to economic prosperity, how network structure affects social contagions, and algorithmic transparency in social media platforms. His work has appeared in prestigious journals including PNAS and Nature Human Behaviour, and he has provided expert testimony before the US Senate on algorithmic ranking. Long ties, disruptive life events and economic prosperity (PNAS) Long ties accelerate noisy threshold-based contagions (Nature Human Behaviour) Algorithmic transparency and assessing effects of algorithmic ranking (Senate testimony) Eckles actively shares his research through social media platforms including Bluesky, Twitter, and Mastodon, as well as through his blog and contributions to the Gelman et al. blog. His work bridges academic research with practical applications in technology and policy.

• Social Influence
• Network Analysis
• Causal Inference
• +۴ مورد دیگر

Qianwen Wang is a tenure-track Assistant Professor in the Computer Science department at the University of Minnesota, Twin Cities. Her research combines interactive visualization with interpretable machine learning to foster intuitive, efficient, and reliable Human-AI collaboration. She actively seeks motivated students, research assistants, and interns to join her dynamic research team at UMN CS. Dr. Wang's research focuses on three primary themes: Human-AI Collaboration, where she designs tools to facilitate Human-AI interaction; Automatic & Intelligent Visualization, where she develops techniques to make visualizations accurately interpreted and easily used; and VIS+(X)AI in Biomed/Healthcare, where she studies how visualization and explainable AI can promote scientific discoveries in biomedicine and healthcare. Her work has made significant contributions to visualization, human-computer interaction, and bioinformatics, with particular applications in biomedical knowledge graphs and single-cell omics analysis. Her recent publications demonstrate a strong trend toward integrating visualization with large language models and graph neural networks for biomedical applications. She has published extensively at top venues including IEEE VIS, ACM CHI, and Nature Medicine, with a focus on making AI systems more interpretable and useful for domain experts, particularly in healthcare contexts. Her work often bridges theoretical advances in visualization with practical applications in genomics and healthcare. Two IEEE VIS Honorable Mention Awards (2022, 2024) Best Paper Award from IMLH@ICML 2021 Two Best Abstract Awards from BioVis ISMB (2021, 2022) HDSI Postdoctoral Research Fund Award Research covered by MIT News and Nature Technology Features Dr. Wang actively contributes to the academic community through service roles including General Chair for ISMB BioVis, VisNotes and Poster Chair for IEEE PacificVis, and Program Committee member for IEEE VIS, ACM CHI, and ACM IUI. Her research has been supported by various grants that enable her team to develop innovative visualization techniques and explore their practical applications in biomedical domains. Her research group maintains an active presence in the visualization and HCI communities, with members participating in major conferences and workshops. The lab focuses on creating tools that bridge the gap between complex AI models and human understanding, with particular emphasis on making these technologies accessible and useful for domain experts in biomedical research.

• Interactive Visualization
• Interpretable Machine Learning
• Human-AI Collaboration
• +۵ مورد دیگر

Loreta Vilkienė is a Professor at the Department of Lithuanian Studies, Vilnius University, since October 2020, and served as its Head from 2018–2023. She has been affiliated with Vilnius University since 2007, initially as an Associate Professor, and has lectured since 2001. Her academic background includes a PhD in Humanities (2000) and a qualification as a philologist and teacher of Lithuanian (1986), both from Vilnius University. Education: PhD in Humanities, Vilnius University (2000) Philologist and Teacher of Lithuanian, Vilnius University (1986) Research Interests: Applied linguistics (foreign language teaching/assessment, language attrition, partial acquisition) and sociolinguistics (linguistic attitudes, diaspora language dynamics, language-identity links). Her work focuses on multilingualism, heritage language maintenance, and sociolinguistic transitions in post-Soviet contexts. Article Trends: Recent publications analyze language attitudes in Lithuania, lexical proficiency in native speakers, diaspora language policies in Kazakhstan and Russia, and sociolinguistic impacts on identity. Her studies integrate quantitative methods (e.g., vocabulary size estimation) and qualitative discourse analysis. Scientific Awards: Recipient of the 2006 Lietuvos Science Award (applied sciences) for collaborative work on Lithuanian language pedagogy. Grants & Projects: Managed EU-funded projects like ARQUS (2020) and international diaspora language studies (2020–2022). Active in UNESCO-related language preservation initiatives and digital outreach platforms. Outreach: Delivered public lectures on diaspora identity, contributed to podcasts, and authored 15+ peer-reviewed articles. Co-developed teaching tools like the Po truputį Lithuanian language series.

• Applied Linguistics
• Foreign Language Teaching and Acquisition
• Language Testing
• +۹ مورد دیگر

Nancy M. Wells is a Professor in the Department of Human Centered Design and serves as the Senior Associate Dean for Research and Graduate Education in the College of Human Ecology at Cornell University. Her work bridges environmental psychology and public health, examining how built and natural environments impact human health and behavior across the lifespan. Dr. Wells received a joint PhD in Psychology and Architecture from the University of Michigan and completed National Institute of Mental Health (NIMH) post-doctoral training at the University of California, Irvine. Her educational background uniquely positions her to investigate the intersection of physical environments and human wellbeing through both psychological and architectural lenses. Her research focuses on how environmental contexts—from homes to neighborhoods to schools—affect health outcomes, cognitive functioning, and resilience. A central theme examines nature's role in human resilience, particularly how natural environments buffer against adversity and challenge. She has conducted influential work on school gardens and their effects on children's physical activity, dietary habits, and learning. More recently, she has pioneered research on nature and autism, conducting a randomized controlled trial examining natural environments' effects on autistic youth wellbeing. Analysis of Dr. Wells' recent publications reveals consistent focus on nature's health benefits, with strong emphasis on experimental methodologies including randomized controlled trials and natural experiments. Her work spans environmental psychology, public health, and education, with particular attention to vulnerable populations including low-income communities and children of color. NSF Funding for environmental health research USDA Funding for school garden studies Robert Wood Johnson Foundation Funding MacArthur Foundation Funding Senior Associate Editor of Environment and Behavior (4 years) Research Advisory Board of Children and Nature Network Board of Directors for reDirect Dr. Wells actively mentors undergraduate and graduate students through the Wells Lab, involving them in all research stages from data collection to publication. Her research has been supported by multiple significant grants examining housing quality effects on mental health, neighborhood design impacts on physical activity, and school garden interventions. She leads interdisciplinary research teams that integrate perspectives from environmental psychology, public health, landscape architecture, and education. The Wells Lab operates as an integrated research-teaching-outreach unit that develops practical yet rigorous studies to assess causal relations between environment and health, creates valid measurement tools, and identifies causal pathways. Current projects include examining nature's effects on autistic youth wellbeing in partnership with The Center for Discovery in New York, and investigating multi-sensory design in urban public spaces.

• Environmental Psychology
• Human-Environment Interactions
• Nature and Health
• +۷ مورد دیگر

Adriana Schulz is an Assistant Professor in the Department of Computer Science & Engineering at the University of Washington's College of Engineering. She leads a research group focused on computational design, computer-aided design (CAD), and digital fabrication. Her work bridges computer science with practical applications in manufacturing, robotics, and sustainable design. Dr. Schulz received her Ph.D. in Computer Science from MIT in 2018 under the supervision of Professor Wojciech Matusik. Prior to her doctoral studies, she earned a Master's degree in Mathematics from IMPA (Instituto Nacional de Matemática Pura e Aplicada) in Rio de Janeiro, where she worked with Professor Luiz Velho, and a Bachelor's degree in Electronics Engineering from UFRJ (Federal University of Rio de Janeiro). Her research interests center around computational tools that enhance design and manufacturing processes. She develops novel algorithms for CAD systems, computational fabrication techniques, and sustainable design approaches. Her work spans multiple domains including robotics, textiles, electronics, and architecture, with a strong emphasis on creating practical tools that designers and engineers can use in real-world applications. She explores how machine learning, particularly neurosymbolic approaches, can improve design workflows and enable new capabilities in computational design systems. Analysis of her recent publications reveals a strong trend toward more intelligent and user-centered design tools. Her research increasingly integrates machine learning with traditional CAD systems to create more intuitive interfaces, supports sustainable design practices with computational tools, and develops novel fabrication techniques that push the boundaries of what's possible with digital manufacturing. She has made significant contributions to zero-waste fashion design, immersion cooling for high-performance computing, and CAD program understanding through novel representation learning techniques. Innovators Under 35 - MIT Technology Review Bolsa Aluno Nota 10 from FAPERJ Engineer 20000 award Dr. Schulz actively mentors several PhD students and postdoctoral researchers, including Haisen Zhao, Ben Jones, Yuxuan Mei, and others, often in collaboration with colleagues across different departments. Her research has attracted significant media attention, with coverage in major outlets including MIT News, BBC, IEEE Spectrum, Wired, and TechCrunch. Her work on Interactive Robogami was noted as the most read article in the International Journal of Robotics Research in its publication year. She leads a vibrant research group at the University of Washington that focuses on computational design systems, with particular emphasis on creating tools that bridge the gap between digital design and physical fabrication. Her team develops novel algorithms for CAD systems, computational fabrication techniques, and sustainable design approaches that have practical applications across multiple industries.

• Computational Design
• Computer-Aided Design (CAD)
• Digital Fabrication
• +۴ مورد دیگر

Dr. Nienke Smit is an Assistant Professor in the Department of Education at Utrecht University's Faculty of Social and Behavioural Sciences. Her research focuses on scaffolding processes, adaptive teaching, and classroom observational research from a complex dynamic systems perspective. Specializes in teacher-student interaction Expert in adaptive instruction and observational methods Collaborates with Data Science department Develops tools for classroom observation Research interests include language learning and teaching , judgment and decision-making in education , and professional development of teachers . She leads projects like Eye Get It (joint attention in classrooms) and a replication study on adaptive instruction effectiveness. Her work applies dynamic systems theory to second language development and foreign language pedagogy. Recent publications address translanguaging in multilingual classrooms, replication studies , and process-oriented research . She teaches at Utrecht's Graduate School of Teaching and works on initiatives to reduce teacher shortages through improved training programs.

• Language Learning and Teaching
• Observational Research
• Educational Research
• +۷ مورد دیگر

Marie Sandberg is an Associate Professor in the Promotion Programme at the Saxo Institute, University of Copenhagen. She is affiliated with the Faculty of Humanities and participates in HUM:Global initiatives focused on interdisciplinary global studies. Her research emphasizes ethnological analyses of migration, borders, and refugee policies, particularly exploring temporal governance, state-civil society interactions, and the paradoxes of welfare-state frameworks. Her work examines the everyday practices of refugees and volunteers in contexts of temporary protection status, as well as the ethical challenges in digital migration studies. She contributes to debates on deterrence policies, repatriation agendas, and the precarity of academic labor. Sandberg’s research methodologies often combine ethnography with critical analysis of policy frameworks. Key Research Themes: Refugee temporariness, border studies, humanitarianism, and academic precarity Professional Roles: Member of the Professional Project Group (PPG) in HUM:Global, coordinating interdisciplinary projects Geographic Focus: Europe, with emphasis on Denmark, Poland, and Germany Recent publications highlight her focus on the interplay between state policies and grassroots efforts, as well as the temporal dimensions of displacement. She has co-edited special issues on migration and authored studies on volunteerism in refugee relief work.

• Ethnology
• Migration Studies
• Refugee Studies
• +۳ مورد دیگر

Olga Saukh is an Associate Professor at the Institute of Technical Informatics, Graz University of Technology (TU Graz), and a Faculty member at the Complexity Science Hub Vienna (CSH). She leads the Embedded Learning and Sensing Systems research group, which operates across both institutions, focusing on the design and deployment of efficient AI-based systems on edge and mobile platforms. Her work bridges deep learning and embedded systems, with applications in environmental monitoring, precision agriculture, and digital health. Ph.D. in Computer Science, University of Bonn (2009) Habilitation in Embedded Systems, TU Graz (2020) Postdoctoral Training, ETH Zurich (2010–2016) B.Sc. in Applied Mathematics, Taras Shevchenko National University of Kyiv (2002) M.Sc. in Applied Computer Science, University of Freiburg (2004) Her research centers on efficient machine learning, particularly model optimization, neural network pruning, and contrastive learning for resource-constrained devices. She is deeply engaged in solving real-world challenges in IoT, sensor networks, and cyber-physical systems. Her work emphasizes data privacy, sustainability, and practical deployment of AI at the edge. The 15 most recent publications highlight a strong trend in efficient deep learning, including model compression, pruning, and transfer learning, applied to diverse domains such as environmental sensing (air quality, pollution tracking), digital agriculture (cattle farming), and embedded AI (sensor calibration, on-demand sensing). Her work frequently appears in top-tier venues like NeurIPS, ICLR, and IEEE/ACM IPSN, reflecting her leadership at the intersection of machine learning and embedded systems. Scientific awards include: CONET Ph.D. Academic Award (2010) Multiple Best Paper Awards at IEEE PerCom, ACM/IEEE IPSN, IEEE ICPADS, IEEE SECON, and UrbCom Spotlight and Oral presentations at ICML and CoLLAs workshops Ph.D. scholarship from IPVS, University of Stuttgart (2004–2005) Prizes in Ukrainian national mathematics competitions (1996–1998) Olga Saukh actively serves on program committees of leading international conferences in machine learning and embedded systems. She has advised multiple students and leads a collaborative research group spanning TU Graz and CSH Vienna. Her group develops practical AI systems for real-world deployment, with a focus on sustainability and privacy. She co-organizes the public EfficientML reading group and has secured recognition through numerous grants and awards. Her future work continues to explore the theoretical and practical challenges of deploying efficient, trustworthy AI in mobile and embedded environments. Her research group, Embedded Learning and Sensing Systems, operates jointly between TU Graz and CSH Vienna, fostering interdisciplinary collaboration across institutions. The team develops AI solutions for edge computing, sensor networks, and cyber-physical systems, with a strong emphasis on environmental sustainability and data privacy. Members work on joint challenges using advanced collaboration tools, reflecting the distributed nature of modern academic research.

• Efficient Machine Learning
• Deep Learning
• Embedded Systems
• +۱۲ مورد دیگر

Susan Bradley is a Research Fellow at the Centre for Maternal and Child Health Research at City St George's, University of London . Her work focuses on equitable access to maternity care in low-income contexts, particularly sub-Saharan Africa, using interdisciplinary approaches integrating postcolonial theory and organizational studies. Education: PhD in Health Services Research (2018), City, University of London MSc in Global Health (2007), Trinity College Dublin PGCE in Secondary Science (University of Reading) BSc (Hons) in Biology (University of Sussex) Professional Experience: Research Fellow at City St George's (2018–present) Researcher at Trinity College Dublin (2007–2014) Researcher/writer at Columbia University Mailman School of Public Health (2010) Her research examines power dynamics, organizational culture, and community-based care models in maternal health. She has extensive fieldwork experience in Malawi, Tanzania, and Mozambique, specializing in qualitative data analysis and capacity-building initiatives. Recent publications focus on group antenatal care, respectful maternity practices, and health workforce dynamics in low-resource settings. Key findings from her work include: Community-making in group care enhances health literacy and belonging Socio-spatial dynamics influencing maternal care access Structural barriers affecting midwives' ability to provide quality care

• Equitable access to maternity care
• Interdisciplinary research
• Power dynamics in healthcare
• +۵ مورد دیگر

Professor Beatrice Heuser is a distinguished academic in the Department of Politics within the School of Social & Political Sciences at the University of Glasgow. Her career spans multiple prestigious institutions across Europe, including King's College London, University of Reading, and visiting professorships at Sciences Po Paris, Bundeswehr University Munich, and MGIMO. She maintains significant affiliations with major strategic research institutes including Chatham House, RUSI, IFRI, and IRSEM. Education: BA from Bedford College London, MA from LSE, DPhil from Oxford (St Antony's/St John's), Habilitation from University of Marburg Professional Experience: Former Director of Studies at German Bundeswehr's military history research office, NATO Headquarters consultant, and extensive teaching across European institutions Her research centers on strategic studies with particular focus on the cultural dimensions of warfare, nuclear strategy, and the historical evolution of strategic thought. Key research areas include strategic culture, military exercises as political instruments, laws of war development, and European defense policy. Her work bridges historical analysis with contemporary security challenges, examining how cultural narratives shape strategic decision-making from antiquity to the nuclear age. Professor Heuser's recent publications demonstrate consistent scholarly output across strategic theory, military history, and contemporary security issues. Her work shows particular emphasis on the conceptual foundations of strategic culture, historical analysis of warfare evolution, and practical applications to modern security challenges including nuclear deterrence and asymmetric warfare. The interdisciplinary nature of her research connects political theory, historical analysis, and security studies. She actively supervises graduate students in strategic theory, nuclear strategy, insurgency studies, and defense policy-making within NATO/EU contexts. Her teaching portfolio includes War and International Relations, Defense Policy, and Strategic Theory courses.

• Strategic Studies
• War Theory
• Nuclear Strategy
• +۷ مورد دیگر

Roberto Manduchi is a Professor of Computer Science and Engineering at the University of California, Santa Cruz, within the Baskin School of Engineering. His primary affiliation is with the Computer Science and Engineering department where he leads research in assistive technology for visual impairments. He holds a Dottorato di ricerca in Electrical Engineering from the University of Padova, Italy, and previously worked at Apple and NASA JPL before joining UCSC in 2001. His research focuses on mobile computer vision, inertial sensors, and location-aware systems to enhance spatial awareness and information access for blind and low-vision individuals. Key research areas include indoor navigation systems, screen magnification for low-vision readers, obstacle detection using augmented reality, and text accessibility assessment through specialized OCR pipelines. His work bridges computer vision, human-computer interaction, and accessibility design. Analysis of his recent publications (2022-2025) reveals strong emphasis on inertial-based indoor navigation (e.g., PALMS localization system, backtracking algorithms), screen magnification usability studies, and novel approaches to scene text access for blind users. His research consistently targets practical applications for visual impairment, with significant contributions to pedestrian dead reckoning, magnetic signature localization, and gaze-contingent interfaces. Manduchi serves on the scientific advisory board of Aira and is a board member of the Vista Center for the Blind and Visually Impaired. He leads the UCSC Computer Vision Lab where his team develops accessible computing solutions. His work includes both theoretical contributions to computer vision and tangible assistive applications, with recent projects focusing on smartphone-based inertial odometry, multi-scale tactile maps, and real-time obstacle cueing systems.

• Computer Vision
• Assistive Technology
• Human-Computer Interaction
• +۲ مورد دیگر

Douglas D. Ready is an Associate Professor of Education and Public Policy at Teachers College, Columbia University , where he serves as Director of the Consortium for Policy Research in Education (CPRE-TC). His research focuses on the intersections of education policy, social policy, and educational equity, particularly how policies influence socio-demographic disparities in cognitive development. Research Interests: Ready’s work examines the structural determinants of educational equity, including school choice architecture, personalized learning, early childhood education, and the impacts of technology on instruction. He has published extensively in journals such as Educational Evaluation and Policy Analysis and Sociology of Education . Editorial Roles: Ready contributes to the academic community as a member of the editorial boards of Educational Evaluation and Policy Analysis and American Educational Research Journal . Key Projects: He has led analyses of programs like Teach to One: Math and Pre-K for All , exploring their effects on student outcomes and equity.

• Education Policy
• Social Policy
• Educational Equity
• +۳ مورد دیگر

Erik Willcutt is a Professor in the Department of Psychology and Neuroscience at the University of Colorado Boulder. His research focuses on the genetic and neurobehavioral underpinnings of ADHD, learning disabilities, and developmental psychopathologies. He holds positions at the Institute for Behavioral Genetics and the Center for Neuroscience. Education: PhD in Psychology from the University of Denver (1998). Research Interests: Etiology and assessment of ADHD, reading disabilities, and developmental psychopathologies. His work integrates behavioral genetics, neuroimaging, and longitudinal twin studies to understand cognitive and psychiatric disorders. Key topics include neuroanatomical correlates of ADHD, genetic influences on dyslexia, and comorbidity between learning disabilities and psychiatric conditions. Publications highlight advanced methods like genome-wide association studies (GWAS) and phenotype harmonization (e.g., Rosetta method). His work bridges molecular genetics with clinical psychology, emphasizing translational research. Lab/Affiliations: Active in the Institute for Behavioral Genetics and collaborates with interdisciplinary teams studying neurodevelopmental disorders. Office located at Muenzinger D451B.

• Behavioral Genetics
• Psychiatric Genetics
• ADHD Etiology
• +۳ مورد دیگر