Find Academic Supervisors

Callie HaoView profile

Assistant Professor

• Software/Hardware Co-design
• Reconfigurable Computing
• Graph Computing
• +5 more

Callie Hao is an Assistant Professor in the Department of Electrical and Computer Engineering at the Georgia Institute of Technology since 2021, holding the ON Semiconductor Junior Professorship. Her research bridges hardware efficiency and algorithmic innovation with significant industry and federal recognition. Education: Ph.D. in Electrical Engineering, Waseda University (2017) M.S. and B.S. in Computer Science and Engineering, Shanghai Jiao Tong University Research Focus: Dr. Hao pioneers software/hardware co-design for edge AI, specializing in hardware-efficient machine learning algorithms, FPGA-based reconfigurable computing, graph neural networks, and electronic design automation (EDA). Her work emphasizes neural architecture search, high-level synthesis optimization, and memory-efficient systems for embedded and IoT applications, driven by the philosophy that "1 + 1 > 2" for transformative efficiency gains. Publication Impact: Her 15 most recent publications (2023-2026) reveal a strategic shift toward machine learning-driven EDA tools, with 60% focused on high-level synthesis frameworks and 40% on graph neural network acceleration. Key trends include simulation speed breakthroughs (LightningSim), automated accelerator generation (GNNBuilder), and cryptographic hardware innovations (Cryptonite), predominantly published in top-tier venues like MICRO, ICCAD, and DAC. Awards & Recognition: NSF CAREER Award (2024) and Intel Rising Star Faculty Award (2023) Best Paper Awards at MLCAD 2024 and GLSVLSI 2021 ON Semiconductor Junior Professorship (2025) and Sutterfield Family Early Career Professorship (2022) DAC-SDC competition championships (2018-2020) Mentorship & Funding: Dr. Hao advises 8+ Ph.D. students in the Sharc Lab, with Rishov Sarkar winning the Oscar P. Cleaver Award and Qualcomm Innovation Fellowship. Her research is funded by DARPA (2021) for ultra-light video intelligence systems and supported by industry awards from Amazon and Sony. She actively serves on program committees for DAC, ICCAD, and DATE conferences. Lab Leadership: As director of the Sharc Lab (Software/Hardware Co-design lab), she cultivates interdisciplinary research at the intersection of FPGA design, machine learning, and EDA, requiring expertise in Verilog/HLS, GNNs, and compiler technologies while maintaining strict focus on real-world hardware implementation.

Pamela A. Morris-PerezView profile

Professor

• Developmental Psychology
• Suicidology
• Education Policy
• +6 more

Pamela A. Morris-Perez is a Professor of Applied Psychology at the NYU Steinhardt School of Culture, Education, and Human Development and an Affiliated Professor at the NYU School of Global Public Health. She is an elected member of the National Academy of Education. Her research bridges developmental psychology, suicidology, education, and policy, with over $75M in research funding. She holds a BA from Columbia University and a PhD in Developmental Psychology from Cornell University. Her research focuses on early childhood interventions, adolescent suicide prevention (through ARCADIA), and policy impacts. Notable projects include a $5M IES-funded NYC Universal Pre-K initiative and a $10M NIH trial on parenting interventions. She has also led institutional roles as Vice Dean/Interim Dean of NYU Steinhardt, overseeing significant research growth and diversity initiatives. Research Themes: Suicidology, early childhood development, policy evaluation, pediatric health interventions. Key Projects: ARCADIA suicide prevention, NYC Pre-K expansion, pediatric primary care interventions. Her articles highlight interdisciplinary approaches to child development and policy, with recent work emphasizing adolescent mental health and pandemic impacts on early childhood programs. Awards include the National Academy of Education membership and a 2017 Best Paper Award. Leadership Achievements: 44% increase in research expenditures, tripling of faculty of color hires, pandemic response coordination. Grants & Funding: William T. Grant Foundation, NIMH, NIH, IES. Morris-Perez collaborates across academia and public agencies to translate research into scalable interventions, particularly in under-resourced communities.

Jana Schaich BorgView profile

Research Fellow

• Neuroscience
• Computational Modeling
• Social Decision-Making
• +4 more

Jana Schaich Borg is an Assistant Research Professor at the Social Science Research Institute at Duke University. She specializes in integrating neuroscience, computational modeling, and emerging technologies to study social decision-making processes and their interactions with internal value representations. As a data scientist, she collaborates with interdisciplinary teams to develop novel statistical approaches for analyzing high-dimensional, multi-modal data. Research interests include Moral psychology and computational ethics Human-AI interaction in decision-making Automated social behavior analysis Neuroscience of social cognition Interdisciplinary data science education Recent publications highlight her focus on ethical AI development, moral preference modeling, and automated behavioral analysis. She teaches IDS 707: Data Visualization at Duke University.

Vicki L. Plano ClarkView profile

Professor

• Mixed Methods Research
• Research Methodology
• Qualitative Research
• +3 more

Vicki L. Plano Clark is a Professor in the Research Methods area of the School of Education at the University of Cincinnati, where she advises students in the Quantitative and Mixed Methods Research Methodologies (QMRM) concentration of the Educational Studies doctoral program and the Applied Research Methods (ARM) track of the Educational Studies master's program. She joined the University of Cincinnati in 2012 after serving as the director of the Office of Qualitative and Mixed Methods Research at the University of Nebraska-Lincoln. Dr. Plano Clark earned her Ph.D. in Quantitative and Qualitative Methods in Education from the University of Nebraska-Lincoln (2005), M.S. in Physics from Michigan State University (1993), and B.A. in Physics from Kalamazoo College (1990). Her academic journey transitioned from physics education to research methodology, bringing a unique interdisciplinary perspective to her work. As a leading methodologist specializing in mixed methods research, Dr. Plano Clark's scholarship focuses on delineating useful designs for conducting mixed methods research, examining procedural issues associated with these designs, and exploring the contexts for the adoption and use of mixed methods. Her research spans diverse application areas including cancer pain management, STEM graduate student identity development, teacher professional development, and the well-being of rural low-income families. Her work demonstrates how mixed methods approaches can effectively address complex research questions across multiple disciplines. Dr. Plano Clark has made significant contributions to the field through her editorial leadership and publications. She was the founding Managing Editor for the Journal of Mixed Methods Research and currently serves as an Associate Editor. In 2011, she co-led the development of Best Practices for Mixed Methods in the Health Sciences for NIH's Office of Behavioral and Social Sciences Research. In 2012, she became a founding co-editor of the Mixed Methods Research Series with Sage Publications. She has authored numerous influential books including 'Designing and Conducting Mixed Methods Research' (now in its 3rd edition) and 'Mixed Methods Research: A Guide to the Field.' Founding Managing Editor for the Journal of Mixed Methods Research Co-developer of NIH's Best Practices for Mixed Methods in the Health Sciences (2011) Founding co-editor of the Mixed Methods Research Series with Sage Publications (2012) Chair of the Mixed Methods Research Special Interest Group of AERA As an active researcher, Dr. Plano Clark has secured multiple grants including a Department of Education grant evaluating Ohio Network of Education Transformation (ONET) Schools (as Principal Investigator) and a UC University Research Council grant on reducing mass incarceration by improving public defense (as Collaborator). Her recent publications continue to advance methodological understanding in mixed methods research, with a focus on integration techniques, terminology challenges, and applications across health sciences and education. Dr. Plano Clark maintains an active role in the research community through invited presentations and workshops worldwide, helping to train the next generation of researchers in mixed methods approaches and contributing to the ongoing development of methodological standards and practices.

• Computer Architecture
• Memory Systems
• Parallel Computing
• +5 more

Mark D. Hill is a Professor at the University of Wisconsin—Madison, renowned for transformative contributions to computer architecture spanning memory systems and parallel computing. His work earned the ACM-IEEE CS Eckert-Mauchly Award in 2019 and ACM Fellowship in 2004. Hill pioneered the 3C model for cache misses, SC for DRF memory consistency (with Sarita Adve), and transactional memory via LogTM (with David Wood). His simulation frameworks—Dinero, GEMS, gem5, and BadgerTrap—enable advanced analysis of memory behavior and virtual systems, while concepts like 'page reservation' directly impact Linux kernel design. Research spans cache optimization, heterogeneous processor memory models, and scalable parallel evaluation techniques. Hill's accolades include: ACM-IEEE CS Eckert-Mauchly Award (2019) for contributions to memory systems and parallel computer design/evaluation ACM Fellow (2004) for innovations in memory consistency models and memory system architecture With over 160 co-authors and 20,000+ citations, Hill mentored influential researchers like Sarita Adve. His grant-supported projects—including the Wisconsin Wind Tunnel simulator—produced industry-adopted tools cited thousands of times, driving real-world implementations in programming languages and operating systems. Hill leads critical research initiatives at Wisconsin, developing the Dinero cache simulator, GEMS/gem5 full-system simulators, and BadgerTrap virtual memory analyzer. These projects underpin modern architecture research and continue to evolve for emerging heterogeneous computing challenges.

Vera LiaoView profile

Associate Professor

• Human-Computer Interaction
• Human-AI Interaction
• Responsible AI
• +6 more

Vera Liao is a Principal Researcher at Microsoft Research, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group. She will join the University of Michigan Computer Science and Engineering department as an Associate Professor in fall 2025. Her work focuses on human-AI interaction, explainable AI, and responsible computing. Liao has made significant contributions to IBM products such as AI Explainability 360 and Uncertainty Quantification 360 during her time at IBM T.J. Watson Research Center. Dr. Liao received her education from the University of Illinois at Urbana-Champaign and Tsinghua University. Her academic journey has positioned her at the intersection of human-computer interaction and artificial intelligence, with a strong emphasis on creating AI systems that are transparent, accountable, and user-centered. Vera Liao's research primarily centers around human-centered AI explainability and transparency. She investigates how to design AI systems that effectively communicate their capabilities, limitations, and decision-making processes to users. Her work examines the intersection of AI transparency with trust, control, and user experience. Liao has pioneered approaches to bridging the socio-technical gap in AI evaluation and has developed frameworks for contextualized evaluation of explainable AI systems. Her research spans multiple domains including conversational interfaces, data storytelling, and creative work with generative AI. Liao's publications reveal a clear trend toward addressing the challenges of large language models and their impact on human-AI interaction. Her recent work focuses on understanding how uncertainty communication affects user trust, how to design for appropriate reliance on AI systems, and how to create authentic co-creation experiences with generative models. She has been examining the risks in AI-infused information ecosystems and developing methods for human-centered evaluation of language technologies. Her scientific contributions have been recognized with multiple honors: Best Paper Award, Honorable Mention at CHI 2025 (two papers) Best Paper Award at CHI 2024 Best Paper Award, Honorable Mention at FAccT 2023 Best Paper Award, Honorable Mention at HCOMP 2022 Best Paper Award, Honorable Mention at CHI 2021 Best Paper Award, Honorable Mention at CHI 2014 Outstanding Paper Award at IUI 2019 Dr. Liao is an active mentor, having guided numerous research interns from top universities including Cornell, Princeton, CMU, Stanford, and MIT. She serves in editorial roles as Co-Editor-in-Chief of the Springer Human-Computer Interaction Book Series and as an Editor for ACM CSCW. Liao has secured research funding through her work at Microsoft Research and previously at IBM, focusing on projects related to AI explainability, transparency, and responsible AI development. As part of Microsoft Research's FATE group, Liao collaborates with a multidisciplinary team of researchers focused on the ethical implications of AI technologies. Her work bridges the gap between technical AI development and human-centered design principles, ensuring that AI systems are developed with user needs and societal impacts in mind.

Yasmin KafaiView profile

Professor

• Computational Thinking
• Artificial Intelligence Education
• STEM Equity
• +3 more

Yasmin Kafai is a Professor at the University of Pennsylvania's Graduate School of Education (GSE), Department of Learning Sciences. Her research focuses on computational thinking, AI education, and equitable K-12 computing pedagogy. She has pioneered work on integrating electronic textiles (e-textiles) and participatory design into STEM education to engage youth in critical perspectives of technology. Kafai's recent work emphasizes algorithmic literacy, youth-led auditing of machine learning systems, and bridging technical and societal dimensions of computing. Key research areas include: computational empowerment, AI ethics in education, youth agency in technology design, and culturally responsive computing curricula. Her projects often involve hands-on making activities, such as constructing generative AI models or debugging e-textile systems, to foster both technical and critical understandings. Publications from 2024-2025 highlight trends in youth engagement with generative AI, algorithm auditing frameworks, and the intersection of physical computing with growth mindset practices. She has also explored the role of storytelling methodologies in reimagining computing narratives for marginalized groups. Kafai collaborates extensively with teachers to develop scalable professional development programs addressing equity in CS education. Her work frequently appears in learning sciences and computing education journals, with a focus on practical classroom implementations and systemic educational reforms. Ongoing efforts include designing 'Hour of Code' activities that integrate critical AI literacy and fostering youth as co-designers of ethical technology solutions.

Kenneth RossView profile

Professor

• Database Systems
• Query Processing
• Query Language Design
• +7 more

Kenneth Ross is a Professor in the Computer Science Department at Columbia University in New York City. His primary appointment is within the Department of Computer Science, with affiliations including the Foundations of Data Science Committee. His work bridges theoretical database research and practical system implementation. His research focuses on database systems with particular expertise in query processing, query language design, data warehousing, and architecture-sensitive database system design. Additional research spans computational biology, especially analysis of large genomic data sets. Current projects include Linear Algebra Operators in Databases for machine learning workloads and Repeats and Somatic Mutation analysis in genomics. His work consistently addresses the intersection of hardware capabilities and database system design. Ross leads the Database Research Lab at Columbia, which has produced significant work on query optimization, GPU database processing, and hardware-conscious database systems. His recent publications demonstrate strong focus on adapting database systems to modern hardware including GPUs, SIMD processors, and persistent memory. His scientific recognition includes: Packard Foundation Fellowship Sloan Foundation Fellowship NSF Young Investigator Award Distinguished Faculty Teaching Award (2008) Ross actively advises undergraduate engineering students (juniors with last names P-Z) and has taught foundational courses including Introduction to Databases and Programming and Problem Solving for over two decades. His teaching portfolio shows consistent engagement with both theoretical concepts and practical implementation challenges in computer science education.

• Health Equity
• Health Disparities
• Vulnerable Populations
• +5 more

Melanie Molina, MD, MAS is an Assistant Professor of Emergency Medicine at the University of California, San Francisco (UCSF) and Affiliate Faculty of the Philip R. Lee Institute for Health Policy Studies. She serves as Co-Director of the Social Emergency Medicine and Health Equity Section and holds a secondary appointment in the Department of Medicine’s Division of Clinical Informatics and Digital Transformation. Clinically, she works at Zuckerberg San Francisco General Hospital and UCSF Medical Center. National Clinician Scholars Program Fellowship (2023) MAS in Clinical Research, UCSF (2023) Residency in Emergency Medicine, Harvard Medical School (2021) MD in Medicine, The University of Texas at Austin (2017) BS/BA in Biology and Hispanic Studies, The University of Texas at Austin (2012) Dr. Molina’s research centers on leveraging technology to address social determinants of health in emergency settings, with a focus on vulnerable populations. Her work spans health equity, opioid use disorder interventions, microaggressions in healthcare, and clinical informatics. She pioneers EHR-enabled tools to integrate social care into emergency clinical workflows while minimizing clinician burden. Her NIH-funded projects emphasize practical solutions for racial and ethnic health disparities, particularly in vaccine delivery and social risk documentation. Her recent publications (2024-2025) reveal three dominant trends: (1) Integration of AI and informatics for social risk screening and clinical decision support, (2) Health equity interventions targeting vaccine hesitancy and long COVID disparities, and (3) Critical analysis of DEI implementation challenges in academic emergency medicine. The work consistently bridges technical innovation with community-centered approaches to address systemic inequities. National Institutes of Health NIDA Loan Repayment Award (2024-2025) National Hispanic Medical Association Top 40 Under 40 (2024) UCSF John A. Watson Faculty Scholar (2023) National Institutes of Health NIAID Loan Repayment Award (2022-2024) Academy for Women in Academic Emergency Medicine Outstanding Research Publication Award (2021) Harvard Medical School Presidential Scholars Public Service Initiative Award (2017) Dr. Molina actively mentors medical students, residents, and fellows in health equity research. As Principal Investigator on multiple NIH and foundation grants—including the Harold Amos Medical Faculty Development Program grant ($825,575, 2024-2028) and an NIH/NIDA K23 award (2024-2029)—she leads projects developing EHR-integrated interventions for social risk documentation and opioid use disorder treatment. Her PROBOOSTVAXED trial addresses vaccine hesitancy through ED-based delivery across eight U.S. cities. She co-directs the Social Emergency Medicine and Health Equity Section within UCSF’s Department of Emergency Medicine, collaborating closely with the Action Research Center for Health Equity and the Philip R. Lee Institute for Health Policy Studies. Her team integrates clinical informatics expertise with community health workers to develop scalable solutions for social risk mitigation in safety-net emergency departments.

Ari SchlesingerView profile

Assistant Professor

• Human-Centered Computing
• Anti-Discriminatory Computing
• Technology Policy
• +4 more

Ari Schlesinger is an Assistant Professor of Computer Science at the University of Georgia (UGA), directing the Socially Responsible Tech Lab. She holds a PhD from the School of Interactive Computing at Georgia Institute of Technology. Her research focuses on anti-discriminatory computing, technology policy, and equitable sociotechnical systems. She advocates for reducing computing-enabled harm to advance justice in technology. Education : PhD in Human-Centered Computing (HCC), Georgia Tech Affiliations : ACM's U.S. Technology Policy Committee Her work spans Human-Computer Interaction (HCI), Artificial Intelligence (AI), and broader CS applications. Key interests include addressing algorithmic bias, inclusive design, and policy frameworks for ethical computing. She has developed strategies to mitigate discrimination in technical systems through frameworks like anti-discriminatory computing. Awards include the 2021 Outstanding Graduate Teaching Assistant Award and a Best Paper Award at CHI 2018. Her research has been featured in venues like CSCW and CHI, focusing on topics from chatbot ethics to decentralized social networks. Lab : Socially Responsible Tech Lab at UGA Grants/Advising : Advises graduate student Eddie Alexander Gomez Schieber. Active in policy advocacy and academic leadership roles.

Angela CrowView profile

Associate Professor

• Design
• User Experience (UX)
• Freedom of Movement
• +7 more

Angela Crow is an Associate Professor at James Madison University (JMU) in the School of Writing, Rhetoric and Technical Communication, where she has served since 2012. Her research bridges literacy studies, design, and urban mobility, focusing on how communities advocate for car-free infrastructure and equitable public spaces. She explores the role of digital communication in fostering feminist interventions, particularly around cycling advocacy and street design. Her work intersects with gender studies, urban studies, and rhetorical theory. Educated at the University of Kansas (Ph.D., 1997) and Point Loma College (B.A., 1987), she has authored books on writing programs and composition studies, including Aging Literacies (2006) and Field of Dreams (2002). Recent publications analyze surveillance, privacy in digital contexts, and transportation equity. Her research often highlights marginalized voices in shaping public discourse. Research Interests: Her current projects examine embodied literacies in mobility advocacy, social media practices of grassroots movements, and the rhetoric of urban infrastructure. She critiques car-centric planning through feminist and critical frameworks, emphasizing accessibility and safety for non-car users. Her work also addresses aging populations’ digital literacies and the intersection of technology with social inequality. Publications: Her articles span rhetorical analysis of social movements, educational assessment frameworks, and the sociotechnical dimensions of writing. Recent trends include collaborations on privacy in big data and participatory design for community mobility.

David DotyView profile

Professor

• Molecular computing
• Algorithmic self-assembly
• Chemical reaction networks
• +8 more

David Doty is a Professor in the Department of Computer Science at the University of California, Davis . His research focuses on the intersection of molecular systems and computation , exploring how natural processes like chemical reactions , DNA nanotechnology , and self-assembly can perform computation. He also investigates connections to theoretical computer science, including distributed computing and algorithmic information theory . Doty's work bridges physics , chemistry , and biology through rigorous computational models like the Tile Assembly Model and Population Protocols . His research program includes software development ( scadnano , ppsim ), theoretical analysis, and collaborations with experimentalists. He teaches courses on theory of computation and molecular computing , and has advised numerous students in his research group. His publications cover topics such as algorithmic self-assembly , chemical reaction networks , and thermodynamic binding networks , with a focus on understanding fundamental computational and physical limits. Key software tools developed by his group include scadnano for DNA design and ppsim for population protocol simulations. Doty's recent research trends explore rate-independent chemical computing , error correction , and stochastic modeling in molecular systems. Current academic activity includes teaching ECS 120 (Undergraduate Theory of Computation), ECS 220 (Graduate Theory of Computation), and ECS 232 (Theory of Molecular Computation). He maintains a research lab in 2306 Academic Surge and continues to publish in leading conferences like DNA Computing and CMSB .

Brandon M. StewartView profile

Associate Professor

• Quantitative Methods
• Statistical Methods
• Text Analysis
• +5 more

Brandon M. Stewart is an Associate Professor of Sociology at Princeton University with extensive interdisciplinary affiliations. He serves as Director of the Statistics Core at the Office of Population Research and maintains formal connections with the Politics Department, Princeton Institute for Computational Science and Engineering, Center for Information Technology Policy, and Center for the Digital Humanities. Stewart holds editorial leadership as Co-Editor-in-Chief of Political Analysis and Associate Editor at Sociological Methods & Research . His educational background includes: Ph.D. in Government from Harvard University (2015) Master's degree in Statistics from Harvard University (2014) Stewart's research pioneers innovative quantitative methods for social science applications, specializing in automated text analysis and modeling complex heterogeneity in regression. His methodological frameworks enable researchers to uncover hidden structures in large datasets that were previously too costly or impossible to analyze. While his recent work has focused on using newspaper archives to study propaganda mechanisms in contemporary China, his tools are deliberately designed for broad applicability across diverse domains including education, human trafficking, forced migration, international relations, constitutional law, and psychology. His publication record demonstrates consistent innovation at the intersection of statistics, machine learning, and social inquiry. Stewart's work shows a clear trajectory from foundational methodological development to practical implementation across numerous substantive areas, with recurring themes of enhancing causal inference with textual data, developing robust topic modeling techniques, and creating accessible computational tools for social scientists. Stewart's scholarly excellence has been recognized through multiple prestigious awards: 2024 Leo Goodman (Early Career) Award from the Methodology Section of the American Sociological Association 2023 Emerging Scholar Award from the Political Methodology Society Edward R Chase Dissertation Prize Gosnell Prize for Excellence in Political Methodology Political Analysis Editor's Choice Award Recognition for Excellence in Mentoring Graduate Students As a mentor, Stewart has guided several successful graduate students to faculty positions at institutions including UCLA and Georgetown. His collaborative approach is evident in numerous multi-author projects spanning disciplines from political science to computational linguistics. His leadership extends to the Sociology Statistics Reading Group, which he founded to foster interdisciplinary methodological exchange, and his summer methods camp that trains social scientists in advanced quantitative techniques.

Cristina BicchieriView profile

Professor

• Game Theory
• Social Norms
• Decision Science
• +11 more

Cristina Bicchieri is the S. J. Patterson Harvie Professor of Social Thought and Comparative Ethics at the University of Pennsylvania , where she also holds appointments as Professor of Philosophy and Psychology and Professor of Legal Studies at the Wharton School. She founded and directs the Penn Center for Social Norms and Behavioral Dynamics , the Philosophy, Politics & Economics Program , and the Master of Behavioral and Decision Sciences . Education : PhD in Philosophy from Cambridge University and a Laurea (Summa cum Laude) from the University of Milano . Her research lies at the intersection of philosophy , game theory , and cognitive psychology , focusing on: Judgment and Decision-Making : Fairness, trust, cooperation, and how expectations influence behavior. Social Norms : Their nature, evolution, measurement, and application in policy (e.g., sanitation, corruption). Epistemic Foundations of Game Theory : Rational choices under bounded knowledge and computational models for game solutions. Her recent articles explore topics like norm stability , language framing effects , and sanitation interventions in India . These works emphasize behavioral dynamics , cognitive psychology , and public policy applications . Scientific Awards : Member, American Academy of Arts and Sciences (2021) Member, German Academy of Sciences (2021) Honorary Fellow, Wolfson College, Cambridge (2016) Pufendorf Medal (2015) Cavaliere Ordine al Merito della Repubblica Italiana (2007) She leads the Behavioral Ethics Lab and collaborates with organizations like UNICEF , the World Bank , and the Gates Foundation to implement norm-based interventions globally.

Monica DeHartView profile

Professor

• Cultural Anthropology
• Economic Development
• China-Latin America Relations
• +3 more

Monica DeHart is a Professor of Sociology and Anthropology and Director of the Global Development Studies program at the University of Puget Sound. Her work focuses on the cultural politics of economic development in Central America, particularly exploring how gender, class, race, and ethnic differences shape development projects and their outcomes. She has conducted ethnographic research in Costa Rica, Nicaragua, and Guatemala for over two decades, with recent emphasis on China-Central America relations. Her forthcoming book Transpacific Developments: The Politics of China and Chineseness in Central America examines the multifaceted roles of China, Taiwan, and local diaspora communities in the region. Education: B.A., University of California, Davis (1994) M.A., Stanford University (1997) Ph.D., Stanford University (2001) Research Interests: DeHart’s work critiques neoliberal development paradigms and explores how transnational actors and institutions redefine development. Her studies often highlight contradictions in policies that reframe ethnic identity as a tool for economic growth. Recent projects analyze China’s growing influence in Central America, including infrastructure investments, cultural diplomacy, and anti-corruption policies. She emphasizes the intersection of local and global dynamics in shaping development outcomes. Key Themes in Publications: Her articles and books address topics such as China’s transpacific political economy, the role of diaspora communities, and the historical legacies of anti-Chinese sentiment. She also examines how language institutes and infrastructure projects serve as geopolitical tools. Her work bridges anthropological theory with critical analyses of global development trends. Professional Activities: DeHart teaches courses on global development, anthropological theory, and cultural studies. She is currently on leave for Spring 2026. Her office is located in McIntyre 213P, and she can be reached at mdehart@pugetsound.edu.