Crystal S. Rudds is an Assistant Professor in the Department of English at the University of Utah, specializing in African American literature and culture. Her research focuses on twentieth-century American and African American fiction, qualitative narratives about urban life and housing, Black Feminisms, and black geography/ecology. PhD in English from the University of Illinois at Urbana-Champaign (2016) MFA in Creative Writing from Indiana University-Bloomington (2004) BA in Communications with minors in French and Theatre from Wake Forest University (1999) Her scholarly work examines the intersection of literature and urban environments, particularly through public housing fiction. She uses interdisciplinary approaches combining qualitative research with literary analysis, emphasizing community engagement and the phenomenological experiences of residents in urban spaces. Her publications address topics like the historical context of public housing narratives and the concept of 'the black interior' as a framework for understanding spatial identity. Rudds has received prestigious honors, including the David D. Anderson Award for Midwestern Literary Studies and the Mary Blinn Poetry Prize. She is also a Faculty Research Fellow and Intersectionality Pedagogy Fellow at the University of Utah. Her teaching philosophy integrates experiential learning and community-focused methods, with courses such as African Amer Lit 2, Seminar in Lit. Study, and Studies Af Amer Lit. She emphasizes archival research, site visits, and performance-based learning to empower students as co-creators of knowledge.
Ryan Heuser is an Assistant Professor in Digital Humanities at the University of Cambridge, specializing in computational approaches to literary and intellectual history, prosody, and artificial intelligence's impact on language. His work bridges data science, machine learning, and literary studies through digital methodologies. Doctoral training in Eighteenth-Century British Literature, Stanford University (2019) Founding member & Associate Research Director, Stanford Literary Lab Junior Research Fellow, King’s College Cambridge (2019-2022) Research interests span computational modeling of semantic revolutions, large-scale literary field analysis, and the intersection of digital methods with historical and intellectual studies. His book Explorations in the Digital History of Ideas (2023) co-edited with Peter de Bolla exemplifies this approach. Recent publications focus on historical semantics, metrical analysis, and digital mapping of emotions in literature, reflecting his interdisciplinary expertise in natural language processing, network theory, and literary data visualization. Currently leads teaching initiatives at Cambridge Digital Humanities and contributes to computational projects exploring textual rhythms and large language models.
Sigrid Schmalzer is a Professor of History at the University of Massachusetts Amherst, specializing in the history of science and modern China. She holds a Ph.D. in History and Science Studies from the University of California, San Diego (2004). Her research bridges the social, cultural, and political dimensions of science in China, with a focus on the intersections of agriculture, activism, and revolutionary movements. Schmalzer is the author of *Red Revolution, Green Revolution: Scientific Farming in Socialist China* (2016), winner of the Joseph Levenson Book Prize, and *The People's Peking Man: Popular Science and Human Identity in Twentieth-Century China* (2008), recipient of the Allan Sharlin Award. Her current projects include a book on agricultural heritage in the People’s Republic of China and leadership roles in organizations like the Critical China Scholars and Science for the People. She co-edits the *Activist Studies of Science and Technology* series for UMass Press, emphasizing socially engaged scholarship. Schmalzer also serves as Co-President of the MSP faculty union at UMass Amherst. Research interests span the history of science activism, transnational movements, and the legacy of Maoist science. Notable awards include the Freeman Book Award (2018) for her children’s book *Moth and Wasp, Soil and Ocean*, which integrates science education with historical narratives. Her work often critiques capitalist and authoritarian structures while advocating for science as a tool for justice and sustainability. Recent publications explore themes like agroecology, science policy, and the global dimensions of China’s scientific history. She teaches courses on modern China, science in society, and radical science movements, blending interdisciplinary approaches to engage students in critical analysis of historical and contemporary issues.
Sharese King is the Neubauer Family Assistant Professor of Linguistics at the University of Chicago, where she has taught since 2018. She earned her Ph.D. and Master's in Linguistics from Stanford University, focusing on language variation across African American communities. Her research bridges sociolinguistics, critical race theory, and phonetics to examine how African American speech is constructed, racialized, and socially evaluated. Education: Ph.D., Linguistics, Stanford University (2018) M.A., Linguistics, Stanford University Research Interests: Sociolinguistics Language Variation & Change African American Language Critical Race Theory Phonetic and experimental analysis Dialect and judicial systems Notable Contributions: Interdisciplinary studies on raciolinguistics and courtroom bias Analysis of /s/ articulation in intersectional contexts Reconceptualization of AAVE as AAL to emphasize linguistic diversity Fieldwork in Bakersfield, Rochester, and Chicago Publications in American Speech , Journal of Sociolinguistics , Language , and Nature Scientific Awards: Provost's Postdoctoral Fellowship Neubauer Family Assistant Professorship Labs & Projects: Co-founder of the Chicagoland Language Project
Florian Mussgnug is Professor of Comparative Literature and Italian Studies at University College London (UCL), Faculty of Arts and Humanities. He has held visiting roles at Heidelberg University, Roma Tre University, La Sapienza University Rome, University of Siena, and British School at Rome. Educational Background: PhD in Literary Studies (2009) at Scuola Normale Superiore di Pisa DPhil in Italian Literature (2000) at University of Oxford MSt Research Methods in Modern Languages (1999) at University of Oxford BA in Philosophy and Modern Languages (1995) at University of Oxford Research Interests: His scholarship spans theories of authorship, genre and mode; religious/secular apocalyptic storytelling; posthumanism; anthropocene studies; comparative literature; intermediality; narratives of catastrophe and resilience; and modern/contemporary Italian, English, and German literature and culture. Grants and Research Leadership: As co-investigator for the AHRC-funded 'Interdisciplinary Italy 1900-2020' project (£831,131 total), he explores intermediality and interdisciplinarity. Additional grants include £35,000 (UCL Global Engagement Office, 2017) and £12,300 (ANCI, 2019). Scientific Awards & Service: He serves on prize juries (Premio Strega, Peter Lang Young Scholars) and national research assessment panels (Italy, Portugal). Awards include Edinburgh Gadda Prize (2012), Premio Nicoletta Quinto (2002), and Oxford Gibbs Prize (1998). Editorial and Institutional Roles: He sits on editorial boards (Arabeschi, Between, Modern Languages Open) and held leadership roles at UCL, including Vice-Dean International (2021) and Acting Head of School of European Languages, Culture and Society (2022).
Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Massachusetts Institute of Technology (MIT), where she is affiliated with the Department of Economics within the School of Humanities, Arts, and Social Sciences. She co-founded and co-directs the Abdul Latif Jameel Poverty Action Lab (J-PAL) and holds the position of Chaire, Pauvreté et politiques publiques at the Collège de France. Duflo also serves as President of the Paris School of Economics, demonstrating her significant international influence in economic policy and research. Her educational background includes first degrees in history and economics from Ecole Normale Superieure, Paris, followed by a Ph.D. in Economics from MIT in 1999. This strong foundation has enabled her to become one of the most influential economists of her generation. Duflo's research focuses on understanding the economic lives of people living in poverty, with the explicit aim of informing effective social policy design and evaluation. Her work spans critical areas including health, education, financial inclusion, environmental sustainability, and governance. What distinguishes her approach is the rigorous application of randomized controlled trials to evaluate development interventions, bringing scientific precision to poverty alleviation efforts. Her research methodology has revolutionized how economists approach development questions, moving beyond theoretical models to evidence-based policy recommendations. Her scholarly output demonstrates remarkable breadth and impact, with publications spanning from technical academic papers to influential books for general audiences. Duflo's work consistently bridges the gap between academic research and practical policy applications, with recent publications addressing contemporary challenges including climate change adaptation, pandemic response, and economic policy for hard times. Her research trends reveal a deepening commitment to translating complex economic concepts for broader audiences while maintaining scholarly rigor. Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2019, with Abhijit Banerjee and Michael Kremer) Princess of Asturias Award for Social Sciences (2015) A.SK Social Science Award (2015) Infosys Prize (2014) John Bates Clark Medal (2010) MacArthur 'Genius Grant' Fellowship (2009) Member of the National Academy of Sciences (2017) Duflo has supervised numerous graduate students and collaborated extensively with researchers worldwide through J-PAL, which has grown into a global network conducting field experiments across multiple continents. Her grant portfolio includes substantial funding from major foundations and government agencies supporting large-scale development research. Beyond traditional academic advising, Duflo has mentored a generation of development economists through J-PAL's training programs and field research opportunities. Her primary institutional home is the Abdul Latif Jameel Poverty Action Lab (J-PAL), which she co-founded at MIT. J-PAL has grown into a major research center with offices worldwide, connecting academic researchers with policymakers to ensure that program evaluations inform real-world decisions. Duflo also leads research teams at the Collège de France and the Paris School of Economics, creating a transatlantic network focused on evidence-based poverty reduction strategies.
Jonathan Rosa is Associate Professor in the Graduate School of Education, Center for Comparative Studies in Race and Ethnicity, and, by courtesy, Departments of Anthropology, Linguistics, and Comparative Literature at Stanford University. He serves as Director of Stanford's Program in Chicanx-Latinx Studies and has held leadership positions including President of the Association of Latina/o and Latinx Anthropologists of the American Anthropological Association. Dr. Rosa's educational background includes: Ph.D. in Sociocultural and Linguistic Anthropology from the University of Chicago (2010) M.A. in Sociocultural and Linguistic Anthropology from the University of Chicago (2006) B.A. in Linguistics and Educational Studies from Swarthmore College (2003) Dr. Rosa's research examines the co-naturalization of language and race as a key feature of modern governance, tracking colonially structured interrelations among racial marginalization, linguistic stigmatization, and institutional inequity. His scholarship centers on raciolinguistic ideologies, Latinx studies, and educational justice, with a community-based approach that develops tools for challenging systemic vulnerability. He investigates how race and language are jointly defined across historical, geopolitical, and institutional contexts, with particular focus on Latinx communities and educational settings. His recent publications demonstrate a consistent thematic focus on decolonizing linguistic and educational frameworks, challenging standard language ideologies, and examining the intersections of race, language, and power. The work spans multiple disciplines including sociolinguistics, anthropology, education, and critical race studies, increasingly emphasizing undoing raciolinguistics and addressing coloniality in language education and assessment practices. Dr. Rosa has received numerous prestigious awards for his scholarship: Distinguished Summer Scholar, Banks Center for Educational Justice, University of Washington College of Education (2024) Outstanding Book of the Year Award for "Looking like a Language, Sounding like a Race," American Association of Teaching and Curriculum (2022) First Book Award for "Looking like a Language, Sounding like a Race," American Association for Applied Linguistics (2021) Prose Award for Excellence in Language & Linguistics for "Looking like a Language, Sounding like a Race," Association of American Publishers (2020) Charles A. Ferguson Award for Outstanding Scholarship, Center for Applied Linguistics (2018) Dr. Rosa actively mentors doctoral students across multiple programs, serving as primary advisor for students researching race, ethnicity, language, and education. His research has been supported by major grants from the National Science Foundation, Andrew W. Mellon Foundation, Woodrow Wilson National Fellowship Foundation, and Ford Foundation. He collaborates extensively with community organizations, particularly in Chicago, to develop educational approaches grounded in decolonial praxis, focusing on how scholarship can serve as a platform for social transformation. Dr. Rosa co-directed Stanford's Center for Global Ethnography (2021-2023) and directed Stanford's Program in Chicana/o-Latina/o Studies (2020-2023). He serves on multiple editorial boards including Current Anthropology and Equity & Excellence in Education, and has held leadership positions in professional organizations including President of the Association of Latina/o and Latinx Anthropologists (2020-2022).
Antoine Bosselut is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he leads the EPFL NLP group. His research focuses on developing AI reasoning agents that can model, represent, and reason about human and world knowledge, with applications in health, education, and global fairness. His research interests span multiple critical areas in modern AI: LLM Representations of Knowledge: Understanding what language models know and how they represent that knowledge internally Reasoning Algorithms: Developing methods to improve LLMs' reasoning capabilities through symbolic systems, neuroscience, and cognitive science Large-scale AI Development: Creating open-source foundation models with multilingual capabilities AI Democratization: Ensuring equitable access to AI technologies across different cultural and regulatory contexts His recent publications reveal a strong focus on the intersection of language models and cognitive science, with multiple studies examining how LLMs align with human cognition. He's also deeply engaged in practical applications of NLP technology, particularly in education and multilingual settings, as evidenced by his work on evaluating AI's impact on higher education and developing culturally-aware language models. His scientific achievements have been recognized with several prestigious awards: Outstanding Paper Award at NAACL 2025 ELLIS Scholar designation in 2024 Outstanding Paper Award at ACL 2023 Inclusion in Forbes 30 Under 30 list for Science & Healthcare in 2021 Bosselut actively mentors numerous PhD students across diverse NLP research areas and has secured significant recognition for his work in both academic and media circles. His lab has been featured in major publications including Communications of the ACM, The Atlantic, and Quanta Magazine, highlighting the societal impact of his research on commonsense reasoning and AI capabilities.
Mark Schmidt is a Professor in the Department of Computer Science at the University of British Columbia, Faculty of Science. He holds the Canada Research Chair in Large-Scale Machine Learning and is a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute. His research spans multiple centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action), the Data Science Institute, and the Machine Intelligence Learning Discovery (MILD) group. Dr. Schmidt's educational background includes a Ph.D. from UBC (2005-2010), an M.Sc. from the University of Alberta (2003-2005), and a B.Sc. from the University of Alberta (2000-2003). His academic career progressed from Postdoc positions at Simon Fraser University, Ecole Normale Superieure, and UBC to Assistant Professor (2014-2019), Associate Professor (2019-2024), and current Professor (2024-present) at UBC. His research focuses on machine learning optimization, with particular emphasis on improving numerical algorithms for large-scale machine learning applications. His work bridges theoretical optimization and practical applications across computer vision, natural language processing, and reinforcement learning. He has developed numerous optimization techniques including variants of stochastic gradient methods, coordinate descent algorithms, and natural gradient approaches. Analysis of his recent publications reveals a strong focus on optimization for over-parameterized models, particularly transformers and large language models. His work addresses critical challenges in step-size selection, convergence guarantees, and efficient implementation of optimization algorithms. His research has significant implications for training deep neural networks more effectively and understanding why certain optimization methods outperform others in practice. Among his notable awards are the Dorothy Killam Fellowship (2025), Arthur B. McDonald Fellowship (2024), Sloan Research Fellowship (2017), and multiple UBC teaching awards. He has also received the Lagrange Prize in Continuous Optimization and Best Paper Award at AISTATS 2021. Dr. Schmidt actively supervises numerous graduate students, with over 40 PhD and Master's students listed as current or alumni members of his research group. His laboratory maintains strong connections with industry partners, with many alumni securing positions at leading AI companies including Google, Amazon, Meta, and Microsoft.
Abhijit Banerjee is a Professor in the Department of Economics at the Massachusetts Institute of Technology (MIT). His research focuses on development economics, public health policy, and social protection programs, particularly addressing poverty and inequality in low- and middle-income countries. He has conducted large-scale experiments evaluating interventions such as conditional cash transfers, universal basic income, and healthcare policies. Key areas of interest include the design and implementation of anti-poverty programs, behavioral economics, and the long-term health impacts of infectious diseases like COVID-19. His work often integrates experimental methods to assess policy effectiveness, with contributions to global health studies and economic development strategies. Notably, his research on the RECOVERY trial evaluates treatments for hospitalized COVID-19 patients, while other studies explore financial spillover effects of electronic government transfers in Indonesia and savings behavior interventions in Chile. Banerjee has collaborated on projects analyzing post-COVID-19 health outcomes, labor market dynamics in India, and the role of trusted messengers in public health communication during crises. Despite the breadth of his contributions, specific details about his educational background, grants, or lab affiliations are not explicitly provided in the source text.
Claire Bowern is Professor of Linguistics at Yale University specializing in historical linguistics, language documentation, and Australian Indigenous languages. Her research employs computational phylogenetics to study language evolution and supports language revitalization through digital archives and fieldwork methodologies. Recent publications address: Phylogenetic signal in lexical evolution across language families Digital infrastructure for endangered language documentation (FLEx software analysis) Decolonizing linguistics pedagogy and research practices Her work consistently integrates linguistic, anthropological, and computational approaches to analyze language diversity and change. She contributes to global databases including Grambank and D-PLACE, examining links between linguistic, cultural, and environmental patterns.
H. Samy Alim is a Professor and David O. Sears Presidential Endowed Chair in the Division of Social Sciences at UCLA, holding a joint appointment in the Department of Anthropology. He serves as Associate Director of the Ralph J. Bunche Center for African American Studies and leads the UCLA Hip Hop Initiative. Alim’s research focuses on Hip Hop Culture, Black Language, and Culturally Sustaining Pedagogies, with over 25 years of scholarship in these areas. His work bridges academia and activism, emphasizing Hip Hop’s transformative role in global social justice movements. Alim earned his PhD in Anthropology from Stanford University (2003), following MA (2002) and BA (1999) degrees. His academic contributions include twelve authored/edited books, such as Freedom Moves (2023) and Articulate While Black (2012). His research spans Hip Hop’s linguistic innovations, racialized language politics, and its pedagogical potential in education. Key projects include ethnographic studies in Cape Town, South Africa, and collaborative initiatives like the UC Press Hip Hop Studies Book Series. He co-edits the Oxford Handbook of Language and Race and directs the Center for Race, Ethnicity, and Language. Alim has engaged with global Hip Hop artists (e.g., Chuck D of Public Enemy) to co-produce knowledge, emphasizing Hip Hop as a site of theorizing and activism. His teaching and research highlight intersections of language, race, and power, advocating for pedagogies that sustain cultural identities while fostering equity. Collaborations with organizations like Heal the Hood in South Africa reflect his commitment to community-driven scholarship.
Sewoong Oh is a Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he has been faculty since 2019. His research focuses on the foundations of machine learning with particular emphasis on differential privacy, secure and robust machine learning, and federated learning. Prior to joining UW, he was at the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign from 2012-2019. He is affiliated with multiple NSF AI Institutes including ACTION (Agent-based Cyber Threat Intelligence and Operation), AI-EDGE (Future Edge Networks and Distributed Intelligence), and IFML (Foundations of Machine Learning). Oh received his PhD in Electrical Engineering from Stanford University in 2011 under Andrea Montanari, followed by postdoctoral work at MIT's Laboratory for Information and Decision Systems under Devavrat Shah. His educational background spans top institutions in theoretical computer science and electrical engineering. His research spans the critical intersection of machine learning security, privacy, and robustness. Oh's work addresses fundamental challenges in making AI systems reliable and trustworthy, with particular focus on defending against backdoor attacks, developing privacy-preserving algorithms, and creating efficient tokenization methods for language models. His recent SuperBPE work demonstrates how moving beyond traditional subword tokenization can significantly improve language model efficiency and performance. His research consistently bridges theoretical foundations with practical implementations, as evidenced by numerous open-source repositories containing production-ready code. Oh's publications reveal a consistent trajectory toward addressing security and privacy concerns in increasingly complex machine learning systems, with recent work focusing on language model tokenization, data-centric AI, and federated learning frameworks. His research shows strong interdisciplinary connections between theoretical computer science, statistics, and practical machine learning systems. ACM SIGMETRICS best paper award (2015) NSF CAREER award (2016) ACM SIGMETRICS rising star award (2017) GOOGLE Faculty Research Awards (2017, 2020) 2024 ICML Best Paper Award (for work by advisee Jon Hayase) Professor Oh maintains an active research group with numerous PhD students, postdocs, and undergraduate researchers. His students have secured prestigious positions at leading tech companies including Amazon, Google, and Snap, as well as academic appointments at institutions like University of Wisconsin-Madison and Shanghai Jiao Tong University. He has received substantial research funding through his participation in multiple NSF AI Institutes and industry research awards from Google. His lab maintains several active GitHub repositories implementing cutting-edge research in backdoor defense, robust statistics, and privacy-preserving machine learning.
Xin Guo is Professor and Department Chair of Industrial Engineering and Operations Research (IEOR) at UC Berkeley's College of Engineering, holding the Coleman Fung Chair in Financial Modeling. Her research bridges mathematical finance, stochastic control, and machine learning with applications in risk analytics and quantitative trading. Education: Ph.D. in Mathematics, Rutgers University (1999) Research Interests: Professor Guo's work centers on mathematical finance , stochastic games , and reinforcement learning . She develops theoretical frameworks for α-potential games and mean-field systems while applying signature methods and GANs to financial data. Her research addresses critical problems in portfolio optimization, fraud detection (e.g., Medicare analytics), and market forecasting, emphasizing the intersection of stochastic control with machine learning for real-world decision-making under uncertainty. Publication Trends: Recent work (2023-2025) shows increasing focus on multi-agent reinforcement learning through mean-field game theory, with applications spanning finance (corporate bonds, trading), healthcare (fraud detection), and transportation (rate forecasting). Key innovations include BSDE approaches for stochastic games, signature-based time series analysis, and theoretical guarantees for GAN training dynamics. Scientific Awards: Holds the prestigious Coleman Fung Chair in Financial Modeling, reflecting significant contributions to quantitative finance research. Advising and Grants: As IEOR Department Chair, Professor Guo mentors graduate students in stochastic modeling and financial engineering. Her research is supported by the Coleman Fung Endowment Fund, with collaborations spanning finance, healthcare, and transportation sectors through industry partnerships. Labs and Teams: Leads the Risk Analytics & Data Analysis Research (RADAResearch) Lab ( https://risklab.ieor.berkeley.edu/ ), which develops cutting-edge methodologies for risk assessment, data-driven decision-making, and game-theoretic solutions to complex systems. The lab fosters interdisciplinary work connecting mathematical theory with practical applications in FinTech and beyond.
David Williamson Shaffer is the Sears Bascom Professor of Learning Analytics and Vilas Distinguished Achievement Professor of Learning Sciences at the University of Wisconsin-Madison's Department of Educational Psychology. He is also a Data Philosopher at the Wisconsin Center for Education Research. His work focuses on merging statistical and qualitative methods to model complex human collaboration. Shaffer holds an AB in History and East Asian Studies from Harvard University (1987), and MS/PhD in Media Arts and Sciences from MIT (1996/1998). Before academia, he was a teacher, curriculum developer, and game designer. His research emphasizes Quantitative Ethnography —a methodology combining big data analysis with cultural interpretation. Key contributions include Epistemic Network Analysis (ENA) and over 250 publications, including influential books like How Computer Games Help Children Learn (2006) and Quantitative Ethnography (2017). Awardees of the EU Marie Curie Fellowship (2008) and Spencer Foundation Fellowship (2003), Shaffer's work has been presented globally at conferences like Learning Analytics & Knowledge and Computer Supported Collaborative Learning. His interdisciplinary approach bridges education, data science, and humanities, addressing challenges in authentic STEM experiences, collaborative learning analytics, and culturally responsive pedagogy.
