Lillie Padilla is an Assistant Professor of Spanish Linguistics at Sam Houston State University's Department of World Languages and Cultures. Holding a Ph.D. and M.A. in Spanish Linguistics from Arizona State University alongside a Bachelor of Arts from the University of Ghana, her research explores interdisciplinary connections between: Afro-Latinx representation in educational materials Discourse analysis and language ideologies Sociolinguistic studies in Equatorial Guinea Critical race theory applications in language teaching Her work focuses on Spanish subject pronoun expression patterns in multilingual contexts and curriculum development for inclusive pedagogy. Recent publications examine: Representation gaps in Spanish language textbooks Methodological challenges in Equatorial Guinea research Critical discourse analysis of Netflix's Elite series Intersectional representation of Afro-Latinx women Scientific achievements include: Finalist for American Association of Linguistics 2025 award for co-edited volume Representation, Inclusion and Social Justice in World Language Teaching Padilla's research continues to shape conversations about linguistic diversity and marginalized voices in language education through both empirical studies and theoretical frameworks.
David Bamman is an Associate Professor in the School of Information at UC Berkeley, specializing in applying Natural Language Processing (NLP) and machine learning to cultural and social science questions. He leads research in born-literary NLP, computational humanities, and cultural analytics, with affiliated roles in EECS, Linguistics, and Computational Precision Health. Bamman holds degrees from Carnegie Mellon (Ph.D., 2015), Boston University (M.A., 2006), and University of Wisconsin-Madison (B.A., 1998). His work is supported by NEH, NSF, and industry grants. Educations: Ph.D. in Computer Science (2015), Carnegie Mellon University M.A. in Applied Linguistics (2006), Boston University B.A. in Classics (1998), University of Wisconsin-Madison Research Interests: NLP for underserved domains (e.g., literature, social media), coreference resolution, cultural analytics, and computational methods for studying literature and culture. Projects include LitBank and BookNLP datasets. Grants & Awards: Hellman Fellow (2019), Amazon Research Award (2017), NSF CAREER Award, and NEH funding. Teaching: Courses include Natural Language Processing (Info 159/259), Computational Humanities (INFO 190), and Applied NLP (INFO 256). His research group explores topics like racial representation in high school literature, Hollywood diversity metrics, and the sociocultural implications of LLMs. Bamman advises multiple PhD students and collaborates on datasets like CMU Book Summaries and 11K Latin Books.
John Redmond is Professor of English Literature at the University of Liverpool's School of the Arts, specializing in contemporary poetry and creative writing. He holds a D.Phil and is an established poet with three collections published by Carcanet Press. His critical work examines privacy in poetic interpretation and Irish literary traditions. Research intersects creative practice with critical analysis, exploring poetry's relationship with folk drama, online culture, and food (gastro-criticism). Authored the textbook 'How to Write a Poem' and edited James Liddy's Selected Poems. Current projects include a novel and new poetry collection. Regularly participates in literary events including readings at the Anthony Burgess Foundation and Christ Church, Oxford. Chairs the School Extenuating Circumstances Committee and contributes to the Centre for New and International Writing.
Sean Cao serves as Associate Professor (with tenure) at the Robert H. Smith School of Business, University of Maryland, where he is Director and Co-founder of the AI Initiative for Capital Market Research. He also holds an affiliation as professor at Harvard Business School's D 3 Institute. His academic journey began with a Ph.D. from the University of Illinois at Urbana-Champaign. Dr. Cao's research focuses on the intersection of artificial intelligence and capital markets, with particular expertise in how machine learning transforms financial analysis, corporate disclosure practices, and investment decision-making. His work examines the evolving relationship between human analysts and AI systems, blockchain applications in financial reporting, and the strategic adaptation of corporate communications for machine readership. He has pioneered research on the "AI divide" among investor groups and developed frameworks for human-AI collaborative stock analysis. His publication portfolio spans top journals including Journal of Financial Economics, Review of Financial Studies, Journal of Accounting Research, and Management Science. The research demonstrates consistent thematic progression toward increasingly sophisticated AI applications in finance, with recent work exploring distributed ledger technologies for auditing, machine learning for extracting private information from disclosures, and the economics of greenwashing in ESG funds. His studies frequently combine textual analysis with traditional financial metrics to uncover novel market insights. Fama-DFA Prize from Journal of Financial Economics for best paper in capital markets and asset pricing Michael J. Brennan Award from Review of Financial Studies Deloitte Initiative for AI and Learning award for developing trustworthy AI for social equity PanAgora Asset Management's Dr. Richard A. Crowell Memorial Prize Multiple best paper awards from Midwest Finance Association, Global AI Finance Conference, and Asian Finance Association Dr. Cao has delivered over 200 invited research talks at major institutions including the Central Bank of Japan, Central Bank of Thailand, and U.S. Securities and Exchange Commission. He serves as Guest Associate Editor for Management Science and has co-chaired Review of Financial Studies conferences on FinTech and Machine Learning. His educational initiatives include a widely adopted free AI textbook for finance and accounting that has been implemented at universities worldwide including Indiana University, UT Dallas, and University of Minnesota. As Director of the AI Initiative for Capital Market Research, Dr. Cao leads a multidisciplinary team exploring practical AI applications in finance. The initiative has secured significant funding including a $150,000 grant from GRF CPAs & Advisors. His research group maintains strong industry connections through partnerships with regulatory bodies, financial institutions, and technology companies, facilitating the translation of academic research into practical financial applications.
Clifford Stein is a Professor of Industrial Engineering and Operations Research (IEOR) and Computer Science at Columbia University, and Associate Director for Research at the Data Science Institute. He holds a Ph.D. (1992), M.S. (1989), and B.S.E. (1987) from MIT and Princeton University, respectively. His research focuses on algorithms, combinatorial optimization, operations research, scheduling, and computational biology. A co-author of the best-selling textbook Introduction to Algorithms , Stein has published widely in top venues and holds prestigious awards like ACM Fellow and NSF Career Award. His work includes foundational contributions to minimum cut algorithms, scheduling theory, and network optimization, supported by NSF and Sloan Foundation grants. Stein has advised over 40 graduate and undergraduate students, many now in academia and industry.
Eytan Adar is a Professor of Information and Computer Science at the University of Michigan, holding dual appointments in the School of Information and the College of Engineering's Electrical Engineering and Computer Science department. His work sits at the intersection of human-computer interaction and artificial intelligence, focusing on large-scale systems analysis and novel interface design. Adar's research spans multiple domains including social media analysis (Twitter, Reddit), academic citation networks, meme propagation, information extraction, and political networks. His methodological expertise includes data mining, data visualization, and graph-based network analysis. His work often operates at internet scale, examining language, creativity, social network dynamics, and text production. His recent publications reveal a strong focus on AI-human collaboration, with particular attention to generative AI interfaces, visualization techniques for complex data, and ethical considerations in AI systems. His work shows a consistent pattern of bridging theoretical insights with practical system implementations. Best Paper Award at ProtoAI: Model-Informed Prototyping for AI-Powered Interfaces, IUI'21 Honorable Mention Award at CHI'24 for feminist interaction techniques research Best Paper Award at ICWSM'18 for Wikipedia language edition analysis Best Paper Award at ICML 2016 Workshop for neural language model visualization Best Student Paper at WSDM'09 for web dynamics research Best of CHI at CHI 2008 for web revisitation patterns analysis Adar has advised numerous PhD students who have gone on to prominent positions at organizations including Google, Apple, RAND, Northwestern University, and Stanford. His research is generously supported by the NSF, IARPA, NIH, the Education Department, and major technology companies including Adobe, Microsoft, Facebook, Google, and Yahoo. He is also a founder of the International Conference on Web and Social Media (ICWSM) and has served as Co-General Chair for WSDM and Co-Program Chair for UIST.
Kevin D. Ashley is a Professor of Law at the University of Pittsburgh School of Law. He is also a senior scientist at the Learning Research and Development Center and an adjunct professor of computer science at the University of Pittsburgh. His interdisciplinary work bridges artificial intelligence, legal analytics, and ethical reasoning. JD, Harvard Law School M.A. and PhD, University of Massachusetts BA, Princeton University His research focuses on computational modeling of legal reasoning , AI and ethics , legal text analytics , and case-based reasoning . He has pioneered AI applications for legal decision support, automated argumentation, and bias detection in legal corpora. Recent publications include studies on large language models in legal annotation, argument mining, and empirical legal analysis. His work has been supported by multiple National Science Foundation grants, emphasizing fairness in AI and access to justice. 2022 Codex Prize for Computational Law 2015 University of Massachusetts Outstanding Achievement Award 2002 AAAI Fellow for AI in Law contributions 2000 Chancellor’s Distinguished Research Award A former President of the International Association for Artificial Intelligence and Law, Ashley has held visiting roles at the University of Bologna, Stanford CodeX, and IBM Watson Research Center. He co-edits the journal Artificial Intelligence and Law and teaches courses on applied legal analytics.
Achuta Kadambi, Ph.D., is an Associate Professor at UCLA in Electrical Engineering and Computer Science, leading an interdisciplinary research group focused on AI, computational imaging, and bias mitigation in medical technologies. He recruits PhD students from EE, CS, and Bioengineering departments and has commercialized research through two California-based companies. His research investigates the intersection of physics and artificial intelligence, with a focus on unbiased low-level vision systems. Current projects explore how light transport interacts with human skin variations to identify and correct imaging biases in facial recognition and medical devices. His work has produced over 70 patents, with 30+ issued, and a textbook Computational Imaging (MIT Press, 2022). NSF CAREER Award (2021) for light transport bias research DARPA Young Faculty Award (2021) for AI and medical imaging innovations ARO Young Investigator Program (2021) for computational sensing IEEE-HKN Under 35 Award (2022) for inclusive EECS inventions Forbes 30 Under 30 recognition His recent publications focus on polarization imaging, 3D Gaussian splatting, synthetic data generation for healthcare, and bias mitigation in machine learning. Collaborations with UCLA medical school faculty, including Dr. Laleh Jalilian, aim to deploy these innovations in clinical settings. Current teaching includes ECE 149: Foundations of Computer Vision (Fall 2024, Spring 2025) and ECE 102: Signals and Systems (Winter 2024).
Karsten Lambers is Professor of Digital and Computational Archaeology at the Faculty of Archaeology, Leiden University, where he leads research and teaching in the application of computational methods to archaeological data. His work integrates machine learning, remote sensing, text mining, and citizen science to advance archaeological prospection and heritage management. He is affiliated with the Department of Archaeological Sciences and plays key roles in research groups and university-wide initiatives such as SAILS and ARCHON. His research interests span Digital Archaeology , Machine Learning in Archaeology , Remote Sensing , Geoarchaeology , and Human-Environment Interaction . He investigates how computational tools can extract meaningful archaeological information from large datasets, including LiDAR imagery and excavation reports. His fieldwork spans Central Europe and Latin America, with a focus on prehistoric landscapes and cultural heritage. The analysis of his recent publications reveals a strong trend toward automated detection using deep learning (e.g., R-CNN, WODAN), named entity recognition in archaeological texts (e.g., ArcheoBERTje), and citizen science integration for data validation. His work bridges archaeology with computer science, geomatics, and environmental science, emphasizing interdisciplinary collaboration and methodological rigor. His scientific awards include: Best Thesis Award (University of Zurich, 2005) EUROPA NOSTRA Award (2020, 2022) Membership in the German Archaeological Institute (since 2022) Lambers actively supervises students and leads major research projects such as ABMA, EXALT, and Heritage Quest. He has secured substantial research funding and collaborates widely with computer scientists, geophysicists, and palaeoecologists. His teaching includes digital methods, modeling, and simulation, often linked to ongoing research. He has also contributed to open educational resources and digital textbooks in archaeology. He leads or participates in several research labs and teams, including the Digital Archaeology Research Group (which he chairs), the Heritage Quest citizen science project, and interdisciplinary teams focusing on alpine terraces and Iraqi prospection. His work emphasizes the integration of digital tools into practical archaeological workflows, advocating for complementary human-computer strategies.
İbrahim Dağılma is a Lecturer in Zaza Language and Literature at Bingöl University's Faculty of Arts and Sciences since 2013. He holds a Master's (2017) and PhD (2021) in Zaza Language and Literature from Bingöl University's Living Languages Institute. He previously served as a Turkish Language teacher in the Ministry of National Education and authored/co-authored Zazaki textbooks for grades 5-8 published by MEB between 2018-2019. He currently chairs the Zaza Language and Literature department and teaches courses like Modern Zaza Literature and Comparative Literary Analysis. Education: Bachelor's in Turkish Education, Dicle University (1997) Uncompleted Journalism studies at Istanbul University (2010) Master's and PhD in Zaza Studies (2017-2021) Research focuses on Zaza language preservation, modern literary movements, folklore documentation, and comparative studies between Zaza and other languages. He has published 11 books including 'Edebiyato Modern ê Zazaki' and 'Süleyman Hilmi Tunahan', and frequently presents at international conferences on topics like Zaza cultural identity and migration narratives. His recent academic work explores linguistic comparisons between Zaza and Farsi, analysis of traditional Zaza texts, and the role of folklore in educational materials. He has advised 18 undergraduate theses and participated in numerous thesis juries. His research has been published in refereed journals like Bingöl Araştırmalar Dergisi and The Journal of Mesopotamian Studies.
Yin Tat Lee is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington, and a Senior Principal Researcher in Microsoft AI. His research spans convex optimization , convex geometry , graph algorithms , online algorithms , and differential privacy , with applications in machine learning and theoretical computer science.
Arvind Narayanan is a Professor of Computer Science at Princeton University and Director of the Center for Information Technology Policy (CITP). His research focuses on the societal impact of digital technologies, particularly artificial intelligence, with emphasis on policy implications, fairness, and privacy. He leads interdisciplinary efforts connecting technical research with real-world policy challenges. Dr. Narayanan earned his Ph.D. from the University of Texas, Austin in 2009. His academic journey has established him as a leading voice in the critical examination of AI systems and their societal consequences. Narayanan's research spans multiple domains where technology intersects with society. His work on AI includes critical analysis of AI capabilities versus marketing claims (AI Snake Oil), fairness in machine learning systems, and the reproducibility crisis in ML-based science. In privacy research, he led the Princeton Web Transparency and Accountability Project which uncovered how companies track users online, developing the OpenWPM tool used in over 100 studies. His early work demonstrated fundamental limits of de-identification techniques and how machine learning reflects cultural stereotypes. His recent publications reveal a consistent focus on demystifying AI capabilities while identifying genuine opportunities and risks. Narayanan's work bridges technical computer science with policy relevance, emphasizing the importance of evidence-based approaches to AI governance. His research increasingly addresses the limitations of prediction systems, the challenges of evaluating AI systems, and the need for transparency in foundation models. Presidential Early Career Award for Scientists and Engineers (PECASE) Privacy Enhancing Technologies Award (twice recipient) Privacy Papers for Policy Makers Award (three-time recipient) TIME's inaugural list of 100 most influential people in AI 2025 Graduate Mentoring Award Narayanan is recognized as an exceptional mentor, receiving Princeton's Graduate Mentoring Award in 2025. His policy engagement extends to congressional testimony, advisory roles, and frequent media commentary. He has secured significant research funding supporting his work on web transparency, AI policy, and cryptocurrency analysis. His research group has produced influential tools like OpenWPM for web privacy studies and contributed to foundational textbooks on cryptocurrencies and fairness in machine learning. At Princeton, Narayanan leads the Web Transparency and Accountability Project, a major research initiative that has conducted large-scale measurements of online tracking across millions of websites. He also co-founded and directs the CITP's AI Policy Initiative, which brings together researchers from multiple disciplines to address pressing AI governance questions. His work frequently involves collaboration with social scientists, legal scholars, and policymakers to develop practical solutions to technology governance challenges.
Alexey Vladimirovich Vdovin is a Professor and Senior Research Fellow at the National Research University Higher School of Economics (HSE), working within the Faculty of Humanities and School of Philological Sciences. He began his tenure at HSE in 2012 and has accumulated 15 years of scientific and teaching experience. His academic journey includes a Doctor of Philology degree from HSE (2023), a PhD from the University of Tartu (2011), and his initial degree in 'Russian language and literature' from Vyatka State Humanitarian University (2007). He has held significant roles including Deputy Dean for Science at the Faculty of Humanities (2018-2020) and serves on numerous academic councils and committees. Vdovin's educational background demonstrates both depth and international perspective. After completing his undergraduate studies at Vyatka State Humanitarian University in 2007, he pursued doctoral studies at the University of Tartu, where he earned his PhD in 2011 with a dissertation on 'The concept of 'chapter of literature' in Russian criticism of the 1830-1860s.' His academic development has been enriched by numerous international experiences, including visiting researcher positions at Selwyn College, University of Cambridge (2019), Jordan Center at New York University (2017), and multiple research stays at Humboldt University in Berlin through the Aurora Erasmus Mundus program. Professor Vdovin's research focuses on Russian intellectual history, the history of ideas, the Russian Empire, Russian literature of the 19th century, and nationalism studies. His work particularly examines the formation of the Russian literary canon, representations of peasants in literature, and the relationship between literature and society. He has authored approximately 80 articles and 4 monographs on 19th-century Russian literature, culture, and criticism, with works on major figures like Turgenev, Dostoevsky, Tolstoy, Goncharov, Belinsky, Chernyshevsky, Dobrolyubov, and Nekrasov. His recent book 'Monsters at the Threshold: Dracula, Frankenstein, Viy and Other Literary Monsters' (2024) demonstrates his expanding interest in literary archetypes and cultural phenomena. Vdovin has received numerous awards and recognitions for his scholarly work, including the Moscow Government Prize for young scientists (2017), multiple 'Best Teacher' awards (2013-2015, 2017-2024), and recognition as a winner of HSE's competition for best Russian-language scientific works (2022, 2024). He has also received various letters of gratitude from HSE administration, the Faculty of Humanities, and the School of Philology for his contributions to academic life. As an advisor, Vdovin has supervised numerous student research projects, including Smirnova T.V.'s 2014 master's thesis on 'Representation of 'Russianness' and 'Otherness' in Russian essays of the 1840s.' He has also served as a curator for HSE's Personnel Reserve Program at the School of Philological Sciences and has been actively involved in dissertation councils. His research has been supported by significant grants, including a 2024-2025 Russian Science Foundation grant 'The Genre of 'Peasant Life Story' in Russian Literature Before 1861: Poetics, Plots, Socio-Cultural Functions' (No 24-28-00184) and a 2018-2020 RFBR grant on 'State and Literary Institutions: From Peter I's Reforms to the 'Great Reforms.' Professor Vdovin is actively engaged in academic communities beyond HSE, serving as editor-in-chief of the HSE preprint series 'Literary Studies' and participating in the Big Project 'Literature and Society: An Experience of Sociocultural Description.' He is also involved in public scholarship, frequently giving public lectures through platforms like 'Arzamas,' 'Postnauka,' and 'Stradarium,' and appearing on the 'Observer' television program (Culture channel). Since 2015, he has been a mentor at Maya Kucherskaya's Creative Writing School, bridging academic scholarship with creative practice.
Barry Naughton is the So Kwan Lok Chair of Chinese International Affairs at the School of Global Policy and Strategy (GPS), University of California, San Diego, where he has been a faculty member since 1988 and was appointed to his named professorship in 1998. As a globally recognized authority on China's economic transformation, his work bridges academic rigor and policy relevance through decades of analysis of market reforms, industrial development, and international economic relations. His academic foundation includes: Ph.D. in Economics from Yale University (1986) M.A. in International Relations from Yale University (1979) B.A. in Chinese Language and Literature from the University of Washington (1975) Naughton's research centers on China's transition from planned to market economy, with emphasis on industrial restructuring, foreign trade dynamics, and regional development disparities. His scholarship uniquely connects historical analysis of reform milestones with contemporary policy challenges, particularly examining how state-market interactions shape technological advancement and global economic integration. This dual focus on institutional evolution and sectoral transformation has established him as a critical interpreter of China's development model for both academic and policy audiences. Analysis of his 2020-2024 publications reveals a decisive shift toward examining China's industrial policy architecture and state capitalism mechanisms. Key thematic clusters include the conceptualization of 'Grand Steerage' in state-economy relations, the restructuring of science-technology systems, and the sectoral implementation of industrial policies. These works collectively document China's evolving governance approach—from market liberalization to targeted state direction—while analyzing implications for global trade and innovation ecosystems. His scholarly recognition includes: Ohira Memorial Prize for 'Growing Out of the Plan: Chinese Economic Reform, 1978-1993' (1996) Administrative leadership has been integral to Naughton's career, serving as Associate Dean of GPS (1992-1995, 2001-2003) and Chair of UCSD's Chinese Studies Program (1998-2000). His policy engagement extends through the Research Grants Council of Hong Kong (1998-2003) and U.S. academic committees on Chinese studies. Current research examines regional growth patterns and foreign investment linkages while completing a new edition of his seminal textbook 'The Chinese Economy: Transitions and Growth,' which remains the field's authoritative reference. Though not leading a formal laboratory, Naughton shapes discourse through China Leadership Monitor's quarterly economic assessments and collaborative networks like the edited volume 'State Capitalism, Institutional Adaptation and the Chinese Miracle' (2015), which mobilized leading scholars to analyze China's institutional innovation within global capitalism.
Dr. James D. Foley is a Professor in the College of Computing and the School of Electrical and Computer Engineering at Georgia Institute of Technology. He holds the Stephen Fleming Chair in Telecommunications. He earned his Ph.D. in Computer Information and Control Engineering from the University of Michigan and a BSEE from Lehigh University, where he was inducted into Phi Beta Kappa, Tau Beta Pi, and Eta Kappa Nu. Founded the Graphics, Visualization & Usability (GVU) Center at Georgia Tech, ranked #1 in graphics and user interaction. Directed Mitsubishi Electric Research Lab and later served as CEO of Mitsubishi Electric ITA. Executive Director of Yamacraw, Georgia's broadband development initiative. His research focuses on computer graphics, human-computer interaction (HCI), visualization, and user interface design. He co-authored foundational textbooks like Interactive Computer Graphics , translated into multiple languages. Professional leadership includes Chair of the Computing Research Association (CRA), Fellowships with ACM and IEEE, and the ACM/SIGGRAPH Stephen Coons Award. He advised over 30 graduate students and led numerous conferences, panels, and editorial roles in top journals. Contributions span academia and industry, including roles in NSF workshops, JTEC studies on HCI in Japan, and advisory boards for institutions like MIT and Lehigh University.
