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Andrew ConnorView profile

Senior Lecturer

• Ptolemaic Egypt
• Roman Egypt
• Papyrology
• +2 more

Andrew Connor is a Senior Lecturer in Archaeology and Ancient History at Monash University. He specializes in Ptolemaic and Roman Egypt, papyrology, and the social and religious history of ancient Egyptian communities. His research focuses on Egyptian temples during the Roman period, ancient economic practices, and the editing and publication of documentary papyri. Connor has particular expertise in the Fayum depression and Dakhleh Oasis regions. Connor's publications demonstrate a consistent focus on Egyptian religious institutions, economic systems, and textual evidence from archaeological sites. His recent work includes publications on temple administration, Greek papyri, and digital archaeology. He has received multiple teaching awards including the Faculty Citation for Outstanding Contribution to Student Learning (2017), Faculty Citation for Overseas Programs (2018), and Vice Chancellor's Citation for Outstanding Contribution to Student Learning (2018). Connor teaches courses on Greek and Roman history, archaeology, and ancient languages at both undergraduate and postgraduate levels. He serves as Honours Coordinator for the School of Philosophical, Historical, and International Studies.

Aishwarya AgrawalView profile

Assistant Professor

• Multimodal learning
• Deep learning
• Natural language processing
• +3 more

Aishwarya Agrawal is an Assistant Professor at Université de Montréal in the Department of Computer Science and Operations Research (DIRO), affiliated with Mila – Quebec Institute of Artificial Intelligence and a Canada CIFAR AI Chair. She also serves as a research scientist at Google DeepMind, spending one day weekly there. Education: B.E. in Electrical Engineering (IIT Gandhinagar, 2014), Ph.D. in Computer Science (Georgia Tech, 2019). Her research focuses on multimodal learning , deep learning , natural language processing , and computer vision , particularly in developing AI systems that 'see' and 'communicate' effectively. Grants & Awards: Canada CIFAR AI Chair, 2020 Sigma Xi Best PhD Thesis Award, NVIDIA Fellowship (2018–2019), and multiple fellowships from Google and Facebook. She leads projects like Advancing Multimodal Vision-Language Learning (CRSNG-funded) and StarDoc: Document Structure Extraction (MITACS). Research Contributions: Pioneered benchmarks like CulturalVQA and UI-Vision , and frameworks such as PROGRESS for efficient VLM training. Her work emphasizes cross-modal alignment, robust evaluation, and cultural understanding in AI systems. Labs/Teams: Active in Mila’s core academic group and collaborates with Google DeepMind on multimodal and vision-language research. Supervises a dynamic team of PhD and master’s students in Montreal.

Florentina BuneaView profile

Professor

• Statistical machine learning theory
• High-dimensional statistical inference
• Optimal transport
• +6 more

Florentina Bunea is a Professor in the Department of Statistics and Data Science at Cornell University’s Bowers College of Computing and Information Science, and an active member of the Graduate Fields of Statistics, Applied Mathematics, and Computer Science. She also serves on the Diversity and Inclusion Council of her college, championing workforce diversity in data-science disciplines. Education & Institutional Roles Professor, Department of Statistics and Data Science, Cornell University Member, Graduate Fields of Statistics, Applied Mathematics, Computer Science Member, Diversity and Inclusion Council, Bowers College of Computing and Information Science Research Interests Professor Bunea’s research lies at the intersection of statistical machine-learning theory and high-dimensional inference. She develops rigorous methodology supported by sharp theoretical guarantees to tackle core problems in modern data science. Recent themes include: Soft-max mixtures for understanding large-language-model/AI algorithms Optimal transport for high-dimensional mixture distributions Wasserstein-distance inference for sparse mixing measures in topic models Latent-space clustering and cluster-based inference in high dimensions Network modeling and hidden-structure inference Applications spanning genetics, systems immunology, neuroscience, sociology, and economics Research Funding & Awards Her work is supported by grants from the National Science Foundation (NSF-DMS). She is a Fellow of the Institute of Mathematical Statistics and a recipient of the IMS Medallion Award. Editorial & Service Contributions Associate Editor: Annals of Statistics, Bernoulli, JASA, JRSS-B, EJS, Annals of Applied Statistics Co-Editor: Chapman & Hall/CRC Statistics and Applied Probability Monograph Series Advising & Collaboration Professor Bunea has mentored numerous doctoral and post-doctoral researchers, including Xin Bing, Shuyu Liu, Seth Strimas-Mackey, and Yang Ning, among others. Collaborative projects extend across Cornell and external institutions, producing widely-used software packages and high-impact publications. Contact Office: 1184 Comstock Hall, Cornell University Email: fb238@cornell.edu Phone: (607) 255-8449

Andreas VlachosView profile

Professor

• Natural Language Processing
• Machine Learning
• Dialogue Modelling
• +10 more

Andreas Vlachos is a Professor of Natural Language Processing and Machine Learning at the Department of Computer Science and Technology, University of Cambridge, and holds the Dinesh Dhamija Fellowship at Fitzwilliam College. His research spans dialogue modeling, automated fact-checking, imitation learning, semantic parsing, biomedical text mining, and trustworthiness in AI systems. PhD in Computer Science, University of Cambridge (supervised by Ted Briscoe and Zoubin Ghahramani) Lecturer at University of Sheffield Postdoctoral roles at UCL, University of Cambridge (NLIP group, Stephen Clark), and University of Wisconsin-Madison (Mark Craven) Current research focuses on evaluating and mitigating biases in language models, advancing fact-checking methodologies, and improving model robustness through interpolation, reinforcement learning, and causal reasoning. His work integrates natural logic, knowledge graphs, and multimodal evidence for verification tasks. Recent publications address uncertainty quantification, temporal planning benchmarks, and ethical framing of NLP artifacts. Grants from ERC, EPSRC, Facebook, Google, and the Alan Turing Institute fund his research team. Collaborations include Sebastian Riedel, Stephen Clark, and Mark Craven. Key projects explore disinformation detection, long-form generation, and confidence calibration in AI systems.

• History of Childhood and conceptions of childhood in Japan
• Japanese Rules of Etiquette
• Early Modern Japanese lifestyles and value orientations as reflected in Japanese guidebook literature
• +3 more

Michael Kinski serves as Professor of Japanese History of Thought and Japanology at Goethe University Frankfurt within the Faculty of Languages and Cultural Studies, concurrently leading the Institute for East Asian Philologies as Acting Director since 2013. His academic trajectory spans prestigious German institutions including Humboldt University Berlin (1998-2009) and Tuebingen University (1991-1998), with prior research engagement at Japanese universities including Tokyo University and Ritsumeikan. He completed his doctoral studies at Tuebingen University in 1991 following an M.A. at Bochum University (1987), with formative research periods in Japan at Nagoya University, Tokyo University, and Ritsumeikan University. His scholarly foundation centers on Japanese intellectual history, particularly the Edo period. Kinski's research program systematically examines Japanese societal structures through interconnected domains: Historical conceptions of childhood and developmental frameworks Formalized etiquette systems as cultural expression Material culture studies focusing on food practices and consumption Scientific knowledge transmission via Rangaku (Dutch Studies) Social value systems reflected in travel literature Intellectual history of Early Modern Japan No scientific awards were documented in source materials. Information regarding student supervision, research grants, laboratory facilities, or collaborative teams was not provided in the available texts.

Kevin D. AshleyView profile

Professor

• Computational Social Science
• Artificial Intelligence
• Algorithms
• +7 more

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.

Mohsen GoudarziView profile

Associate Professor

• Qur'anic Studies
• Early Islamic History
• Late Antiquity Religious Developments
• +4 more

Mohsen Goudarzi is an Associate Professor of Islamic Studies at Harvard Divinity School (HDS), part of Harvard University. He joined the faculty in 2021 after teaching at the University of Minnesota. His academic background includes a PhD from Harvard University and an MA from Stanford University. His research focuses on the Qur’an and early Islamic history, employing literary, linguistic, comparative, and historical approaches. Key interests include the Qur’an’s role in Late Antique religious developments, Islamic exegetical traditions (tafsīr), and theological frameworks (kalām). His current projects explore the Qur’anic worldview’s interpretation and the significance of Meccan cultic rituals to early Islamic identity. He has received teaching excellence awards, including a certificate from the University of Minnesota’s Center for Educational Innovation and three teaching distinctions from Harvard’s Office of Undergraduate Education. Research outputs include groundbreaking articles on Qur’anic exegesis, cultic practices, and interreligious dynamics. Notable works analyze the Qur’an’s engagement with Abrahamic traditions, ritual practices in Mecca, and the textual history of early Islamic manuscripts. His collaborative work on the Ṣan‘ā’1 codex redefined understandings of early Qur’anic canonization. Teaching spans HDS and Harvard’s Faculty of Arts and Sciences (FAS), covering Islamic studies, Qur’anic studies, and religious history. He advises students in HDS programs and contributes to interdisciplinary initiatives at the intersection of theology, history, and textual criticism.

• Natural Language Processing
• Large Language Models
• Digital Libraries
• +7 more

Min Yen Kan is an Associate Professor and Vice Dean of Undergraduate Studies at the National University of Singapore's School of Computing, Department of Computer Science. With a PhD from Columbia University (2002), he leads the Web Information Retrieval / Natural Language Processing Group (WING.NUS) and serves as ACL Ethics Committee co-chair. His research spans Natural Language Processing , Large Language Models , Digital Libraries , and Information Retrieval , with specific focus on scientific discourse analysis, fact verification, and multimodal systems. Current projects include Scholarly Document Information Extraction (TRL 6), Task-Oriented Dialogue Systems (TRL 4), and Recommendation Systems (TRL 5). Recent publications reveal strong trends in LLM limitations (bias, hallucination, evaluation), conversational recommendation systems , and misinformation detection . His work consistently bridges theoretical NLP with real-world applications in digital libraries and scientific communication. Award highlights include: CIKM 2019 Best Paper Award ACL Distinguished Service Awards Vannevar Bush Best Paper Award (JCDL 2012) ACM Distinguished Speaker designation Kan mentors PhD students with placements at Google and USTC, and serves as associate editor for Information Retrieval and survey editor for Journal of AI Research . His lab WING.NUS develops practical tools like SciWING for scientific document processing and FANG for fake news detection. Media engagements include commentary on AI regulations in Southeast Asia and workforce implications in the AI era.

Huaxiu YaoView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Robotics
• +7 more

Huaxiu Yao is an Assistant Professor at the University of North Carolina at Chapel Hill, holding a joint appointment in the School of Data Science and Society and the Department of Computer Science (College of Arts & Sciences). His research focuses on building reliable large-scale AI models (foundation models) with applications in healthcare, robotics, genomics, and transportation. He leads the AIMING Lab, which explores adaptive intelligence through alignment, interaction, and learning. Education: Ph.D. from Pennsylvania State University (2021), Postdoctoral Scholar at Stanford University (hosted by Chelsea Finn). Research Interests: Generalizable AI agents, preference alignment, out-of-distribution generalization, embodied AI, and multimodal reasoning. Key applications include biomedicine, robotics, and vision-language systems. Notable Awards: KDD Best Paper Award (2024), Amazon Research Awards (2025), TMLR Outstanding Paper Award (2024). Advising & Labs: Recruits Ph.D. and intern students. Leads the AIMING Lab, affiliated with UNC NLP Group. Organizes workshops on foundation models (ICML 2024) and trustworthy AI systems. Publications: Over 40 peer-reviewed papers, including top venues like ICLR, NeurIPS, and ICML. Focuses on AI alignment, multimodal systems, and domain generalization.

Silvia VESCOView profile

Associate Professor

• Japanese Art History
• Edo Period Art
• Ukiyo-e Prints
• +7 more

Dr. Silvia VESCO is an Associate Professor in the Department of Asian and North African Studies at Ca' Foscari University of Venice, where she specializes in Japanese art history, particularly Edo-period visual culture, ukiyo-e prints, illustrated books, and the works of Katsushika Hokusai. She is actively involved in research, teaching, and cultural curation, with a strong focus on Italian collections of Japanese art and cross-cultural artistic dialogues between Japan and the West. Education: PhD in History of Indian and East Asian Art, Ca' Foscari University of Venice (1999) Master in Art & Archaeology, SOAS, University of London (1995) Degree in Oriental Languages and Literatures, University of Venice (1993, with honors) Her research interests encompass Japanese aesthetics, museum studies, and the global reception of Japanese art. She has led major digitization projects for the Museum of Oriental Art in Venice and contributed to the development of its new museological framework. Her scholarly work reveals a consistent focus on Hokusai, Edo-period print culture, and the philosophical dimensions of Japanese visual forms. The recent publications highlight a deep engagement with Hokusai’s pedagogical works, the aesthetics of emptiness, and contemporary reflections on nature in post-Fukushima Japan. Her interdisciplinary approach bridges art history, cultural studies, and museum practice. Scientific Recognition: Finalist, Premio Nazionale per la divulgazione scientifica 'Giancarlo Dosi' (2020) Japan Foundation Fellowship (1997) Postgraduate scholarship from the University of Venice (1994) She has supervised numerous MA theses, served on PhD committees, and mentored students in Japanese art history. Her research has been supported by grants from the Japan Foundation and institutional collaborations with museums and cultural centers. She is a referee for VQR, Edizioni Ca' Foscari, and international journals, and serves on the scientific committees of several academic and museum publications. Labs and Teams: Scientific Committee, Museum of Oriental Art, Ca' Pesaro, Venice Scientific Committee, Edizioni Ca' Foscari Coordinator, Scientific Committee for Ca' Foscari Japanese Studies, Arts and Literature Member of the editorial board of 'Venezia Arti' and 'Quaderni del Polo museale del Veneto'

Peter HendersonView profile

Assistant Professor

• AI safety
• Foundation models
• Law and AI
• +7 more

Peter Henderson is an Assistant Professor at Princeton University with joint appointments in the Department of Computer Science and the School of Public and International Affairs. He is affiliated with the Center for Information Technology Policy (CITP), Princeton Language and Intelligence Initiative (PLI), Center for Statistics and Machine Learning (CSML), and Program in Law & Public Policy (PLAW). J.D./Ph.D., Stanford University, 2023 M.Sc., McGill University and Montréal Institute for Learning Algorithms Henderson's research focuses on the critical intersection of artificial intelligence and law, with particular emphasis on AI safety, methods to improve reasoning in foundation models, interdisciplinary approaches to law and AI, and AI governance. His work spans language-grounded reinforcement learning, alignment techniques, strategic decision-making in legal contexts, and public interest artificial intelligence. He investigates how legal frameworks can guide the development of AI systems that benefit society while addressing potential harms. Henderson's recent publications reveal a strong trajectory toward addressing the safety, governance, and legal implications of foundation models. His work combines rigorous technical AI research with deep legal analysis, particularly examining how intellectual property law interacts with AI development, regulatory pathways that balance innovation with harm prevention, and the role of law in shaping responsible AI deployment. A significant thread throughout his research is the development of better evaluation methodologies for AI systems, especially in critical domains like law. SEAS Excellence in Teaching Award (2025) Henderson leads the Princeton Law+Language, AI, & Society (POLARIS) Lab, where he advises students and researchers working at the intersection of AI and legal studies. His research has been supported through collaborations with government agencies, including work with the IRS on audit selection algorithms. His findings have informed practical applications in government efficiency and equity, as well as legal system improvements. Henderson runs the POLARIS Lab at Princeton, which focuses on developing AI systems that work for the public interest, particularly in legal contexts. His team develops sequential decision-making systems for government efficiency, foundation models capable of reasoning about law, and improved safety evaluation frameworks for AI systems. The lab maintains strong connections with legal practitioners and policymakers to ensure research has real-world impact.

• Information Technology Law
• Infocommunications Law
• Intellectual Property Law
• +8 more

Associate Professor Kiat Boon, Daniel SENG is a leading academic at the National University of Singapore (NUS), specializing in technology law and infocommunications law. He currently serves as Director of the LLM (Intellectual Property & Technology Law) program and IT Coordinator. Previously, he held roles as Director of Research at the Singapore Academy of Law (2001–2003), partner and head of technology practice at Rajah & Tann, and non-residential fellow at Stanford Law School’s Center for Legal Informatics (CodeX). His education includes a JSD and JSM from Stanford University, BCL (Oxford, Rupert Cross Prize recipient, 1994), and LLB (NUS with first-class honors). His research employs machine learning, NLP, and big data to analyze digital law challenges, particularly in copyright takedown notices and AI governance. Research interests span information technology law, empirical legal studies, quantitative research, and AI’s intersection with legal reasoning. He contributes to global legal reform via advisory roles at the World Intellectual Property Organization (WIPO), focusing on copyright exceptions, music licensing, and intermediary liability. Key awards include the 1994 Rupert Cross Prize. His work bridges law and technology through publications on digital evidence, metaverse legal frameworks, and AI’s impact on private law. He is actively involved in shaping Singapore’s legal infrastructure through government committees and academic initiatives.

John B. WhitmanView profile

Professor

• Syntax
• Language Variation
• Historical Linguistics
• +3 more

John B. Whitman is a Professor of Linguistics at Cornell University's College of Arts and Sciences. His research focuses on language variation, syntax, historical linguistics, and East Asian languages, particularly Japanese and Korean. He explores typological universals, syntactic variation, and diachronic developments, contributing to debates on configurationality and structural universals. Whitman has published extensively on topics ranging from Japanese historical phonology to comparative syntax across East Asian languages. His work often integrates cross-linguistic analysis with neuroscientific insights, as seen in studies on semantic number processing. He has received grants for projects including language revitalization initiatives and syntactic research, and he teaches courses on Japanese language history and language endangerment. Whitman collaborates with interdisciplinary teams and actively engages in linguistic fieldwork and historical text analysis, maintaining affiliations with the East Asia Program and research labs at Cornell. Research interests include syntactic variation, historical syntax, and the interaction between language structure and diachronic change. His recent work examines the evolution of verbal conjugations in Japanese/Korean and the typological implications of syntactic reanalysis. Whitman's publications also address methodological questions in glossing practices and comparative lexicography, bridging historical linguistics with modern computational analysis. Grants and projects include funding from the New Frontier Grants for collaborative research on language documentation and historical syntax. He advises graduate students in the linguistics program and contributes to Cornell's language revitalization efforts, such as Cayuga language preservation initiatives. Whitman's work frequently intersects with cognitive science, as seen in neuroimaging studies of linguistic structures.

Alaina LemonView profile

Professor

• Socio-cultural anthropology
• Performance and language
• Historical narrative
• +5 more

Alaina Lemon is a Professor of Anthropology at the University of Michigan, affiliated with the College of Literature, Science, and the Arts (LSA). She serves as Director of Undergraduate Studies in Anthropology and holds affiliations with the Center for Russian, East European, and Eurasian Studies (CREES), the Weiser Center for Europe and Eurasia, and the Interdepartmental Program in Anthropology and History. Her research focuses on socio-cultural anthropology, performance studies, and visual culture, with expertise in Russia, the Romani diaspora, and post-Socialist states. Education: BA in Anthropology (University of Wisconsin, 1987), MA (University of Chicago, 1988), and PhD (University of Chicago, 1996). Notable awards include the Wayne S. Vucinich Book Prize (2001), Heldt Book Prize (2001), and a 2023 visiting scholar position at the École des Hautes Études en Sciences Sociales (Paris). Her work bridges historical and contemporary issues, exploring themes like phatic labor, media infrastructures, and affective politics. Recent projects include editing the documentary Tremors (2023) and researching Soviet-era moral projects through studies of Moscow’s Metro and canine-human interactions. Lemon’s interdisciplinary approach integrates performance studies, linguistic anthropology, and critical race theory to analyze cultural dynamics in transitional societies. Grants include a 2019-2024 University of Michigan Office of Research grant for film collaboration and a 2002-2003 International Research and Exchanges Board fellowship. She has authored influential books such as Between Two Fires (2000) and Technologies for Intuition (2017), and her films document Romani experiences and urban cultural phenomena.

Alexis BattleView profile

Associate Professor

• Genomics
• Machine Learning
• Computational Biology
• +3 more

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .