David A. Smith is an Associate Professor at the Khoury College of Computer Sciences, Northeastern University. His research focuses on Natural Language Processing (NLP) and computational linguistics, with applications in machine translation, information retrieval, digital humanities, and social sciences. He is a founding member of the NULab for Texts, Maps, and Networks, a research center focused on digital humanities and computational social sciences. Smith's work has been funded by grants from the Mellon Foundation, NEH, and IMLS, supporting projects such as the Viral Texts initiative analyzing 19th-century newspaper networks and the Oceanic Exchanges project tracking transnational information flows. He has contributed to advancements in OCR for historical texts, text reuse detection, and computational analysis of classical languages. He has advised numerous PhD students, including Shijia Liu, Si Wu, and Ryan Muther, and teaches courses like Natural Language Processing and Information Retrieval. His research has been featured in outlets like Wired and the Economist .
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.
Prof. Dr. Gülşen Eryiğit is a Professor at Istanbul Technical University within the Faculty of Computer and Informatics , Department of Artificial Intelligence and Data Engineering . She founded and directs the ITU Natural Language Processing Group , Turkey's leading team in Turkish-language NLP, and serves as Senior Action Editor for ACL RR , Director of ITU TÖMER (Turkish Language Teaching Center), and Co-Chair of the EU UniDive Cost Action WG3. Education: PhD in Computer Engineering from ITU (2007), MSc and BSc from ITU and Marmara University Research: Focuses on Natural Language Processing for Turkish, including dependency parsing , coreference resolution , multiword expressions , and language education technology Her recent work involves multilingual transfer learning , LLM applications for Turkish text simplification, and gamification for morphology education. She has received prestigious awards like the Siemens Excellence Award and TÜBİTAK's Above Threshold Award . Her research has produced 65+ publications and 29+ projects funded by EU, TÜBİTAK, and industry partners. Scientific Awards: Siemens Excellence Award (2007) Above Threshold Award (TÜBİTAK, 2015) Certificate of Appreciation (EU 7th Framework, 2012) Thank You Plaque (ITU, 2017) The ITU NLP Group under her leadership has developed Turkey's first licensed NLP software exported internationally. She collaborates with European institutions through COST actions and participates in ACL, CoNLL, and LREC conferences. Her lab focuses on language technology for Turkish , including sign language processing and social media normalization.
Mark Gales is Professor of Information Engineering at the University of Cambridge and an Official Fellow at Emmanuel College. He is currently on sabbatical leave for the 2024/25 academic year. Prior to his academic career, he worked as a consultant at Roke Manor Research Ltd, developing radar systems, before transitioning to speech and language processing. PhD in 'Model-Based Techniques for Robust Speech Recognition' (University of Cambridge, 1995) BA in Electrical and Information Sciences (University of Cambridge, 1988) His research focuses on speech and language processing , particularly in automated language assessment and low-resource speech technology . He leads the Automated Language Teaching and Assessment (ALTA) Institute , which collaborates with Cambridge University Press & Assessment (CUP&A) to develop commercial tools like Linguaskill and Speak & Improve . These platforms provide automated spoken/written assessment for millions of users globally. Recent publications highlight his work in LLM-driven speech processing , including adversarial attacks on foundation models, end-to-end spoken error correction, and uncertainty estimation frameworks. His team's research spans multilingual capabilities, with deployments in languages ranging from Dholuo to Tok Pisin . Awards : IEEE Fellow, ISCA Fellow Leadership : Fellows' Steward at Emmanuel College Mark has contributed extensively to Hidden Markov Model (HMM) applications in speech recognition, which underpinned early automatic speech systems. His work now bridges LLM-based language assessment with cross-lingual transfer learning and robustness testing for real-world deployments.
Mohammad Aliannejadi is an Assistant Professor at the IRLab (formerly ILPS) within the Informatics Institute at the University of Amsterdam. His research focuses on Information Retrieval (IR), machine learning, natural language processing (NLP), and conversational systems, particularly in modeling user information needs on mobile devices and conversational search systems. He holds a Ph.D. in Informatics from Università della Svizzera italiana (USI), Lugano, Switzerland, and a M.Sc. in Computer Engineering from Tehran Polytechnic. During his Ph.D., he visited the CIIR Lab at the University of Massachusetts Amherst, USA. His research interests include conversational search systems, recommender systems, unified search frameworks, and user-centric evaluation methodologies. Notable contributions include work on clarifying questions in open-domain dialogues, contextual suggestion systems, and cross-market recommendation. Aliannejadi has organized major shared tasks and workshops, including the IGLU Contest (NeurIPS 2021) and XMRec Workshop (RecSys 2021). He serves on program committees of top IR conferences like SIGIR, CIKM, and ECIR, and has authored over 50 peer-reviewed publications in these areas. His work has received recognition, including top performance in TREC Contextual Suggestion tracks (2015, 2016). He actively contributes to the IR community through teaching, including courses on Information Retrieval and Human-in-the-Loop Machine Learning at the University of Amsterdam.
Bistra Andreeva is a full Professor of Phonetics and Phonology at Saarland University, Department of Language Science and Technology. She is also a principal investigator of the DFG-funded project “Judeo-Spanish in Bulgaria: a contact language between archaism and innovation” (2022-2025) and leads or co-leads several other externally funded projects on prosody, information structure, and language contact. She teaches and has taught at Saarland University, Sofia University “St. Kliment Ohridski”, and other European universities. Education & Academic Background Habilitation (kumulative Habilitationsschrift): “Contrastive Prosody: Bulgarian vs. German”, Saarland University, 2016. PhD (Dr. phil.): “Zur Phonetik und Phonologie der Intonation der Sofioter-Varietät des Bulgarischen”, Saarland University, 2007. Research Interests Andreeva’s research focuses on the phonetics and phonology of intonation and rhythm, cross-language and individual differences in the production and perception of syllabic prominence, the relation between intonation and information structure, minority languages (especially Judeo-Spanish in Bulgaria), and the interaction between information density and prosodic structure. Her methodological expertise includes experimental phonetics, corpus-based studies, and acoustic analysis. Major Projects SFB 1102 C1: “Information Density and the Predictability of Phonetic Structure” (DFG, 2014-2026) JuSpa: “Judeo-Spanish in Bulgaria: a contact language between archaism and innovation” (DFG, 2022-2025) Prosodic aspects of Bulgarian compared to other languages with lexical stress (Bulgarian National Science Fund, 2019-2024) Prosodic manifestations of focus in French and English from a Bulgarian point of view (DAAD & Sofia University, 2021-2023) Scientific Awards & Recognition While no major named prizes are listed, Andreeva’s work has been continuously supported by competitive grants from the German Research Foundation (DFG), DAAD, and Bulgarian National Science Fund. Her publications appear in top-tier journals and conference proceedings (Journal of the Acoustical Society of America, Interspeech, Speech Prosody, International Congress of Phonetic Sciences). Teaching & Supervision She offers a broad spectrum of courses including Experimental Phonetics, Prosody, Phonetics & Phonology of Slavic Languages, Introduction to Instrumental Phonetics, and seminars on language contact. She has supervised numerous BA, MA, and PhD theses and regularly teaches at the PhD School of Sofia University. Labs & Teams She is affiliated with the Phonetics Laboratory at Saarland University and collaborates closely with the Institute for Bulgarian Language (Bulgarian Academy of Sciences), working in interdisciplinary teams involving phoneticians, computational linguists, and field linguists.
Alison J. Mackey is Professor and Chair of the Department of Linguistics at Georgetown University, College of Arts and Sciences. She is a leading scholar in second language acquisition (SLA), with a focus on interaction, feedback, research methodology, and language learning across the lifespan. Her research interests include second language acquisition , task-based language teaching , research methodology , interaction and corrective feedback , and language learning in children and adults . She has published extensively in top-tier journals and book series, shaping methodological standards in the field. Her recent publications reflect a strong trend in methodological rigor , interactionist approaches , and practical applications of SLA research. Themes include data elicitation , stimulated recall , task design , and pragmatic development , spanning both theoretical and classroom-based inquiry. Mildenberg Prize (2012) for The Handbook of Second Language Acquisition American Association for Applied Linguistics Distinguished Scholarship and Service Award International Association of Task-based Language Learning and Teaching Distinguished Achievement Award CHOICE Outstanding Academic Title (2012) Alison Mackey has advised numerous scholars through co-authorship and editorial leadership. She is Editor-in-Chief of Cambridge University Press Annual Review of Applied Linguistics and Editor of the Routledge Second Language Research series, guiding the publication of cutting-edge research. While specific grants are not listed, her editorial work and high citation count (>35,000) reflect significant research impact and funding support. She leads and contributes to major research initiatives such as the IRIS Repository , promoting open-access research instruments in SLA. Her work fosters collaboration across institutions and supports methodological transparency and replication in the field.
Mark Baker is a Professor of Linguistics and Cognitive Science at Rutgers University. His work focuses on comparative syntax, linguistic universals, semantic roles, and the study of Amerindian and African languages. He holds the title of Distinguished Professor and maintains an office in Scott Hall. As of 2021, his office hours were by appointment due to sabbatical leave. His research interests include syntactic diversity, its limits, and patterns across languages. Notable themes in his work involve logophoric pronouns, switch-reference mechanisms, and the relationship between case systems and agreement structures. He has contributed to discussions on language typology, formal syntax, and the cognitive foundations of linguistic structures. Baker teaches advanced syntax courses and has published extensively on topics ranging from Panoan languages to theoretical models in generative grammar. His recent articles explore syntactic variation, morphosyntactic alignment, and interdisciplinary connections between linguistics and cognitive science. He serves on editorial boards and has reviewed for journals such as Journal of East Asian Linguistics and Yearbook of Corpus Linguistics and Pragmatics . His work bridges formal linguistic theory with empirical cross-linguistic analysis, emphasizing the interplay between universal grammatical principles and lineage-specific traits.
Emily M. Bender is the Thomas L. and Margo G. Wyckoff Endowed Professor in the Department of Linguistics at the University of Washington. She also holds adjunct appointments in the School of Computer Science and Engineering and the Information School. Her research spans multilingual grammar engineering, computational linguistics, societal impacts of language technology, and sociolinguistic variation. She directs the Computational Linguistics Laboratory (The Treehouse) and leads the CLMS program. Bender is a Fellow of the AAAS (2022) and previously served as Howard and Frances Nostrand Endowed Professor (2019–2022). She has authored influential textbooks on NLP fundamentals and pioneered work on data statements to mitigate bias in NLP systems. Her work integrates linguistic theory with computational methods, emphasizing ethical AI and language documentation. Education: PhD in Linguistics from Stanford University (advisor: Ivan A. Sag), AB in Linguistics from UC Berkeley, with studies at Tohoku University. Past roles include NAACL Executive Board Chair (2016–2017) and current roles in the Association for Computational Linguistics leadership. Her Erdős number is 4. Research focuses on the LinGO Grammar Matrix, automatic grammar inference from interlinear glossed text (AGGREGATION project), and societal implications of NLP technologies like large language models. She co-leads the RAISE initiative and contributes to labs like the Tech Policy Lab and Value Sensitive Design Lab. Over 30 advisees have completed PhD and MS degrees under her mentorship. Teaching includes courses on syntax for NLP, societal impacts of language tech, and computational linguistics. Her 2020 ACL paper on form-meaning distinctions in NLP has been influential in ethical discussions. Current projects include The AI CON (2025) on combating tech hype.
Tim Van de Cruys is a Senior Lecturer at the Faculty of Arts, KU Leuven, serving as Head of the Centre for Computational Linguistics (CCL). He maintains significant affiliations with LECTIO (KU Leuven Institute for the Study of the Transmission of Texts, Ideas and Images), Leuven.AI (KU Leuven Institute for Artificial Intelligence), and LILI (KU Leuven Interdisciplinary Language Institute). His work bridges computational linguistics, artificial intelligence, and humanities research with practical applications across multiple disciplines. Dr. Van de Cruys specializes in computational semantics and creative language generation, with particular expertise in applying NLP techniques to historical and classical texts. His research spans multiple domains including: Natural Language Processing for ancient languages (Latin, Ancient Greek) Computational approaches to lexical and compositional semantics Large language models and their applications in humanities research Creative language generation and human-AI collaboration Named entity recognition and disambiguation in historical contexts Non-autoregressive modeling for sequential generation tasks His recent publications demonstrate a strong focus on applying cutting-edge NLP techniques to humanities challenges, particularly in processing ancient languages. He frequently employs transformer models to address named entity recognition, word sense discrimination, and semantic analysis in low-resource language contexts. His work consistently bridges formal linguistic theory with practical computational applications, creating valuable tools for digital humanities scholars. As promotor and co-promotor on numerous research projects extending through 2029, Dr. Van de Cruys supervises PhD students working at the AI-humanities intersection. His current major projects include "Living Corpora" (exploring human-AI collaboration in digital humanities), "Stochastic processes and non-autoregressive models for sequential generation," and "NIKAW" (exploring knowledge networks from classical antiquity). These projects demonstrate his commitment to advancing both theoretical understanding and practical applications of computational linguistics. He teaches various courses including Computational Linguistics, Scripting Languages, Programming for Humanities, Computational Creativity, and AI for Humanities, training students to work at this critical interdisciplinary crossroads. His leadership of the Centre for Computational Linguistics positions him at the forefront of computational linguistics research in Belgium, where he continues to expand the boundaries of what's possible at the intersection of language, computation, and humanistic inquiry.
Mohammad T. Alhawary is Professor of Arabic Linguistics and Second Language Acquisition at the University of Michigan's Middle East Studies department within the College of Literature, Science, and the Arts. He serves as Director of both the MA Program in Arabic for Professional Purposes (APP) and the MA Program in Teaching Arabic as a Foreign Language (TAFL). His educational background includes a Ph.D. from Georgetown University (1999). Prior to joining the University of Michigan, he contributed to developing Arabic and Middle Eastern Studies programs at various US institutions. Professor Alhawary's research spans both theoretical and applied Arabic linguistics, with particular focus on second language acquisition processes. His work examines how factors like age, input quality, output practice, and first language transfer affect Arabic language learning. He has made significant contributions to understanding Arabic language pedagogy, curriculum design, proficiency testing, and the application of technology in language learning. His research also extends to bilingualism, multilingualism, language impairment, and Arabic medieval grammatical traditions. His publications reflect a strong trajectory in Arabic linguistics research, with recent works focusing on practical language teaching applications, reading comprehension mechanisms, code-switching patterns in digital communication, and multilingual acquisition processes. The 2023 publication 'Teaching Arabic as a Foreign Language' represents his latest contribution to language pedagogy methodology. 2019 AATA Book Award for 'Arabic Second Language Learning and Effects of Input, Transfer, and Typology' As an academic leader, Professor Alhawary serves as Executive Director of the American Association of Teachers of Arabic and edits both the Journal of Arabic Linguistics Tradition and Al-'Arabiyya journal. He continues to develop empirical research on Arabic second language acquisition to inform teaching practices both in America and globally.
Sarah Ita Levitan is an Assistant Professor in the Department of Computer Science at Hunter College, CUNY, and a member of the doctoral faculty in both Computer Science and Linguistics PhD programs at the CUNY Graduate Center. She previously served as a Postdoctoral Research Scientist at Columbia University, where she completed her PhD in Computer Science in 2019 under Dr. Julia Hirschberg. Research Focus: Spoken Language Processing Natural Language Processing Paralinguistic Analysis Trustworthiness and Deception Detection Acoustic-Procedic and Lexical Feature Extraction Online Radicalization and Misinformation Recent Publications demonstrate expertise in analyzing speech and text for trust cues, deception detection, and mental health prediction. Her awards include grants from NSF, Google, and Columbia University fellowships. She leads the Hunter Speech Lab , mentoring PhD, MS, and undergraduate students in computational linguistics research. Scientific Awards and Grants: NSF EAGER Grant (2023) Google Cyber NYC Grant (2023) NSF AI Institute Grant (2023) Air Force Office of Scientific Research Grant (2020) Brown Institute Seed Grant (2020) Knight News Innovation Fellowship (2018) Teaching: Courses include Natural Language Processing (undergraduate/graduate), Computational Linguistics, Computer Theory, and advanced topics in spoken language processing at both Hunter College and Columbia University.
Jiawei Han is the Michael Aiken Chair Professor at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Siebel School of Computing and Data Science and the Department of Computer Science. He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison (1985). His research focuses on Data Mining, Text Mining, and Intelligent Systems, with notable contributions to knowledge hypercubes, molecular discovery, and geospatial understanding. Key affiliations include leading the Data Mining Research Group (DMG) and the Data and Information Systems Research Laboratory (DAIS). He is also involved in major initiatives like the NSF AI Institute for Molecular Discovery (Molecule Maker Lab) and the DARPA INCAS project. Recent work emphasizes large language models (LLMs), scientific knowledge integration, and graph-based reasoning. Notable achievements include an ICLR 2024 Outstanding Paper Honorable Mention (co-authored with Suyu Ge) and mentoring Yu Meng, recipient of the ACM SIGKDD 2024 Dissertation Award. Teaching includes courses such as CS 412 (Data Mining), CS 512 (Data Mining Principles), and specialized topics like Text Mining with Large Language Models (Fall 2024). He has authored/co-authored numerous books, including editions of *Data Mining: Concepts and Techniques* and works on taxonomy discovery and text mining. His research spans interdisciplinary areas such as bioinformatics, geospatial analytics, and molecular innovation, with a focus on practical applications and foundational theory.
Kostas Daniilidis is the Ruth Yalom Stone Professor at the University of Pennsylvania in the School of Engineering and Applied Science , specifically the Department of Computer and Information Science . He is also affiliated with the GRASP Laboratory and Archimedes, Athena Research Center, Greece . Education : PhD in Computer Science (1992) from the University of Karlsruhe with Hans-Hellmut Nagel Diploma in Electrical Engineering (1986) from the National Technical University of Athens Research Interests : Kostas Daniilidis is a leading researcher in Computer Vision and Robotics , with significant contributions to event-based vision , equivariant learning , 3D human pose estimation , and hand-eye calibration . His work spans neural rendering , dynamic scene modeling , and low-latency sensing systems . Article Trends : Daniilidis’s recent publications focus on event cameras for low-light and high-speed applications, Gaussian splatting for real-time 3D reconstruction, and equivariant neural architectures for robust motion estimation. His work bridges deep learning with geometric vision , emphasizing human mesh recovery and multi-agent coordination . Scientific Awards : Best Conference Paper Award at ICRA 2017 IEEE Fellow (2012) Teaching : He has taught courses such as CIS580: Machine Perception and CIS121: Data Structures , alongside advanced topics in robotics and computer vision. Lab & Collaborations : As director of the GRASP Laboratory (2008–2013), he fostered interdisciplinary research in robotics, and currently collaborates with institutions like the Athena Research Center in Greece.
Gabrielle Hodge is a Senior Lecturer in Sign Language Linguistics at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. A deaf researcher, she specializes in sociolinguistics related to deaf communities, sign languages, and multimodal communication. Her work incorporates corpus linguistics, applied linguistics, and semiotics methodologies. Education: PhD in Linguistics (Macquarie University, 2014), BA (Hons) in Linguistics (La Trobe University, 2008). Teaching includes undergraduate and postgraduate courses in sign language linguistics and sociolinguistics. She chairs the University BSL Plan Implementation Group (2024-2030) and actively supervises PhD and MSc students in deaf community research. Research focuses on accessibility, sign language corpus methods, and inclusive language theory. Notable projects include the Accessibility & Inclusion Toolkit for deaf Australians and Signing to Know & Survive , exploring deaf communication resilience. She develops training for educators and interpreters, emphasizing direct access without relay systems. Key contributions include advancing corpus-driven sign language research, analyzing deaf professionals' trust in interpreters, and creating climate change resilience resources in Auslan. Her work challenges traditional linguistic frameworks to better incorporate deaf perspectives and embodied communication practices.
