جست‌وجوی استاد و پژوهشگر

Vera Dembergمشاهده پروفایل

استاد

• Cognitive Models of Human Language Understanding
• Natural Language Generation
• Experimental Psycholinguistics
• +۷ مورد دیگر

Prof. Dr. Vera Demberg is a full Professor of Computer Science and Computational Linguistics at Saarland University, affiliated with the Faculty of Mathematics and Computer Science. She holds a chair in her field and is co-opted into the Department of Language Science and Technology. Since 2024, she has also been a Max Planck Fellow at the Max Planck Institute for Informatics, where she leads a research group on Multimodal Language Processing. She currently serves as Dean of Study Affairs for her faculty (2024–2026). Her research focuses on cognitive models of human language understanding, natural language generation, experimental psycholinguistics, and computational discourse and pragmatics. She integrates computational modeling with empirical methods such as eye-tracking and reading time experiments to study how humans process language in real time. Key themes include individual differences in comprehension, information-theoretic models, and multimodal language processing (language and vision/body language). The recent publications and talks reflect a strong trend in modeling incremental and predictive language processing, discourse coherence, and individualized interaction in dialogue. Her work bridges computational linguistics, cognitive science, and artificial intelligence, often applying rational agent models and information theory to human language processing. Elected Member of the Academy of Sciences and Literature Mainz (2024) ELLIS Fellow (2023) ERC Starting Grant 'Individualized Interaction in Discourse' (2020–2025) Cognitive Science Society Glushko Dissertation Prize (2011) Falling Walls Lab 2014, Berlin Multiple Google Anita Borg Scholarship Finalist recognitions Prof. Demberg advises several PhD students and postdoctoral researchers, including Marian Marchal, Anupama Chingacham, Iza Škrjanec, Alexandra Mayn, and Jiaxin Li. She leads multiple funded research projects, including an ERC Starting Grant and several SFB projects funded by the DFG. Her lab hosts guest researchers and organizes international workshops such as IndiREAD and IndiPRAG. She is actively involved in the academic community, serving on the Executive Committee of ACL, as Program Chair for SigDIAL 2024, and as Associate Editor for IEEE TPAMI and other journals. Her research group is involved in several major projects, including 'Individualized Interaction in Discourse' (ERC), 'Cognitive Modelling of Information Density for Discourse Relations' (SFB 1102), and the DFG Research Training Group on Neuroexplicit Models of Language, Vision, and Action. These projects explore the intersection of human cognition and machine language processing, often using eye-tracking and computational modeling.

Mohssen Esseesyمشاهده پروفایل

استاد

• Historical Linguistics
• Arabic Language Testing
• Curriculum Development
• +۳ مورد دیگر

Mohssen Esseesy is a Full-time Professor of Arabic and International Affairs at George Washington University, where he has been since 2004. He holds a Ph.D. with Distinction in Arabic from Georgetown University. Prior to GW, he served at the University of Michigan, Georgetown University, and the University of Florida. His expertise spans historical linguistics, Arabic-language testing, curriculum development, and teacher training. Professor Esseesy is actively engaged in research on grammaticalization processes in Arabic, presenting at Middle East Studies Association conferences. He contributed entries to the Encyclopedia of Arabic Language and Linguistics (Brill Publishers) and served on the Board of Reviewers for the Standards for Learning Arabic K-16 . He also held an elected position on the Executive Board of the American Association of Teachers of Arabic (2003-2005). He teaches courses such as Beginning Arabic , Modern Arabic Literature: Fiction , and Genres in Modern Arabic Literature . His work emphasizes bridging linguistic theory with pedagogical practice, particularly in Arabic language education.

Suresh Jagannathanمشاهده پروفایل

استاد

• Programming Language Semantics
• Formal Verification
• Type Theory
• +۷ مورد دیگر

Professor Suresh Jagannathan is a leading researcher in programming languages and formal verification. His work focuses on semantics of high-level languages, type theory, program analysis, and compiler design, with a particular emphasis on concurrent and distributed systems. He explores formal methods for certified compilation, memory model consistency, and verification techniques enabling safe program optimizations. Core research areas: programming language semantics, formal verification, type theory, compiler design Key applications: concurrent/distributed systems, certified compilation, safe neural network verification Recent publications highlight his contributions to automated verification of concurrent data structures, type-guided repair of input generators, and differentiable logic specifications for AI planning systems. His work combines theoretical rigor with practical implementations like ECOOP best papers and tool developments. Professor Jagannathan has received multiple scientific awards (not specified in available data) and maintains active collaborations with researchers in formal methods and systems verification communities.

Mirella Lapataمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۲ مورد دیگر

Mirella Lapata is a Professor at the School of Informatics, University of Edinburgh, with visiting roles at the University of Washington and MIT. Her research focuses on natural language processing, machine learning, computational linguistics, and natural language generation. She has held academic positions since 2002, progressing from Lecturer at the University of Sheffield and University of Edinburgh to Reader (2007) and eventually Professor (2012). Key awards include Fellowships from the Royal Society of Edinburgh (2019) and ACL (2019), as well as the Royal Society Wolfson Merit Award (2018). She leads major grants such as the £6.8M UKRI Centre for Doctoral Training in Natural Language Processing (2019) and the €1.9M ERC Consolidator Grant (2016). Her work spans semantic parsing, neural networks, text generation, and machine learning applications. She has delivered keynote speeches at major conferences like ACL, EMNLP, and ICLR. Professional service roles include associate editorships for Royal Society Open Science and JAIR, and conference chairs for EACL and EMNLP.

Louiqa Raschidمشاهده پروفایل

استاد

• Database Systems
• Data Integration
• Data Mining
• +۸ مورد دیگر

Louiqa Raschid is a Professor at the University of Maryland, holding appointments in the Robert H. Smith School of Business, the Institute for Advanced Computer Studies (UMIACS), and the Department of Computer Science. Her research bridges computer science and business information systems, focusing on data integration, management, and mining in non-traditional domains. Education: B.Tech (IIT Madras, 1980), PhD (University of Florida, 1987) Research Interests include: Data integration and mining across life sciences, health sciences, and financial ecosystems Humanitarian IT solutions for disaster management Semantic query optimization and data delivery techniques Grid and wide-area data management Article Trends reflect interdisciplinary efforts combining bioinformatics, database systems, and social behavior modeling. Key themes include ontology-driven data analysis, network-aware query optimization, and disaster relief systems development. Scientific Awards include: ACM Distinguished Member (2016) ACM Fellow (2016) IEEE Fellow (2000) DILS 2008 Best Paper Award Grants from NSF and DARPA have funded her work on biological data integration and financial cyberinfrastructure. She co-directs the Computational Linguistics and Information Processing (CLIP) Lab and collaborates with institutions worldwide.

Matthew Traxlerمشاهده پروفایل

استاد

• Psycholinguistics
• Cognitive Neuroscience
• Language Comprehension
• +۷ مورد دیگر

Matthew Traxler is a Distinguished Professor in the Department of Psychology at the University of California, Davis, and an affiliated faculty member of the UC Davis Center for Mind and Brain. His research focuses on unconscious processes in language comprehension, particularly syntactic parsing and semantic processing. Current NIH-sponsored work explores connections between working memory and syntactic parsing Former editorial roles include editorship of Language and Linguistics Compass and associate editorship of Quarterly Journal of Experimental Psychology Research Trends: Recent publications emphasize bilingual language processing, cognitive aging, syntactic priming, and electrophysiological correlates of language comprehension. Key methodologies include eye-tracking, ERP analysis, and multilevel modeling of individual differences. Scientific Awards & Roles: NIH-sponsored investigator Editorial Board Member - Journal of Memory and Language Consulting Editor - Journal of Experimental Psychology: Learning, Memory, and Cognition

Antonella Soraceمشاهده پروفایل

استاد

• Bilingualism
• Language acquisition
• Cognitive science
• +۳ مورد دیگر

Antonella Sorace is a Professor of Developmental Linguistics at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences, with an Honorary Professorship at University College London. She holds prestigious fellowships from the British Academy, Royal Society of Edinburgh, and American Association for the Advancement of Science. Her work bridges linguistics, psychology, and cognitive science, focusing on bilingualism across the lifespan, language acquisition, and the cognitive benefits of multilingualism. She pioneered the use of Magnitude Estimation in linguistic research and founded Bilingualism Matters, a global network promoting evidence-based language policies. Sorace has supervised over 40 PhD students and led major grants from ESRC, AHRC, and the EU. Her research explores bilingualism's impact on autism, heritage language attrition, and the interplay between syntax and pragmatics. Education: Laurea (University of Rome), MA (University of Southern California), PhD (University of Edinburgh) Affiliations: Visiting professorships at Utrecht, Trondheim, Max Planck Institute for Psycholinguistics, Johns Hopkins University, and others Research Interests: Bilingualism's effects on cognition, language attrition in adults, child bilingual acquisition, and experimental methods in linguistics. Her work highlights bilingualism's cognitive advantages and challenges stereotypes about 'native speaker' competence. She has quantified how bilingualism influences pragmatic reasoning and executive control, with special attention to neurodivergent populations like autistic individuals. Grants & Projects: Current and past grants include ERASMUS+ (2021-23), SSHRC (2019-22), and EU's 'Advancing the European Multilingual Experience' (2014-2019). Projects investigate bilingualism in autism, heritage language maintenance, and hate speech perception. She co-led studies on Gaelic medium education's cognitive benefits and the impact of intensive language learning. Awards: Beltane Fellowship for Public Engagement (2007-08), ESRC Knowledge Transfer Grant (2007-08) Bilingualism Matters: As founder and director, she created a global network providing accessible science communication about multilingualism. The organization advises schools, health services, and policymakers, with branches in 25+ countries. Sorace advocates for bilingualism's societal value through media outreach, including hundreds of lectures and interviews worldwide.

Thao Nguyenمشاهده پروفایل

استادیار

• Robotics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Thao Nguyen is an Assistant Professor in the Department of Computer Science at Haverford College . She focuses on robotics and artificial intelligence, particularly in areas like visual object search, language-conditioned observation models, and hierarchical planning systems. Her office is located at KINSC L303. Her research bridges human-guided robot learning with advanced state abstractions and multimodal interaction frameworks. Key contributions include integrating gesture-based inputs and natural language queries into robotic object retrieval systems, enabling more intuitive human-robot collaboration. Recent publications highlight her work on language-visual alignment , contextual robotics , and non-Markovian planning . Her projects leverage Bayesian inference, deep learning, and temporal logic to enhance robot perception and task execution.

Mayur Naikمشاهده پروفایل

استاد

• Programming Languages
• Artificial Intelligence
• Neurosymbolic Programming
• +۲ مورد دیگر

Mayur Naik is the Misra Family Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research specializes in programming languages and artificial intelligence, with current focus areas including neurosymbolic programming, trustworthy AI for healthcare, and AI-enhanced development tools. He leads the development of the Scallop neurosymbolic programming language and maintains active collaborations in bioinformatics and clinical research. Education: Ph.D. in Computer Science, Stanford University (2008) M.S. in Computer Science, Purdue University (2003) B.S. from BITS Pilani (1999) Research Focus: His work bridges symbolic AI with neural approaches through neurosymbolic programming, enabling interpretable and domain-aware solutions. Current projects include Dolphin (scalable neurosymbolic learning), IRIS (LLM-assisted static analysis), and applications in computer vision and healthcare. Research emphasizes both theoretical foundations and practical system implementations. Publication Trends (Recent Focus): Recent work demonstrates strong emphasis on neurosymbolic learning frameworks (55%), AI-enabled programming tools (30%), and healthcare applications (15%). Key technical threads include LLM integration with program analysis, GPU acceleration for symbolic reasoning, and weakly-supervised learning paradigms. Awards & Honors: Test of Time Award, Foundations of SW Engineering (2023) Distinguished Paper Awards (PLDI 2019, SIGSOFT 2015, FSE 2015, SIGPLAN 2014) NSF CAREER Award (2013) Lockheed-Martin Teaching Excellence Award (2015) Outstanding Junior Faculty Award, Georgia Tech (2016) Academic Leadership: Advises 8 PhD students with research spanning neurosymbolic systems, program analysis, and AI security. Teaches core courses CIS 5470 (Software Analysis) and CIS 5500 (Database Systems). Research supported by NSF and industry partnerships. Labs & Teams: Leads the neurosymbolic programming research group at UPenn, collaborating with Intel Labs, Google AI, and healthcare institutions. Group develops open-source tools including Scallop compiler and LLM-assisted analysis frameworks.

PAN Haihuaمشاهده پروفایل

استاد

• Chinese Linguistics
• Formal Semantics
• Syntax
• +۴ مورد دیگر

Prof. PAN Haihua is a Professor at The Chinese University of Hong Kong, where he has served since December 2015. Previously, he held academic positions at City University of Hong Kong (1995-2015), Huazhong University of Science and Technology (1986-1988), and was a Research Associate at CUHK in 1995. He earned his BA from Huazhong University of Science and Technology, MA from Wuhan University, and PhD from the University of Texas, USA. His educational background includes: BA, Huazhong University of Science and Technology, China MA, Wuhan University, China PhD, University of Texas, USA Prof. PAN's research centers on theoretical Chinese linguistics with emphases on formal semantics and syntax. His work systematically investigates reflexives, quantification, focus phenomena, and information structure in Mandarin Chinese. He has made foundational contributions to understanding donkey anaphora, negative polarity items, and the syntax-semantics interface, often bridging empirical Chinese data with universal linguistic theory. His methodological approach combines formal analysis with psycholinguistic insights, particularly in sentence processing and comprehension constraints. Analysis of his recent publications (2022-2025) reveals sustained focus on syntactic structures and semantic interpretation in Chinese, with recurring themes in quantification (especially the dou operator), anaphora resolution, and information-structural phenomena like cleft constructions and focus marking. His work consistently addresses theoretical puzzles at the syntax-semantics-pragmatics interface, demonstrating how Chinese data challenges and refines broader linguistic frameworks. His distinguished honors include: Changjiang Scholar-Chair Professor by China's Ministry of Education (2012) KC Wong Foundation Scholar (2010) Prof. PAN has held significant academic leadership roles including Associate Dean for Postgraduate Education and Research at City University of Hong Kong (2005-2010), President of the Linguistic Society of Hong Kong (2010-2011), and Executive Committee member of the International Association of Chinese Linguistics (2004-2006). He serves as a reviewer for premier journals including Language , Linguistic Inquiry , and Natural Language and Linguistic Theory , and has published two research monographs on Chinese reflexives and formal semantics while editing two volumes on Chinese linguistics and focus phenomena.

Muhammad Ali Gulzarمشاهده پروفایل

استادیار

• Software Engineering
• Automated Debugging
• Testing
• +۶ مورد دیگر

Muhammad Ali Gulzar is an Assistant Professor in the Department of Computer Science at Virginia Tech and an Amazon Scholar at Amazon Web Services. He holds a Ph.D. (2020) and B.S. (2014) in Computer Science from UCLA and Lahore University of Management Sciences, respectively. His research focuses on improving developer productivity through automated debugging and testing for emerging software domains, including data-intensive systems, machine learning applications, and computational notebooks. Education Ph.D., Computer Science, University of California, Los Angeles (2020) B.S., Computer Science, Lahore University of Management Sciences, Pakistan (2014) Research Interests Dr. Gulzar redesigns software productivity tools for emerging applications across three areas: (1) automated tracking-code localization in web applications, (2) re-engineering testing/debugging for data-intensive systems (e.g., Apache Spark), and (3) advancing testing/debugging in federated learning. His work includes projects like TraceFL for federated learning interpretability, NoT.JS for JavaScript tracking blocking, and MeanCache for LLM caching. Recent Contributions Recent papers address accessibility issues in ad-driven web pages (ICSE 2025), interpretability in federated learning (ICSE 2025), and notebook executability (MSR 2025). His team received the ACM CCS 2024 Distinguished Artifact Award for tracking JavaScript function analysis and a 2024-25 Amazon-VT Award for semantic caching research. Grants & Projects CCI-funded project on web ad transparency/accessibility engineering Amazon Scholar collaboration on productivity tools Student Contributions Recent advisees include Abdul Haddi Amjad (ad accessibility), Waris Gill (Federated Learning), and Tien Nguyen (notebook analysis). Students have contributed to industry-relevant tools like GitMeter for evidence-based hiring and DeSQL for SQL debugging.

• Empirical Legal Studies
• Law and Economics
• Law and Technology
• +۶ مورد دیگر

Jerrold SOH is an Assistant Professor of Law at the Yong Pung How School of Law, Singapore Management University (SMU), serving concurrently as Deputy Director of the Research Programme in Computational Law at the Centre for Digital Law. He holds an LL.M. from Harvard University and dual first-class honors degrees in Law (LL.B.) and Economics (B.Soc.Sci.) from the National University of Singapore (NUS). His academic journey includes roles as Deputy Director at the Centre for Computational Law (2021–2024) and Lecturer of Law at SMU (2018–2020). SOH’s research focuses on empirical legal studies, law and technology intersections, and computational methods in jurisprudence. He investigates topics such as judicial citation patterns, algorithmic accountability, AI-driven legal systems, and tort liability for automated vehicles. His work often bridges legal theory with data science, exemplified by projects like legal text formalization, network analysis of case law, and blockchain applications in property law. SOH has published widely in journals like the Asian Journal of Comparative Law , Frontiers in Physics , and American Business Law Journal , with recent work addressing AI legal implications, blockchain land transfers, and antitrust regulation. He is a Chief Data Scientist at Lex Quanta Pte Ltd and has received honors such as the SMU START Overseas Postgraduate Scholarship and multiple Dean’s Lists at NUS. His professional contributions span computational law infrastructure development, legal innovation advocacy, and educational initiatives in technology law. Current research priorities include AI ethics in legal contexts, control-centric liability frameworks, and empirical analyses of judicial decision-making processes.

• Programming Languages
• Functional Programming
• Type Systems
• +۵ مورد دیگر

Ningning Xie is an Assistant Professor in the Department of Computer Science at the University of Toronto. She holds a part-time Research Scientist position at Google DeepMind and is a Faculty Affiliate at the Schwartz Reisman Institute. Previously, she was a Research Associate at the University of Cambridge and earned her Ph.D. from the University of Hong Kong and B.S. from Zhejiang University. Her research focuses on foundational aspects of programming languages, including functional programming, type systems, logics, and their applications in broader domains. Key areas include algebraic effect handlers, staged compilation, type inference, and parallel computing. She has contributed to systems like MacoCaml and Perceus, and her work has been recognized with ACM SIGPLAN Distinguished Paper Awards and the Cambridge Hall of Fame Award. Dr. Xie co-chairs the Haskell Symposium 2025 and serves on committees for major programming language conferences (PLDI, ICFP, etc.). She actively organizes workshops and tutorials, including invited keynotes at Lambda Days and ZuriHac 2024. Her service roles include moderating the Types Forum and steering committees for Haskell and PLMW. Her academic contributions span over 25 peer-reviewed publications, with a focus on practical implementations and formal proofs. She advises students through her research group and emphasizes generative programming techniques in her teaching.

Apurva Gandhiمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Apurva Gandhi is a Researcher at Carnegie Mellon University , affiliated with the School of Computer Science and the Computer Science Department. Their research focuses on Artificial Intelligence with applications in program synthesis , agentic tasks , and handwritten content analysis . Research Interests : Artificial Intelligence Machine Learning Natural Language Processing Program Synthesis Publications highlight expertise in web agents , AI-driven database systems , deepfake detection , and sequence modeling for cybersecurity . Contact : apurvag@andrew.cmu.edu

Patrik Haslumمشاهده پروفایل

پژوهشگر

• AI Planning
• Plan Quality Optimization
• Optimization for Decision Support
• +۵ مورد دیگر

Roles and Affiliations : Patrik Haslum is a part-time Researcher in the AI group at the Research School of Computer Science (ANU College of Engineering and Computer Science), Australian National University. He is seconded to Data61's Decision Sciences program. Previously, he was at NICTA and Linköpings Universitet. Education : PhD in Computer Science from Linköpings Universitet (Sweden), with research on admissible heuristics for automated planning. Research Interests : Focuses on AI planning, particularly plan quality optimization and heuristic search. Specializes in optimal planning, domain analysis, and applying planning techniques to problems like genome edit distance, diagnosis, and robotics. His work bridges automated planning with Petri nets and discrete event systems. Advising & Students : Supervised four PhD students including Jing Cui (2018), Franc Ivankovic (2018), Fazlul Hasan Siddqui (2015), and Debdeep Banerjee (2015). Offers student projects in areas like story planning, optimal troubleshooting, and policy validation for MDPs. Labs & Contributions : Leads research in the AI group at ANU, contributing to tools like the INVAL plan validator and PDDL domain encodings. Active in international planning competitions and workshops.