جست‌وجوی استاد و پژوهشگر

Sabine Schulte im Waldeمشاهده پروفایل

دانشیار

• Computational Linguistics
• Natural Language Processing
• Lexical Semantics
• +۵ مورد دیگر

Prof. Sabine Schulte im Walde is an Associate Professor at the University of Stuttgart's Institute for Natural Language Processing. She holds affiliations with the International Max Planck Research School for Intelligent Systems (IMPRS-IS), ELLIS Society, and CLARIN-D. Her research focuses on computational modeling of lexical-semantic phenomena, including compositionality of noun compounds and particle verbs, abstract/concrete semantics, and diachronic language change. She has contributed to datasets on association norms for German compounds and led projects on multimodal semantic analysis. Research Interests: Her work bridges computational linguistics and cognitive science, emphasizing data-intensive methods. Key areas include semantic classification of verbs, metaphor detection, and evaluating semantic relations using distributional models. She explores how abstractness influences plausibility judgments and investigates semantic shifts in compounds over time. Awards: Nominated for AcademiaNet by the German Research Foundation (DFG). Active in professional societies including ACL, GSCL, and DGfS. Publications span over 50 peer-reviewed articles in venues like Computational Linguistics and ACL. Labs/Teams: Leads research on computational terminology and semantic change analysis at the Stuttgart Research Focus Language and Cognition (SRF). Collaborates internationally on projects like the DURel annotation tool for diachronic semantics.

• Natural Language Processing
• Computational Linguistics
• Language Models
• +۳ مورد دیگر

Kentaro Inui is a distinguished researcher at Tohoku University , specializing in Natural Language Processing , Computational Linguistics , and Machine Learning . His work focuses on advancing language model behavior through rigorous empirical analysis, including mechanisms for detokenization , entity identification , and numerical reasoning . Inui has pioneered methods to rectify spurious beliefs in LLMs via unlearning techniques and explored the dynamics of reasoning strategies in neural models. His research addresses chat translation quality through metrics like MQM-Chat and investigates repetition neurons responsible for text generation patterns. Inui also contributes to argumentation analysis with annotation frameworks like LPAttack and develops resources such as COPA-SSE for commonsense reasoning. His work on universal graph-based relation extraction and cross-stitching architectures has established new benchmarks in NLP task performance. Inui's publications span top-tier conferences including ACL , EMNLP , and LREC , often involving collaborations with researchers like Benjamin Heinzerling and Jun Suzuki. His methodological innovations in semi-structured explanation generation , position embedding (e.g., SHAPE), and zero pronoun resolution demonstrate his focus on both theoretical and practical NLP challenges. While no direct awards or student mentorship data appear in the provided corpus, his extensive publication record (over 20 papers between 2021-2025) underscores significant contributions to NLP education tools , knowledge base integration , and dialogue system consistency . Current projects like ReCall mechanisms and numerical property encoding directions highlight his ongoing impact on model interpretability and reasoning accuracy.

Dan Moldovanمشاهده پروفایل

استاد

• Natural Language Processing
• Artificial Intelligence
• Question Answering Systems
• +۸ مورد دیگر

Dan Moldovan is a Professor in the Department of Computer Science at The University of Texas at Dallas, within the Erik Jonsson School of Engineering and Computer Science. He leads the InterVoice Research Center in the Human Language Technology Research Institute and has played a pivotal role in advancing question answering technologies, achieving top performance in multiple TREC evaluations (TREC-8 to TREC-13). Education: Ph.D. in Electrical Engineering and Computer Science, Columbia University (1978) M.S. in Electrical Engineering and Computer Science, Columbia University (1974) Diploma Engineer in Electrical Engineering, Polytechnic Institute of Bucharest (1969) His research centers on Natural Language Processing and Artificial Intelligence , with major contributions in Question Answering Systems , Knowledge Acquisition from Text (KAT) , Word Sense Disambiguation , and Semantic Indexing and Retrieval . He has developed systems to enrich WordNet with domain knowledge and transform it into a logical knowledge base. His work also explores distributed and parallel processing for scalable NLP algorithms. The recent publications (2005–2007) highlight his focus on semantic reasoning, multilingual QA, validation of answers using logic provers like COGEX, and the semantics of noun compounds. These works reflect a strong trend toward deep semantic understanding, contextual reasoning, and integration of logic in NLP systems. Scientific Awards: Best performance in TREC-8 (1999), TREC-9 (2000), TREC-11 (2002), TREC-12 (2003), and TREC-13 (2004) QA competitions Dan Moldovan has advised numerous research projects and led major initiatives such as Extended WordNet and the development of PowerAnswer. He has secured significant research support through appointments and leadership roles across institutions. His work in distributed NLP and parallel processing of rule-based systems reflects a long-standing interest in scalable AI architectures. He has directed several key research labs: InterVoice Research Center, UTD Parallel and Distributed Computer Systems Laboratory, University of Southern California Parallel Knowledge Processing Laboratory, University of Southern California

Shuhao Fuمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Cognitive Science
• Relational Reasoning
• +۳ مورد دیگر

Shuhao Fu is a Program Postdoctoral Fellow at the Santa Fe Institute (SFI) researching the intersection of machine learning and cognitive science. He completed his Ph.D. in Psychology at UCLA under advisors Hongjing Lu and Ying Nian Wu, following a B.S. in Computer Science and Mathematics from Hong Kong University of Science and Technology. His research examines human-like relational reasoning in AI systems through cognitive modeling and computational approaches. Research focuses on: Bridging human-machine reasoning gaps via analogical mapping Developing explicit relational representations in vision models Structural cognitive modeling for compositional understanding Multimodal reasoning and scene interpretation Relational knowledge representation in biological and artificial systems Publication trends show concentrated work in computational cognitive science (2021-2025), with evolving focus from visual analogy fundamentals to applications in 3D recognition, social interaction modeling, and mental health diagnostics. Recent work demonstrates increased emphasis on transformer architectures, multimodal integration, and human-AI comparative studies. Professional experience includes research internships at Google X and Mineral.ai, with prior affiliation at Johns Hopkins University's CCVL lab under Alan Yuille. Currently serves as reviewer for ICML, ICCV, and Cognitive Science Society conferences.

• Adversarial Machine Learning
• Text Processing
• Machine Learning Algorithms
• +۳ مورد دیگر

Nura Aljaafari is a researcher in the Department of Computer Science, focusing on adversarial machine learning and text processing. Her work explores the robustness of machine learning models against adversarial attacks and defenses, particularly in federated learning and natural language processing contexts. Dr. Aljaafari holds a Doctor of Philosophy (Ph.D.) in Computer Science, providing expertise in advanced computing and machine learning methodologies. Her research interests center on adversarial machine learning, text processing, and enhancing the security of machine learning algorithms. Her recent studies include analyzing token compositionality in large language models and interpreting conceptual frameworks in GPT models, highlighting her focus on model interpretability and reliability. Earlier work includes investigating adversarial attacks in federated learning systems and developing defenses for license plate recognition systems. While her profile does not explicitly list awards or grants, her publications have garnered significant attention, with citations in cybersecurity and machine learning fields. Collaborations include developing bioinformatics tools using GANs and analyzing organizational security practices in Saudi Arabian contexts.

Shufang Zhuمشاهده پروفایل

مدرس

• Artificial Intelligence
• Formal Methods
• Automated Reasoning
• +۳ مورد دیگر

Dr. Shufang Zhu is a Lecturer (Assistant Professor equivalent) at the Department of Computer Science, University of Liverpool , and an Associate Member at the University of Oxford’s Department of Computer Science . Previously, she held roles including Senior Research Associate at Oxford (2023–2024) and Postdoctoral Researcher at Sapienza Università di Roma (2020–2022). She earned her Ph.D. in Software Engineering from East China Normal University (ECNU, 2020) under Prof. Geguang Pu, with a visiting Ph.D. at Rice University (2016–2018) under Prof. Moshe Y. Vardi. Education: B.Sc./Ph.D. in Software Engineering from ECNU (2010–2020). Scholarships include the Chinese Scholarship Council (CSC) and UT Austin EECS Rising Star (2022). Her research focuses on interdisciplinary areas of Formal Methods and Artificial Intelligence , emphasizing automated reasoning, planning, and synthesis. Key topics include temporal logics (LTL/LTLf), symbolic synthesis frameworks, and applications in reactive systems. Notable work addresses finite-trace specifications, best-effort strategies, and coordination in multi-agent systems. Teaching: Lecturer for Game-Theoretic Approach to Planning and Synthesis (European Summer School) and Foundations of Self-Programming Agents (Oxford). She also supervises funded Ph.D. positions, including a 2025 deadline for CSC-Liverpool scholarships. Awards: Future Digileader (Digital Futures, 2023), UT Austin EECS Rising Star (2022). Erdős number ≤3 via Moshe Y. Vardi. Collaborations: Co-chair of AAAI 2023 symposium on temporal logics in AI. Active in open-source tools like LydiaSyft for LTLf synthesis. Engages with academic networks through Google Scholar, DBLP, and GitHub.

Susagna Tubau Muntañaمشاهده پروفایل

دانشیار

• Theoretical Linguistics
• Syntax
• Negation Phenomena
• +۵ مورد دیگر

Susagna Tubau Muntaña is an Associate Professor at the Autonomous University of Barcelona (UAB), Department of English Philology and German Studies. She is part of the Center for Theoretical Linguistics and the Theoretical Linguistics Research Group funded by the Generalitat de Catalunya. Her academic roles include tenures as Associate Professor (2020–2023), Interim Associate Professor (2015–2020), and various teaching/research positions at UAB and other institutions since 2001. Education: PhD in English Philology (UAB, 2008) MA in Linguistics (University College London, 2004) MA in English Philology (UAB, 2003) Bachelor's in English Philology (UAB, 2001) Research Focus: Main interest: Theoretical linguistics, syntax, and negation phenomena (simple/double negation, negative agreement, negative quantifiers) Secondary areas: First/second language acquisition, the that-trace effect in English, gender expression in translated texts Key contributions: Studies on Catalan and English negative concord, experimental syntax, and language typology Grants & Projects: Principal Investigator (IP) of a funded project, plus member of 6 other projects and 2 thematic networks Active in projects like La interpretación de las categorías funcionales (2018–2021) and EXPLETIVITAD Y SIGNIFICADO EXPRESIVO (2024–2027) Awards & Recognition: Positive evaluations from CNEAI (National Commission for Research Activity) and AQU (Catalonia's Quality Agency) Speaker at 40+ linguistics conferences Reviewer for journals, La Caixa-British Council grants, and U.S. National Research Foundation projects Lab/Team Affiliation: Member of the consolidated Theoretical Linguistics Group funded by the Catalan government

Richard K. Larsonمشاهده پروفایل

استاد

• Formal Linguistics
• Syntax
• Semantics
• +۳ مورد دیگر

Richard K. Larson is a Distinguished Professor of Linguistics at Stony Brook University, specializing in syntax and semantics. He holds a Ph.D. from the University of Wisconsin-Madison (1983). His research focuses on syntactic structures, quantification, clausal complementation, and cross-linguistic phenomena in languages like Warlpiri, Japanese, Turkish, and Mandarin. He is recognized for pioneering the Grammar as Science Project , developing educational software Syntactica and Semantica , which earned him the 1998 EduCom Medal. Education: Ph.D. in Linguistics, University of Wisconsin-Madison, 1983 Research Interests: Larson’s work spans syntax-semantics interface, quantifier scope, NP adverbs, psych-verbs, and formal linguistic theory. He emphasizes scientific rigor in syntax, advocating for linguistics as an experimental science. Current projects include rethinking syntactic cartography and Ezafe constructions in Iranian languages. Awards: EduCom Medal (1998) MIT Graduate Council Teaching Award SUNY Chancellor’s Award for Excellence in Teaching Stony Brook Dean’s Award for Excellence in Graduate Teaching Advising & Grants: Larson has advised numerous graduate students and contributed to NSF-funded initiatives like the Accelerated College Education (ACE) program. His grants focus on computational linguistics tools and language education outreach. Key Contributions: Authored foundational textbooks including Grammar as Science (2010) and Knowledge of Meaning (1995). His work on AP-de adverbs in Mandarin and Ezafe construction has reshaped syntactic analysis. Active in promoting linguistics education at secondary/higher education levels through AP Linguistics initiatives.

Dilian Gurovمشاهده پروفایل

استاد

• Software Specification and Verification
• Multi-Agent Strategic Planning
• Formal Methods
• +۳ مورد دیگر

Dilian Gurov is a Professor in Computer Science at KTH Royal Institute of Technology, associated with the Digital Futures Faculty and the Division of Theoretical Computer Science. He also coordinates the Doctoral Programme in Computer Science at the CSC school. Before joining KTH in 2002, he earned a Ph.D. from the University of Victoria, Canada (1998), and worked at the Swedish Institute of Computer Science (1997-2002). His research focuses on software specification and verification, including contracts, program models, logics, and tools, as well as multi-agent strategic planning involving knowledge-based strategies in imperfect information settings. Key contributions include the CAV Distinguished Paper Award 2023 for 'Automatic Program Instrumentation for Automatic Verification' and an EASST award for 'Checking Absence of Illicit Applet Interactions: A Case Study' (2004). He leads projects funded by VR (SEFROS, ContraST) and Vinnova (AVerT2) and collaborates with industries like Scania on formal verification of C programs. His service roles span over 30 conference committees and organization roles, including PC memberships for iFM, TAP, and ISoLA. Teaching responsibilities include courses such as 'Formal Methods,' 'Program Semantics and Analysis,' and 'Knowledge in Games with Imperfect Information.' His work emphasizes practical applications of formal methods, bridging academic research with industry needs through collaborations and tool development (e.g., CVPP, ProMoVer, TriCo).

• Semantics
• Pragmatics
• Syntax
• +۲ مورد دیگر

Kyle Rawlins is a Professor in the Department of Cognitive Science at Johns Hopkins University (JHU), where he heads the Semantics Lab located in Krieger Hall 105. His research focuses on semantics, pragmatics, syntax, and their intersections, often collaborating with labs like the Van Durme Lab in Computer Science. The Semantics Lab facilitates weekly meetings for discussing research, structured as seminars or traditional lab sessions, and co-organizes projects such as the Decomp Project and MegaAttitude Project . Current lab members include PhD students Karl Mulligan and Natalia Talmina. Notable collaborators: Ilaria Frana (University of Enna), Barbara Landau (JHU), Ben Van Durme (JHU CS), and Aaron Steven White (Rochester). His research spans topics like: Questions Under Discussion (QUD) frameworks Evidentiality and bias in language Multimodal semantic parsing Decompositional semantics Pragmatic particles in Italian Recent publications analyze polar questions, neural network representations, and discourse particles. The lab maintains a mailing list for event announcements, emphasizing collaborative research in semantics and computational linguistics.

Amal Ahmedمشاهده پروفایل

استاد

• correct and secure compilation
• linking types for multi-language software
• typed compilation of dependent types
• +۱۲ مورد دیگر

Amal Ahmed is a Professor and Associate Dean for Graduate Programs at Khoury College of Computer Sciences, Northeastern University, USA. Her career spans over two decades, with a focus on correct and secure compilation , safe language interoperability , and semantic type systems . Research Interests: Her work addresses key challenges in Secure compilation across software-hardware stacks Design of sound foreign-function interfaces (FFIs) Typed compiler intermediate languages for multi-language systems Probabilistic and modal separation logic Gradual typing with parametricity Provenance and concurrency semantics Recent Publications highlight advancements in application binary interfaces , probabilistic logic , WebAssembly interoperability , and gradual typing . These works span POPL , ICFP , LICS , and PLDI , with collaborations across institutions like Cornell and UBC. Scientific Recognition: NSF CISE CAREER Workshop awardee (2016) Editorial Board, Journal of Functional Programming (2017–present) Editorial Board, Mathematical Structures in Computer Science (2016–present) Advising & Mentorship: She mentors PhD students like John Li (co-advised with Steven Holtzen) and Andrew Wagner, alongside postdocs and undergraduates. Alumni include Daniel Patterson (Assistant Teaching Professor at Northeastern), Max New (Assistant Professor at U. Michigan), and William Bowman (Assistant Professor at UBC). Professional Leadership: Active in program committees for POPL , OOPSLA , and LICS , she co-organizes workshops like Dagstuhl Seminars and chairs PLDI 2024 and POPL 2023 .

Joachim Kockمشاهده پروفایل

دانشیار

• Category theory
• Homotopy theory
• Combinatorics
• +۴ مورد دیگر

Joachim Kock is an Associate Professor at the Department of Mathematical Sciences, University of Copenhagen, with research focusing on category theory, homotopy theory, combinatorics, and algebraic geometry. His work explores intersections with probability theory, mathematical physics, and computer science, particularly through decomposition spaces, operads, and categorical structures. Education: Not explicitly mentioned External Employment: Professor Titular at Autonomous University of Barcelona Research Areas: Category theory and higher structures Homotopy-theoretic combinatorics Decomposition spaces and incidence algebras Applications in computer science and mathematical physics Recent Publications: 2024: ∞-operads as symmetric monoidal ∞-categories 2022: Tracelet Hopf Algebras and Decomposition Spaces 2022: Infinity-Operads as Analytic Monads 2021: Every 2-Segal space is unital 2021: Operadic categories and decalage Editorial Activities: Editor, Theory and Applications of Categories (since 2017) Editor, Higher Structures (2016–2022) Editor, Compositionality (since 2018)

• Semantics
• Pragmatics
• Syntax
• +۳ مورد دیگر

Aron Hirsch is a researcher and Assistant Professor specializing in Semantics & Pragmatics , with affiliations including the ERC project Realizing Leibniz’s Dream: Child Languages as a Mirror of the Mind (Research Area 4). His work bridges theoretical linguistics and cognitive modeling. Current Role: Assistant Professor (since August 2023) Past Role: Researcher in the ERC project on child language and semantics Research Interests Aron Hirsch investigates the syntax-semantics interface, particularly focus particles like 'only,' type disambiguation, and logical strength in language. His research explores how cognitive constraints shape linguistic structures and how pragmatic principles interact with formal semantics. Recent Publications Aron’s publications (2022–2024) focus on semantic operators, cumulativity in questions, and register variation. He collaborates with leading scholars such as Bernhard Schwarz and Itai Bassi , contributing to major venues like Proceedings of Semantics and Linguistic Theory (SALT) and Sinn und Bedeutung . Labs & Collaborations He works within the ERC project Realizing Leibniz’s Dream , focusing on child language as a window into the mind, and collaborates with international teams at institutions including University of Rochester and Universidad Nacional Autónoma de México .

Mathis Richterمشاهده پروفایل

پژوهشگر

• Higher cognition
• Concept representation
• Dynamic Field Theory
• +۹ مورد دیگر

Dr. Mathis Richter is a Postdoctoral Researcher at the Institute of Neuroinformatics (INI), part of the Faculty of Computer Science at Ruhr University Bochum, Germany. He has been affiliated with the INI since 2008, progressing from Research Assistant to Research Associate, and currently serves as a Postdoctoral Researcher since July 2018. At the INI, he contributes to both the Embodied Cognition group and the Autonomous Robotics group, led by Prof. Dr. Gregor Schöner. Dr. Richter earned his Dr.-Ing. (Ph.D. equivalent) in Engineering from Ruhr-Universität Bochum between 2011 and 2018, following an M.Sc. and B.Sc. in Applied Computer Science from the same institution. His academic journey includes an exchange year at the University of Birmingham, UK. His research centers on higher cognition, specifically concept representation, how concepts combine to form complex mental scenes, and the neural mechanisms organizing cognitive operations in time. Using Dynamic Field Theory as his primary framework, he develops mathematical models explaining how neural populations represent objects and concepts. His work demonstrates how these cognitive models connect to sensory-motor systems, often implemented on robotic platforms to validate their autonomy and functionality. Analysis of Dr. Richter's publications reveals a consistent focus on neural dynamic modeling of cognitive processes, with particular emphasis on spatial relations, language grounding, and embodied cognition. His research trajectory shows increasing sophistication in modeling complex cognitive phenomena while maintaining strong connections to robotic implementations. As an educator, Dr. Richter has taught Lab courses in Autonomous Robotics across multiple terms since Winter 2015/2016 and has delivered Lectures in Computational Neuroscience: Neural Dynamics since Winter 2018/2019. His teaching directly reflects his research expertise in neural dynamics and cognitive systems. Dr. Richter actively participates in interdisciplinary research that bridges cognitive science, neuroscience, computer science, and robotics, contributing to the INI's mission of understanding how organisms generate behavior and cognition through interaction with their environments.

R. Manmathaمشاهده پروفایل

استاد مدعو

• Computer Vision
• Information Retrieval
• Image and Video Retrieval
• +۸ مورد دیگر

R. Manmatha is an Adjunct Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst and a Principal Scientist at Amazon A9 since 2013. His academic journey includes a Ph.D. in Computer Science from University of Massachusetts Amherst (1997), an M.S. in Electrical Engineering from University of Hawaii (1986), and a B.Tech in Electrical Engineering from Indian Institute of Technology Kanpur (1983). Research Interests Manmatha's work spans Computer Vision , Information Retrieval , and Document Analysis . Key projects include: Developing Vision-Language Models for GUI grounding and OCR-free document understanding Creating Word Spotting techniques for historical manuscripts like George Washington's papers Advancing Image Retrieval through statistical and relevance models Building Meta Search systems using score distribution analysis Optimizing Diffusion Transformers for text-to-image generation Scientific Contributions His research has led to numerous publications in conferences like SIGIR , CVPR , and ICDAR , focusing on: Automatic Image Annotation using cross-media relevance models Scale Space Techniques for handwritten manuscript segmentation Alignment Methods for document-groundtruth generation Indian Language Document Search via locality-sensitive hashing Transformer-based architectures for multimodal and document tasks Advising & Collaborations Manmatha has mentored students including Jiwoon Jeon , Shaolei Feng , Toni Rath , Jamie Rothfeder , and Nitin Srimal . He co-founded Snaptell (acquired by Amazon) and contributed to Amazon's mobile search technology. Labs & Teams He leads the Multi-media Indexing and Retrieval (MIR) group at the Center for Intelligent Information Retrieval (CIIR) , focusing on non-textual information indexing through ASCII conversion and direct content analysis.