جست‌وجوی استاد و پژوهشگر

Sanjay Jainمشاهده پروفایل

استاد

• Inductive Inference
• Recursion Theory
• Complexity Theory
• +۳ مورد دیگر

Sanjay Jain is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). His research focuses on theoretical computer science with particular emphasis on inductive inference, recursion theory, complexity theory, and computational learning theory. Education: B.Tech. in Computer Science from Indian Institute of Technology Kharagpur, India (1986) M.S. in Computer Science from University of Rochester, USA (1988) Ph.D. in Computer Science from University of Rochester, USA (1990) Professor Jain's research spans multiple areas of theoretical computer science. His primary contributions are in computational learning theory, where he has made significant advances in understanding the intrinsic complexity of language identification and the limits of inductive inference. His work on recursion theory explores fundamental questions about computability and complexity, while his research in complexity theory addresses structural aspects of computational problems. A notable achievement was his work on "Deciding Parity Games in Quasipolynomial Time," which won the prestigious STOC 2017 best paper award and later the EATCS-IPEC Nerode Prize. Professor Jain's publication record shows a consistent focus on theoretical foundations of computer science, particularly in learning theory and computational complexity. His recent work has expanded into automatic structures, semiautomatic models, and connections between computational learning and algebraic structures. There is a clear progression from foundational work on language identification to more complex models involving automatic functions, transducers, and connections to mathematical logic. Scientific Awards: STOC 2017 Best Paper Award for "Deciding Parity Games in Quasipolynomial Time" EATCS-IPEC Nerode Prize (2021) Professor Jain has served on the editorial board of Information and Computation and has been actively involved in the academic community through program committee memberships for major conferences including COLT, ALT, LATA, TAMC, and PRICAI. He has held leadership roles as program co-chair for ALT 2000 and ALT 2013, and conference chair for ALT 2005. His work has been supported by various research grants, though specific details are not provided in the available materials. Professor Jain leads research in theoretical computer science at NUS, where he has built a strong research group focused on computational learning theory and related areas. His work often involves collaborations with researchers from around the world, particularly with Frank Stephan, with whom he has co-authored numerous papers. His research group has made significant contributions to understanding the fundamental limits and possibilities of computational learning models.

Roberto Giorgiمشاهده پروفایل

دانشیار

• Computer Architecture
• Multiprocessor Systems
• Multicore Architectures
• +۶ مورد دیگر

Roberto Giorgi is an Associate Professor of Computer Engineering at the Department of Information Engineering, University of Siena, Italy. He has held this position since October 1, 2006, following his tenure as an Assistant Professor since March 15, 1999. His educational background includes a Ph.D. in Computer Engineering from the University of Pisa (1999) with a thesis on coherence protocols for shared-memory multiprocessors, and an Electronic Engineering degree (1995) with a thesis on trace-driven performance evaluation of multiprocessors. Giorgi's primary research focuses on Computer Architecture , particularly on multiprocessor/multicore issues including processor design, coherence protocols, programmability, and energy efficiency. His work spans both theoretical and practical aspects of computer architecture, with emphasis on real-world implementations and educational tools. He has coordinated significant EU-funded projects including AXIOM (2014-2018) on Smart Cyber-Physical Systems and TERAFLUX (2009-2014) on Many-Cores. His recent publications (2022-2025) demonstrate a strong progression toward practical applications of computer architecture research, with particular emphasis on RISC-V architecture, FPGA-based acceleration, dataflow computing models (especially DF-Threads), and graph processing. Many of his papers address educational tools for computer architecture education, real-time object detection on embedded platforms, and novel execution paradigms for edge computing and HPC. IEEE Senior Member ACM Lifetime Member Coordinator of EU-funded AXIOM project (2014-2018) on Smart Cyber-Physical Systems Coordinator of EU-funded TERAFLUX project (2009-2014) on Many-Cores Giorgi has been actively involved in securing research funding and building collaborations, particularly in high-performance computer architecture research with emphasis on scalable architectures and embedded systems. He leads the Computer Architecture Lab (ROOM 223) at the University of Siena, which was established in 2007, and has been instrumental in developing practical implementations of architectural concepts including the AXIOM platform for cyber-physical systems.

Jamal Atifمشاهده پروفایل

استاد

• Artificial Intelligence
• Responsible AI
• Privacy Preservation in Machine Learning
• +۴ مورد دیگر

Jamal Atif is a Professor at Paris-Dauphine University and holds multiple significant leadership positions including Project Manager for 'Data Science and Artificial Intelligence' at the Institute of Information Sciences and their Interactions (INS2I) of the CNRS, Deputy Scientific Director of 3IA PRAIRIE, Head of the MILES team/project at LAMSADE (UMR CNRS-Université Paris-Dauphine), Co-leader of the Transverse Artificial Intelligence Program at PSL University, and Director of the Dauphine Numérique program. Professor Atif's primary research focuses on the foundations of responsible artificial intelligence, with specific expertise in privacy preservation in machine learning, robustness of deep learning algorithms to malicious attacks, causality, and explainability. His work bridges theoretical foundations with practical applications in security and reliability of AI systems. He has developed innovative approaches to address adversarial vulnerabilities in machine learning models and has made significant contributions to privacy-preserving techniques in data analysis. His publication record demonstrates a consistent focus on robust and trustworthy AI systems, with recent work exploring differential privacy in clustering, adversarial robustness, and explainable AI. The research spans theoretical foundations in logic and knowledge representation to practical applications in finance, healthcare, and computer vision. His publications appear in top-tier venues including Machine Learning journal, Neural Information Processing Systems, and International Joint Conferences on Artificial Intelligence. Scientific Awards: Recipient of two awards from the North American Society of Radiology for his thesis work Professor Atif has co-supervised or is currently supervising around fifteen doctoral students, demonstrating his commitment to mentoring the next generation of AI researchers. His leadership extends to directing major institutional programs including Dauphine Numérique and the Transverse Artificial Intelligence Program at PSL University, where he shapes strategic research directions in AI. He leads the MILES team/project at LAMSADE, which focuses on foundational aspects of machine learning and artificial intelligence. The team's research spans theoretical aspects of learning algorithms to practical applications requiring robust and reliable AI systems, with particular emphasis on security and privacy considerations in modern machine learning deployments.

Rohan Frenchمشاهده پروفایل

دانشیار

• Modal Logic
• Non-Classical Logic
• Proof Theory
• +۴ مورد دیگر

Rohan French is an Associate Professor in the Department of Philosophy at the University of California, Davis (UC Davis), where he has been employed since 2018. Previously, he was a post-doctoral researcher at the University of Groningen in the Netherlands. Education: Ph.D. in Philosophy, Monash University (2011) B.A. in Philosophy and Computer Science, Monash University (2006) Research Focus: French specializes in philosophical logic with emphasis on: Modal and non-classical logics Proof theory and semantic paradoxes Formal methods in philosophy Substructural approaches to logic Logic translation and expressivity Publications Overview: His scholarly output primarily explores technical aspects of logic systems, including model theory, dialogical frameworks, and paradox resolution. Recent works demonstrate consistent focus on valuational semantics, proof-theoretic structures, and applications of non-classical logics to philosophical problems. Collaborative research features prominently in his publication record.

Sam Cummingمشاهده پروفایل

استاد

• Philosophy of Language
• Semantics
• Reference Theory
• +۵ مورد دیگر

Sam Cumming is a Professor in the Department of Philosophy at the University of California, Los Angeles. His research spans philosophy of language, semantics, and the philosophical analysis of film and narrative structures. With a Ph.D. from Rutgers University (2007), he has established himself as a significant contributor to contemporary debates in linguistic reference, truth conditions, and nominalist approaches to semantics. Dr. Cumming's research interests focus on foundational questions in the philosophy of language, particularly concerning reference, truth, and meaning. His work examines how language connects to reality through semantic content, with special attention to problematic cases like fictional entities, indefinite descriptions, and reportative constructions. He has made notable contributions to understanding the semantics of film, exploring how cinematic techniques create coherent narrative viewpoints and convey meaning through visual representation. His interdisciplinary approach bridges analytic philosophy with cognitive science and film studies, revealing how linguistic structures parallel audiovisual cognition in storytelling. Analysis of Cumming's publication record reveals a consistent trajectory from formal semantic theory toward broader applications in narrative and film. His early work focused on technical aspects of reference and indefinites, while more recent publications demonstrate increasing engagement with moral philosophy in narrative contexts and the cognitive foundations of film perception. A unifying thread throughout his career is the examination of how meaning is constructed across different representational systems, whether linguistic or audiovisual. His articles frequently address the relationship between semantic content and cognitive processing, suggesting an underlying interest in how humans make sense of complex representational structures. Dr. Cumming actively mentors graduate students, as evidenced by his students Gabe, Rory, and Koby Leff who have presented research at academic conferences. His advising appears focused on the intersection of philosophy of language with film and narrative studies, guiding students through technically rigorous analyses of cinematic representation and narrative structure. While specific grant information isn't provided in the available materials, his sustained publication record in prestigious journals suggests successful research funding throughout his career.

Shira Elqayamمشاهده پروفایل

استاد

• Cognitive Psychology
• Cognitive Science
• Reasoning
• +۹ مورد دیگر

Shira Elqayam is Professor of Cognitive Psychology & Cognitive Science at De Montfort University, affiliated with the School of Applied Social Sciences within the Faculty of Health and Life Sciences. Her research critically examines the role of normativity in human reasoning and decision-making, advocating for a descriptivist approach over normativist frameworks. Her research interests center on higher cognitive processes, particularly reasoning, decision-making, rationality, dual-process theories, disjunctive thinking, and the linguistic aspects of inference. A major focus is the critique of normativism—the idea that human cognition should be judged against normative standards—highlighting methodological flaws such as the 'is-ought' inference. Her empirical work explores how people infer normative conclusions from descriptive premises, influenced by causal links and outcome valuations. Shira Elqayam’s recent publications reveal a strong focus on the interplay between logic, probability, and human judgment. Her work spans conditional reasoning, moral cognition, clinical decision-making, and the psychology of rationality. Trends in her research include challenging normative models in psychology, developing alternative theories like Grounded Rationality, and exploring the mechanisms behind inferential connections in conditionals. Keynote speaker at the Sixth Annual Meeting of the New Frameworks of Rationality Program (2017) Associate Editor, Frontiers in Psychology: Cognitive Science and Theoretical and Philosophical Psychology Guest editor for special issues in Thinking & Reasoning and Frontiers in Cognitive Science Regular and ad hoc reviewer for leading journals including Cognition , Behavioral and Brain Sciences , and Synthese She has secured significant research funding, including a Leverhulme Trust grant on the generative capacity of norms and grants from the Experimental Psychology Society and EURO-XPRAG. She supervises PhD students, including Ashleigh Jeffries, and collaborates with prominent scholars such as David Over, Jonathan Evans, and Valerie Thompson. She has organized international workshops and convened symposia at major conferences, contributing actively to the global academic community in cognitive science and psychology.

Constantinos Daskalakisمشاهده پروفایل

استاد

• Theory of Computation
• Game Theory
• Economics
• +۳ مورد دیگر

Constantinos Daskalakis is the Avanessians Professor of Computer Science at MIT's Electrical Engineering and Computer Science department within the Schwarzman College of Computing. He is a member of CSAIL (Computer Science and Artificial Intelligence Laboratory) and affiliated with LIDS (Laboratory for Information and Decision Systems) and ORC (Operations Research Center). Additionally, he serves as an investigator in the NSF-funded Foundations of Data Science Institute and is a co-founder and chief scientist of the Archimedes AI research center. Dr. Daskalakis holds a diploma in electrical and computer engineering from the National Technical University of Athens and earned his PhD in computer science from UC Berkeley under advisor Christos H. Papadimitriou. His doctoral thesis focused on "On the Existence of Pure Nash Equilibria in Graphical Games with succinct description." His research spans the intersection of theoretical computer science with economics, game theory, machine learning, statistics, and probability theory. Daskalakis has made fundamental contributions to understanding the computational complexity of Nash equilibrium, the mathematical structure of multi-item auctions, and the behavior of machine learning algorithms like expectation-maximization. His work includes developing computationally efficient methods for statistical hypothesis testing and learning in high-dimensional settings, as well as characterizing the structure of high-dimensional distributions. His extensive publication record demonstrates a consistent focus on the theoretical foundations of computation and its applications to economic and learning systems. His recent work shows increasing integration of game theory with machine learning, particularly in areas like generative models, equilibrium computation, and mechanism design. The breadth of his publications across top venues in computer science, economics, and machine learning reflects the interdisciplinary nature of his research. 2007 Microsoft Graduate Research Fellowship 2008 ACM Doctoral Dissertation Award Game Theory and Computer Science (Kalai) Prize from the Game Theory Society 2010 Sloan Fellowship in Computer Science 2011 SIAM Outstanding Paper Prize 2011 Ruth and Joel Spira Award for Distinguished Teaching 2012 Microsoft Research Faculty Fellowship 2015 Research and Development Award by Giuseppe Sciacca Foundation 2017 Google Faculty Research Award 2018 Simons Investigator Award 2018 Rolf Nevanlinna Prize from the International Mathematical Union Best Paper awards at ACM Conference on Economics and Computation (2006, 2013) FOCS 2022 Test of Time Award Daskalakis has advised numerous PhD students and has been involved in organizing major academic programs including the Causality program at the Simons Institute (Spring 2022). His research group focuses on theoretical aspects of computation with applications to economic systems and machine learning. Current work explores connections between generative models, game theory, and statistical learning, with applications to mechanism design and econometrics.

Jonni Virtemaمشاهده پروفایل

مدرس

• finite model theory
• logic in computer science
• logics for dependence and independence
• +۶ مورد دیگر

Dr. Jonni Virtema is a Lecturer in Verification at the School of Computer Science, University of Sheffield, UK, where he has been employed since September 2021. He also serves as the Study Abroad/International Student Exchange Officer for the department. His research is centered within the Foundations of Computation research group, focusing on the theoretical aspects of computer science with particular emphasis on logic and verification. Dr. Virtema earned his MSc (2008) and PhD (2014) in mathematics from the University of Tampere, Finland. In 2020, he was awarded the title of Docent in Mathematical Logic from the University of Helsinki, Finland. Prior to joining the University of Sheffield, he held various research positions funded by prestigious organizations including the German Research Foundation (DFG), the Japan Society for the Promotion of Science (JSPS), the Research Foundation - Flanders (FWO), and the Academy of Finland (AKA). Dr. Virtema's research interests originate from finite model theory and logic in computer science, with specific focus areas including logics for dependence and independence, modal logics, logics for verification, logical foundations of neural networks, logical foundations of quantum information theory, computational complexity, and logics with team semantics. His work bridges theoretical computer science with practical applications in database theory, verification, and artificial intelligence. Recent publications demonstrate his expanding interest in the intersection of logic with neural networks and quantum information. Dr. Virtema has published extensively with 16 journal articles and 40 conference articles, accumulating 791 citations with an h-index of 18 according to Google Scholar. His recent work spans temporal logics, probabilistic team semantics, database repair mechanisms, and neural network theory, showing a clear trajectory toward interdisciplinary research connecting formal methods with emerging technologies. Program Committee Member for KR 2025, NeurIPS 2025, ICML 2025, ICLR 2025 Organizer of Dagstuhl Seminar on Logics for Dependence and Independence (2024) Local Chair for FoIKS 2024 in Sheffield Principal Investigator for DFG project LogQMC (2020-2024) Dr. Virtema maintains an active research presence through international collaborations and has delivered 44 conference talks and 21 seminar presentations worldwide. His work on graph neural networks and arithmetic circuits accepted to NeurIPS 2024 exemplifies his current research direction exploring the logical foundations of machine learning systems.

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +۷ مورد دیگر

Prof. Dr. Mario Fritz is a Professor at Saarland University and faculty member at CISPA Helmholtz Center for Information Security. He serves as a Fellow at the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on Trustworthy Information Processing at the intersection of AI & Machine Learning with Security & Privacy. Mario Fritz leads numerous significant research initiatives including the European Large Open Multi-Modal Foundation Models for Robust Generalization (ELLIOT), European Lighthouse on Secure and Safe AI (ELSA), and multiple projects on privacy-preserving AI applications in healthcare. His work spans security and privacy aspects of large language models, foundation models, and medical AI applications. He has established himself as a leading researcher in trustworthy AI through his extensive publication record and leadership in major collaborative projects. His recent research (2025 publications) demonstrates a strong focus on the security and safety challenges of large language models, including model stealing attacks, causal reasoning capabilities, sampling methods, and privacy risks. His work bridges theoretical foundations with practical applications across multiple domains, particularly in healthcare and cybersecurity. Mario Fritz actively mentors PhD students and Post-Docs, seeking new researchers to join his group. He has been involved in numerous grants and collaborative projects, including those funded by BMBF and the Helmholtz Association, demonstrating his ability to secure substantial research funding and lead large interdisciplinary teams.

Marcelo Barra Ferreiraمشاهده پروفایل

دانشیار

• Semantics
• Pragmatics
• Computational Linguistics
• +۲ مورد دیگر

Marcelo Barra Ferreira is an Associate Professor in the Department of Linguistics at the University of São Paulo (USP), with a tenured position. He specializes in Semantics, Pragmatics, and Computational Linguistics. His research focuses on Indo-European languages, formal semantic analysis, and computational processing of natural language. Ferreira coordinates the postgraduate program in Linguistics at USP (2022–2026) and holds a CNPq 1D Research Productivity Scholarship, recognizing his contributions to academic research. He has a PhD in Linguistics from MIT (2005), preceded by a Master’s (2000) and Bachelor’s (1997) in Linguistics from the State University of Campinas (UNICAMP). His academic trajectory includes postdoctoral fellowships at USP (2008) and the University of Maryland (2015). Ferreira’s research explores topics like temporal semantics, modality, aspect, and computational linguistics. He co-leads the Grupo de Linguística Computacional (GLIC) and has authored influential textbooks on formal semantics and computational linguistics. His publications span theoretical linguistics, computational models, and Portuguese language analysis. Key contributions include studies on imperfectivity, necessity modals in Portuguese, and the semantics of determiner phrases. His work bridges formal theory with practical applications in computational linguistics, emphasizing cross-disciplinary collaboration.

Whitney Gegg-Harrisonمشاهده پروفایل

دانشیار

• Cognitive Science
• Linguistics
• Writing Pedagogy
• +۳ مورد دیگر

Whitney Gegg-Harrison is an Associate Professor in the Writing, Speaking, and Argument Program at the University of Rochester. Her work bridges cognitive science, linguistics, and writing pedagogy, emphasizing how language reflects and shapes thought. She holds a PhD in Brain and Cognitive Sciences from the University of Rochester (2014), with earlier degrees from The Ohio State University (BS in Linguistics/Computer Science and MS in Computational Linguistics). Her teaching spans foundational first-year writing courses exploring language and cognition to advanced seminars on AI and writing. Notable courses include Language as a Window into the Mind (since 2010) and Writing about and with Artificial Intelligence (launched 2023). She designs curricula that integrate critical AI literacy and cognitive science principles. Research interests include cognitive processes in writing, AI's impact on communication, and inclusive pedagogy. She has published widely on reference resolution, discourse processing, and flow in writing. Her 2024 article A Multidisciplinary Exploration into Flow in Writing examines how cognitive states influence writing productivity. In 2023, she received the prestigious Goergen Award for Excellence in Undergraduate Teaching. She is a sought-after speaker, including a 2024 invited seminar at Smith College on generative AI and writing. Her work appears in venues like Taylor and Francis and TextGenEd’s open-access resources. Gegg-Harrison collaborates with faculty across disciplines, offering workshops on AI-informed writing pedagogy and feedback strategies. Her office is in Rush Rhees Library (G121-H), and she emphasizes accessibility and student-centered learning.

Florin Silviu Maneaمشاهده پروفایل

استاد

• String Algorithms and Combinatorics
• String Solving
• Efficient Algorithms and Data Structures
• +۶ مورد دیگر

Florin Silviu Manea is a Professor for Theoretical Computer Science at the Institute of Computer Science, University of Göttingen, Germany. He has held this W3-Professor position since 2022, funded by the Heisenberg programme of the DFG. Prior to this, he was a W2-Professor for Fundamentals of Computer Science at the same university (2019-2022). His academic career includes research positions at Kiel University (2011-2019) and an Alexander von Humboldt fellowship at the University of Magdeburg (2009-2011). Dr. Manea received his PhD in December 2007 from the University of Bucharest with the distinction Summa cum Laude. His PhD thesis was titled "Networks of bio-processors" and was supervised by Victor Mitrana. He also earned a Master of Science (2005) and Bachelor of Science in Computer Science (2003) from the University of Bucharest, both with perfect GPA scores of 10/10. Professor Manea's research focuses on the theoretical foundations of computer science, with particular emphasis on string algorithms and combinatorics. His work explores the intricate relationships between formal language theory, automata theory, and practical applications in string solving. He has made significant contributions to understanding pattern matching with variables, combinatorial properties of strings, and the computational aspects of word equations. His research bridges theoretical concepts with practical applications in areas like bioinformatics and programming language theory. Analysis of Professor Manea's recent publications reveals a strong focus on string algorithms, particularly in the areas of pattern matching, word equations, and combinatorics on words. His work often explores the computational complexity of string problems while developing efficient algorithms to solve them. A recurring theme is the investigation of repetitions, palindromes, and gapped structures in strings, with applications ranging from DNA sequence analysis to programming language design. His research demonstrates a consistent pattern of advancing both the theoretical understanding and practical applications of string algorithms. Professor Manea has received several prestigious awards for his contributions to computer science: Lehrpreis 2020 (Teaching Award) by CS-students from Göttingen The "Tudor Tanasescu" Prize of the Romanian Academy (2009) Honorable Mention at ACM International Collegiate Programming Contest World Finals (2004, 2007) As an advisor, Professor Manea has successfully supervised multiple PhD students to completion with highest honors, including Maria Kosche (2023), Stefan Siemer (2024), and Tore Koß (2024), all achieving Summa cum Laude distinctions. He currently leads a research group focused on theoretical computer science at the University of Göttingen. His research is supported by significant funding, including a DFG grant for "String Constraint Solving: Combinatorial, Algorithmic, and Language-Theoretic Approaches" and continued Heisenberg-programme funding until 2027 for his project "Combinatorial String Solving." Professor Manea leads the Theoretical Computer Science research group at the University of Göttingen, which focuses on string algorithms, combinatorics, and computational models. His group actively collaborates with researchers worldwide and has organized several major conferences including DLT 2024, NCMA 2024, and CSL 2022. The group offers supervision for BSc and MSc theses on both theoretical and applied topics related to their research areas.

David Dubinمشاهده پروفایل

دانشیار

• Foundations of Information
• Information Representation
• Document Encoding
• +۴ مورد دیگر

David Dubin serves as a Teaching Associate Professor at the University of Illinois School of Information Sciences (iSchool), where he teaches courses in information processing, modeling, and analysis. His office is located in room 330 of the LIS Building at 501 E. Daniel Street, Champaign, IL, with contact via (217) 244-3275 or ddubin@illinois.edu. Education : PhD in Information Science, University of Pittsburgh Research Focus : Dubin's work centers on foundational aspects of information representation and description, particularly expression and encoding mechanisms in documents and digital resources. His expertise spans data curation, digital humanities, information retrieval, and knowledge organization, with significant contributions to document identity theory, markup semantics, and text encoding standards for humanities computing. Publication Trends : Analysis of his scholarly output reveals consistent engagement with digital humanities methodologies, especially TEI-based text encoding for fragmentary classical works and ontological frameworks for game studies. His research demonstrates recurring emphasis on the interplay between content, format, and interpretation across scientific data representation, digital library systems, and semantic modeling of information objects. Teaching Activities : Currently instructing Social History of Games & Gaming (IS142A), Independent Study (IS389DSD), and Decision Analysis and Modeling (IS390DAM) for Fall 2025. Office hours are conducted by appointment through direct contact.

Patrícia Amaralمشاهده پروفایل

استاد

• Syntax-Semantics Interface
• Historical Linguistics
• Lexical Semantics
• +۷ مورد دیگر

Patrícia Amaral is a Professor at the Department of Spanish and Portuguese within the College of Arts & Sciences at Indiana University Bloomington. She holds an adjunct position in Linguistics and has been actively researching the syntax-semantics interface, historical linguistics, and experimental pragmatics. Education: Ph.D. in Hispanic Linguistics from Ohio State University (2007) M.A. in Linguistics from University of Coimbra (1999) B.A. in Classical Languages from University of Coimbra (1996) Her research systematically explores how lexical, contextual, and pragmatic factors influence interpretation, with a focus on inferential mechanisms in semantic change. She has contributed extensively to understanding syntactic and semantic evolution in Ibero-Romance languages, particularly Portuguese and Spanish, and has conducted in-depth studies on Barranquenho, a mixed language from the Portuguese-Spanish border region. Methodologically, she combines corpus analysis with experimental techniques. The most recent articles reveal a concentration on semantic change dynamics, distributional methods in historical linguistics, adversative connectives, and pragmatic markers. Her work spans from theoretical frameworks to computational approaches, often bridging diachronic and synchronic analysis. Affiliations: Cognitive Science Program Institute for European Studies

Roni Katzirمشاهده پروفایل

دانشیار

• Linguistics
• Computational Linguistics
• Cognitive Science
• +۴ مورد دیگر

Prof. Roni Katzir is an Associate Professor in the Department of Linguistics and a member of the Sagol School of Neuroscience at Tel Aviv University. His research focuses on the intersection of mathematical/computational methods and linguistic cognition, investigating how humans represent, learn, and use language knowledge for inference and discourse. He holds a BSc in Mathematics from Tel Aviv University and a PhD in Linguistics from MIT. Education: BSc in Mathematics, Tel Aviv University PhD in Linguistics, Massachusetts Institute of Technology (MIT) His key research areas include computational linguistics, cognitive science, and formal semantics. Notable contributions address the computational modeling of grammar induction, the evaluation of large language models against human linguistic cognition, and the application of Minimum Description Length principles in neural networks. He leads the Computational Linguistics Lab and undergraduate program at TAU and teaches in the Adi Lautman Interdisciplinary Program for Outstanding Students. Recent work critically examines Large Language Models (LLMs), arguing they fail to replicate core aspects of human linguistic competence. His research also explores neural network generalization for grammar induction and the typological stability of logical operators. Prof. Katzir has advised numerous collaborative projects and leads initiatives in computational phonology and semantics. His labs focus on explanatory adequacy in language learning and neurosymbolic AI integration.