Azita Hojatollah Taleghani is an Associate Professor in the Teaching Stream of Linguistics at Language Studies, University of Toronto. She focuses on Persian language, literature, and linguistics, with cross-appointments in the Department of Near & Middle Eastern Civilizations. Education: PhD, Linguistics, University of Arizona MA, Linguistics, University of Arizona MA, General Linguistics, Tehran University BA, English Language and Translation, Tehran University Her research spans second-language and heritage speakers' pedagogy, Persian syntax/morphology, stylistic analysis of Persian women poets, and digital language teaching. Her publications explore theoretical linguistics, Persian second language acquisition, and the intersection of poetic techniques with linguistic processes. Key trends in her work include generative approaches to Persian tense structures, the role of archaism in poetry, and comparative studies of linguistic modules. She has contributed extensively to Persian syntax, aspect, and pedagogical frameworks.
Minos Garofalakis is a Professor at the School of Electronic & Computer Engineering at the Technical University of Crete, specializing in data stream management, complex event processing, and privacy-preserving analytics. His work bridges theoretical and applied computer science, with a focus on scalable algorithms for high-velocity data. Best Paper Award at VLDB 2024 for 'OmniSketch' Leader in sketch-based and distributed stream processing Pioneer in differential privacy for relational data Research interests span stream analytics , probabilistic databases , and interactive query systems . Recent work includes oblivious parallel joins (2025), relational data synthesis under privacy constraints (2024), and cross-platform analytics frameworks (2020). His publications demonstrate a consistent focus on error-controlled approximations and real-time distributed processing. Scientific contributions have been recognized at premier conferences like VLDB, with awards highlighting innovations in multi-dimensional stream analysis and privacy-preserving operations . Collaborations span academia and industry, particularly in bioinformatics and distributed systems.
Henri Hansen is a University Lecturer at Tampere University's Computing Sciences Department within the Faculty of Information Technology and Communication Sciences. His research focuses on concurrency theory, partial order reduction, stubborn sets, Petri nets, and formal methods. He holds a Doctor of Science (Technology) and Master of Science in Technology from Tampere University. Key research interests include optimizing state space exploration through techniques like stubborn sets, analyzing financial networks (e.g., stock market dynamics), and applying formal methods to industrial systems. His work bridges theoretical foundations with practical applications in software verification and blockchain systems. Recent publications emphasize network analysis in financial markets and Bitcoin systems, alongside advancements in partial order reduction algorithms. Hansen has received three notable awards for his contributions to stubborn set theory and coverability algorithms.
Victoria Mateu is an Associate Professor of Hispanic Linguistics at the University of California, Los Angeles (UCLA), Department of Spanish and Portuguese, where she joined in 2019 after completing her Ph.D. in Linguistics at UCLA and serving as Lecturer in Linguistics and Lab Manager of the UCLA Language Lab. Her educational background includes: Ph.D. in Linguistics, University of California Los Angeles (2016) M.A. in Linguistics, University of California Los Angeles (2013) B.A. in English Philology, Universidad de Granada, Spain (2011) Dr. Mateu's research employs experimental methodologies to investigate language representation across populations, with core focus on Spanish acquisition in children and adults. Her work examines morphosyntactic constraints, crosslinguistic differences between Spanish/English, language processing mechanisms, and word segmentation in monolingual/bilingual infants. She explores how developmental paths reveal underlying grammatical structures through both naturalistic and experimental paradigms. Recent publications demonstrate strong trends in intervention effects across syntactic domains (passives, sluicing, wh-questions) with expanding cross-linguistic scope (Mandarin, Italian) and methodological innovation through large-scale collaborations. Her work bridges theoretical syntax with developmental psycholinguistics, emphasizing experimental rigor in child language research. Her scientific recognition includes: UCLA Social Impact Collaborative Seed Grant ($50,000) for ‘A community-centered approach to supporting dual language learning’ Dr. Mateu actively mentors graduate students as evidenced by co-authored publications with emerging scholars. Her current grant-funded project with Megha Sundara and Laurel Perkins develops community-centered approaches to dual language support, reflecting commitment to applied linguistic research. She serves as course instructor for advanced syntax and language acquisition seminars. As former Lab Manager of the UCLA Language Lab and current contributor to the international ManyBabies Consortium, she participates in large-scale initiatives addressing methodological challenges in infant research through multi-lab collaborations.
Sebastian Fedden is Professor of General Linguistics at Sorbonne Nouvelle University, with additional teaching engagements at Ludwig-Maximilians-Universität München (2022-24). His administrative responsibilities include membership in the Conseil de Gestion (ILPGA), representation of LACITO at the Doctoral College, editorship of LACITO Publications, and coordination of research axes in the Labex-EFL project on grammatical typology. Fedden's research explores linguistic diversity through: Core frameworks: Canonical typology and language documentation Regional expertise: Papuan languages (Mian, Telefol, Tifal, Kibiri) Theoretical foci: Nominal classification systems (gender/classifiers), agreement phenomena, argument realization Interdisciplinary connections: Cognition-categorization interfaces, psycholinguistic validation His recent publications (2020-2022) demonstrate methodological diversity—combining discourse analysis, computational modeling, and diachronic approaches—to examine grammatical systems in Papuan languages, particularly agreement mechanics in Mian and grammaticalization pathways in Trans New Guinea. Fedden actively supervises doctoral candidates researching endangered languages: Moisés A. Veláquez (Kibiri grammar) and Neige Rochant (Baga Pukur grammar). He secures significant research funding including the ANR-DFG binational project Complex Predicates in Languages: Emergence, Typology, Evolution (2021-24) and ESRC UK Grant Optimal categorisation (2018-22). He coordinates research networks through LACITO and the Surrey Morphology Group, and organizes major linguistics events including DGfS workshops and the Current Trends in Papuan Linguistics conference.
James Walsh is an Assistant Professor of Philosophy at New York University, specializing in mathematical logic. His research focuses on proof theory, reflection principles, and incompleteness theorems, with applications to foundational mathematics. He received the Sacks Prize (2020) for his dissertation on proof theory and ordinal analysis. His research bridges mathematical logic, proof theory, and theoretical computer science, with recent publications exploring reflection principles, ordinal analysis, and connections between truth theories and modal logic. Walsh has developed novel approaches to incompleteness phenomena and the classification of formal theories. His interdisciplinary work includes collaborations with physicists applying machine learning to thermospheric density modeling. Before joining NYU, Walsh was a Klarman Postdoctoral Fellow at Cornell University and received his DPhil from UC Berkeley.
Arthur Charguéraud is a senior researcher (Directeur de Recherche) at Inria, based in Strasbourg within the Camus team, affiliated with the iCube laboratory at Université de Strasbourg. His research spans program verification, program optimization, and mechanized semantics of programming languages, with a strong focus on separation logic and interactive theorem proving using Coq. Affiliation: Inria, Camus team, iCube Laboratory, Université de Strasbourg Position: Senior Researcher (Directeur de Recherche) Research Focus: Formal verification, separation logic, source-to-source transformations, high-performance computing His research interests center on developing formal methods to ensure correctness and efficiency in software systems. He works extensively on separation logic to verify both time and space complexity of programs, especially in the presence of garbage collection. His work bridges theoretical foundations with practical tools, such as the CFML framework and the OptiTrust optimization framework, which enables trustworthy source-to-source transformations with formal guarantees. His publications reveal a consistent focus on interactive verification, formal semantics, and performance optimization. Key themes include granularity control in parallelism, mechanized semantics (e.g., for JavaScript), and verified compilation. He has made significant contributions to separation logic, including extensions for time and space credits, big-O reasoning, and higher-order representation predicates. Arthur Charguéraud has received notable recognition for his work, including: Distinguished Paper Award at CPP 2022 SIGPLAN Research Highlight at PPoPP 2019 He has advised several PhD students and postdoctoral researchers, including Guillaume Bertholon, Alexandre Moine, and Armaël Guéneau. He leads the ANR-funded OptiTrust project (2022–2027), which aims to build a framework for verified source-to-source optimizations. He has also been involved in other major projects such as ANR VOCAL, ANR AJACS, and ERC DeepSea. His work is supported by both national (ANR, Inria) and institutional (CEA, ENS) grants. He is actively involved in the programming languages research community, serving on the program committees of top conferences including POPL, ICFP, PLDI, CPP, and CoqPL, and has chaired several workshops. He is also engaged in education and outreach, co-authoring the book Separation Logic Foundations in the Software Foundations series and designing challenges for the Concours Castor Informatique to promote computer science among young students.
Zachary Kincaid is an Associate Professor in the Department of Computer Science at Princeton University. His research focuses on program analysis , logic , and programming languages , with emphasis on making analysis compositional and robust . PhD, University of Toronto (2016) BSc, Western University Research Interests Dr. Kincaid develops algebraic program analysis frameworks combining symbolic methods with abstract interpretation. His work addresses challenges in: Compositional analysis of concurrent and recursive programs Termination analysis for loops with complex control flow Non-linear numerical invariant generation Strategy synthesis for logical games Parameterized program verification Publication Trends His research output spans program analysis (2024-2010), formal verification (2018-2010), concurrency (2016-2010), and automated synthesis (2013-2012). Recent work (2024) explores polynomial ideals and nonlinear ranking functions , while foundational contributions include vector addition systems and recurrence-based invariants . Scientific Engagement Dr. Kincaid contributes to the academic community through: Program Committee service (PLDI, POPL, CAV, IJCAI, LICS, FMCAD, ESOP, etc.) Co-developing the Duet analyzer for unbounded concurrency Collaborative work with leading researchers (Tom Reps, Azadeh Farzan, Jason Breck) Advising & Grants He advises PhD students and leads research funded by the ONR grant N00014-19-1-2318 . Current advisees include Jake Silverman and Shaowei Zhu, while former student Charlie Murphy (PhD 2023) now holds a postdoctoral position at University of Wisconsin-Madison. Labs & Teams Dr. Kincaid co-developed the Duet program analyzer and contributes to tools like Srk and SimSat . His work integrates SMT solvers (MathSAT, Z3) and mathematical frameworks (rational vector addition systems, recurrence relations) for robust program analysis.
Manuel Otero is an Associate Professor in the Department of English at Eastern Connecticut State University. He specializes in historical linguistics and the documentation of endangered languages, particularly focusing on languages spoken by marginalized communities in western Ethiopia and Sudanese refugees in the U.S. Dr. Otero earned his PhD in Linguistics from the University of Oregon. His research emphasizes the phonology, morphology, and syntax of Ethiopian Komo, with a focus on vowel harmony systems, directional verb morphology, and historical reconstruction of the Koman language family. He also explores typological aspects of Chacoan languages like Nivaĉle and Pilagá. His publications span acoustic phonetics, morphosyntactic analysis, and language documentation. Recent work includes studies on associated motion, deictic direction, and exchoative aspect in Koman languages. His teaching focuses on introductory linguistics and writing courses, aiming to highlight the beauty and complexity of human language. Research grants and lab affiliations are not explicitly mentioned, but his work directly engages with community-based language preservation efforts. He advises no listed students but actively contributes to endangered language documentation through fieldwork and academic collaborations.
Minos Garofalakis is a Professor of Computer Science at the School of Electrical and Computer Engineering (ECE) of the Technical University of Crete (TUC), where he directs the Software Technology and Network Applications Laboratory (SoftNet). He is also the Director of the Information Management Systems Institute (IMSI) at the Athena Research and Innovation Centre in Athens. Previously, he held roles at Yahoo! Research, Intel Research Berkeley, and Bell Laboratories, and was an Adjunct Associate Professor at UC Berkeley. Education: He earned a BSc in Computer Engineering from the University of Patras (1992), followed by MSc (1994) and PhD (1998) in Computer Science from the University of Wisconsin-Madison. Research Interests: His work focuses on Big Data analytics , including database systems, data streams, approximate query processing, probabilistic databases, and secure/private data analytics. Key areas include distributed stream processing, data synopses, and machine learning applications. He has authored over 150 papers and holds 29 patents, with an h-index of 63 and 13,500+ citations. Recent Work Trends: His recent articles emphasize scalable stream analytics (e.g., OmniSketch), privacy-preserving techniques, and distributed event processing. He explores challenges in handling high-velocity data streams, uncertainty in databases, and real-world applications like healthcare analytics. Scientific Awards: ACM Fellow (2018), IEEE Fellow (2017), TUC Excellence Award (2015), and multiple patents from Bell Labs/Yahoo/AT&T. Advising & Grants: He led EU projects such as FERARI, LEADS, and The Human Brain Project. His lab, SoftNet, develops tools for extreme-scale analytics and declarative networking. Current work includes interactive cross-platform analytics (Infore) and AI-driven medical data systems. Labs/Teams: Director of SoftNet Lab and IMSI. Collaborates with industry partners on distributed systems and privacy-preserving technologies.
Dušanka Zvekić-Dušanović is a full professor at the Department of Serbian Language and Linguistics , Faculty of Philosophy , University of Novi Sad . She holds a PhD in humanities-philology and has dedicated her career to the study of Serbian-Hungarian language contact and second language acquisition. Bachelor's, Master's, and Doctoral degrees from the Faculty of Philosophy, University of Novi Sad Co-author of foundational textbooks for Serbian as a non-native language Coordinator of the Center for Serbian as a Foreign Language (2013-2018) Her research focuses on syntactic-semantic structures and modality in Serbian and Hungarian, with a particular emphasis on contrastive linguistics and language teaching methodologies . Her publications analyze modal verb constructions, infinitive usage, and cultural contexts in language education. She has contributed to educational standards development and collaborated on national research projects. The professor has taught courses in contrastive language studies , methodology of Serbian language instruction , and language contact theory at both undergraduate and graduate levels. Her work bridges theoretical linguistics with practical applications in multilingual education systems.
Anne Le Draoulec is a CNRS Research Officer affiliated with the Cognition, Languages, Ergonomics (CLLE) laboratory at the University of Toulouse 2 - Jean Jaurès. Her work focuses on Semantics, Discourse Analysis, and Temporal Markers , particularly the pragmaticalization of temporal expressions and their interaction with spatial and subjective elements in French language. Current affiliation: CNRS research officer, CLLE laboratory, University of Toulouse 2 Research interests include: Evolution of temporal locutions into pragmatic markers (e.g., "à un moment donné") Semantic-pragmatic interface in French discourse Interplay between spatial and temporal expressions Complex prepositions and enunciative rupture markers Recent article trends highlight her exploration of: Pragmaticalization processes in oral/written French Temporal deixis ("dans x temps", "ici") Discourse markers like "après", "maintenant", "ensuite" Gender asymmetry in linguistic structures
Dr. Antonia Ruppel is a Lecturer in Sanskrit at the School of Oriental and African Studies (SOAS), University of London , affiliated with the School of History, Religions and Philosophies . Her work bridges classical philology with modern linguistic theory and pedagogy. Institution : SOAS University of London School : School of History, Religions and Philosophies Role : Lecturer in Sanskrit Contact : ar83@soas.ac.uk Research Interests: Sanskrit syntax and morphology, with a focus on passives and causatives Indo-European comparative grammar and historical reconstruction Development of absolute constructions in early Indo-European languages Innovations in ancient language pedagogy and digital education platforms Curriculum design for classical languages in modern educational contexts Corpus-based analysis of Vedic and Classical Sanskrit texts Her recent publications demonstrate a dual focus on advancing linguistic theory while creating practical tools for Sanskrit learners, including textbooks and digital environments. She has pioneered initiatives to reintroduce Sanskrit to UK schools through modern pedagogical frameworks. Scientific Awards: No formal awards mentioned in the provided data Dr. Ruppel's work has significantly impacted Sanskrit education through innovative resources like The Cambridge Introduction to Sanskrit and research into grammatical constructions that shape our understanding of Indo-European language evolution.
Alexandre Nikolaev is a University Lecturer in General Linguistics at the School of Humanities, University of Eastern Finland. His research focuses on morphological complexity, paradigmatic defectivity in inflectional systems, and cognitive approaches to language structure. Key methodologies include corpus analysis, behavioral experiments, and computational modeling. Affiliation: University of Eastern Finland Research Areas: Morphology, Corpus Linguistics, Psycholinguistics, Neurolinguistics Prominent Research Themes: Paradigmatic defectivity as dynamic systems rather than static gaps Cognitive load in inflectional choice production Interaction of corpus frequency and subjective acceptability ratings Comparative analysis of Finnish, Czech, and Russian inflectional patterns Methodological Expertise: Network analysis, mixed-effects modeling, optimal string alignment techniques, cross-linguistic corpus studies, multi-lab collaboration frameworks. No scientific awards or student advising details were explicitly mentioned in the provided text.
Dr. Olena Syrotkina is a Professor at the University of Windsor's School of Computer Science. She holds a Ph.D. in Mathematical Simulation from Ukrainian State University of Science and Technologies and an M.Sc. in Computer Science from Dnipro University of Technology. Her research focuses on SCADA diagnostics, big data analytics, discrete mathematics, and machine learning algorithms. Research Interests: Her work spans computational methods for large-scale data analysis, including machine learning applications in industrial systems and theoretical frameworks for data optimization. Primary areas include: SCADA system reliability and diagnostics Big data processing and resource optimization Machine learning-driven predictive modeling Research Trends: Her recent publications emphasize mathematical optimization in big data contexts, with themes like quantum computing applications, fault detection in complex systems, and e-commerce analytics. Over 80% of her 2020-2024 publications involve scalable algorithms for industrial data. Honors & Advising: No awards are listed. She currently mentors graduate students but no named advisees were specified. Laboratory & Teams: Leads research in computational methods at UWindsor, collaborating with industrial partners on SCADA and data infrastructure projects.
