Find Academic Supervisors

• German Linguistics
• Syntax
• Formal Grammar
• +3 more

Prof. Stefan Müller is a Professor at the Institute for German Language and Linguistics , part of the Faculty of Languages and Literature at Humboldt University. His research focuses on syntax, formal grammar theories (especially Head-Driven Phrase Structure Grammar), and computational linguistics. He leads the CoreGram Project , developing cross-linguistic grammars using HPSG formalisms. His work includes analyses of German syntax, constituent order, anaphoric binding, and register phenomena. He is also involved in open-access publishing initiatives through Language Science Press . Contact: St.Mueller@hu-berlin.de . Education and academic background details are not explicitly stated in the provided text, but his professional trajectory indicates deep expertise in theoretical linguistics. His research spans multiple languages including German, Mandarin, and Persian, with a focus on grammar implementation and syntax-semantics interfaces. Key contributions include the Head-Driven Phrase Structure Grammar Handbook (2024), analyses of headless nominal structures in German (2022), and exploration of large language models' theoretical implications (2024). He actively engages in interdisciplinary projects bridging formal grammar and computational methods.

Pia KnoeferleView profile

Professor

• Psycholinguistics
• Language Processing
• Register Studies
• +7 more

Prof. Dr. Pia Knoeferle is a leading academic at Humboldt-Universität zu Berlin , where she serves as a Professor in the Department of German Language and Linguistics . She is a principal investigator in the Collaborative Research Center (CRC 1412) focused on register phenomena and leads the Reaction Time, Eye-tracking, and EEG Laboratories . Her research spans psycholinguistics , cognitive neuroscience , and computational modeling of language , with a central interest in how real-time language comprehension interacts with social context , formality-register congruence , and morphosyntactic processing . Appointments: Professor at Humboldt-Universität (2024), CRC 1412 member Methodologies: Eye-tracking, EEG, Visual World Paradigm, ERP Her work investigates lifespan language processing (children, adults, older adults) through contextual cue integration , including emotional , spatial , and social context such as gender cues , eye gaze , and facial expressions . Key questions include: How do pragmatic and contextual factors modulate lexical and grammatical processing ? What representations underlie register sensitivity in spoken and written comprehension ? Recent articles (2022-2024) focus on register congruence effects in German sentence processing, age-related differences in formality-register anticipation , and interactions between register and morphosyntactic knowledge . Using eye-tracking and visual world paradigms , her team examines incremental integration of socially-situated context with verb-argument relations and grammatical constraints . Findings suggest subtle late-stage register effects and interference between pragmatic and syntactic processing . Her lab collaborates with researchers like Katja Maquate , Valentina Nicole Pescuma , and Camilo Ronderos , contributing to the Frame text of the Second Phase Proposal for CRC 1412 (2020) and subsequent reviews in Frontiers in Psychology (2023). The work emphasizes complementary methods to model register variability across languages , modalities , and cultural contexts .

• Computational Linguistics
• Natural Language Processing (NLP)
• Dependency Parsing
• +5 more

Joakim Nivre is a Professor at Uppsala University's Department of Linguistics and Philology. He is a leading researcher in computational linguistics, with a focus on dependency parsing, Universal Dependencies (UD) framework development, and multilingual NLP applications. His recent work explores LLMs in climate change discourse analysis, pharmacovigilance explainability, and historical text processing. Key research areas: Dependency parsing theory, Universal Dependencies standardization, LLM evaluation Collaborations: SweSAT-1.0 benchmark development, ClimateEval project, PARSEME integration His 2025-2023 publications demonstrate expertise in explainable AI for healthcare, synthetic data generation for idioms, and multilingual benchmark design. Notably, he co-developed SweSAT-1.0 to evaluate Swedish LLMs and contributed to typology-informed UD revisions. Despite extensive work in NLP, no scientific awards are mentioned in available texts.

Burkhard MaessView profile

Research Professor

• Neuroscience
• Auditory Processing
• Signal Analysis
• +3 more

Dr. Burkhard Maess is a Research Professor and Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences, leading the Methods and Development Group Brain Networks. His research focuses on auditory and language processing, signal analysis, and dynamic modeling of neuronal networks. He holds a Diploma in Physics (University of Leipzig, 1987) and a PhD in Physics (University of Leipzig, 1990). His career includes postdoctoral positions at the Academy of Sciences of the GDR and the Free University of Berlin before joining the MPI in 1995. Since 2000, he has led research groups on MEG/EEG signal analysis and cortical network dynamics. His work integrates advanced neuroimaging techniques like MEG and EEG to study sensory processing, neural network dynamics, and the effects of aging on auditory attention. Key contributions include developing high-resolution BEM-FMM methods for source localization and analyzing cross-frequency coupling in neuroscience data. His group also explores spinal cord electrophysiology and the neural underpinnings of perceptual decision-making. Dr. Maess’ research spans cognitive neuroscience, biomedical engineering, and computational modeling, with a focus on bridging empirical findings with theoretical frameworks in neuroscience.

• Machine Learning
• Educational Data Mining
• Time Series Forecasting
• +5 more

Irena Koprinska is a prominent researcher at the University of Sydney with over 150 publications from 1996 to 2025. Her work spans multiple interdisciplinary domains with significant contributions to machine learning applications in educational technology, time series forecasting, and health informatics. She maintains strong research collaborations, particularly with Kalina Yacef (38 joint publications), Mashud Rana (26 papers), and Bryn Jeffries (22 papers), indicating leadership in her research group. Her research interests focus on practical applications of machine learning across diverse domains. In educational data mining, she has pioneered methods for predicting student performance in programming courses, analyzing syntax errors, and developing automated hint generation systems. Her work in time series forecasting has made significant contributions to solar power prediction using advanced neural network architectures. Additionally, she has applied machine learning techniques to medical domains, particularly in sleep disorder detection and analysis. The analysis of her 15 most recent publications (2022-2025) reveals a continued focus on educational technology and time series analysis, with increasing attention to interpretable methods and health applications. Her work demonstrates a consistent trajectory of applying sophisticated machine learning techniques to solve real-world problems across multiple domains, with particular emphasis on creating practical tools for education and renewable energy management. Notable Research Contributions: Development of the HINTS framework for automated programming hint generation Innovative approaches to multistep-ahead time series forecasting Applications of deep learning to sleep disorder detection Methods for predicting student performance in programming education Her publication record in top venues including Machine Learning journal, AIED, EDM, and IJCNN demonstrates significant impact in both machine learning and educational technology communities. The consistent output of high-quality research over nearly three decades indicates sustained scholarly productivity and leadership in her fields of expertise.

• Computational Linguistics
• Historical Linguistics
• Phylogenetic Linguistics
• +8 more

Prof. Gerhard Jäger holds the Chair of General Linguistics at the Faculty of Humanities, University of Tübingen . He serves as a Principal Investigator (PI) in the Clusters of Excellence Human Origins and Machine Learning for Science , and leads projects like Phylomilia (funded by Volkswagen Foundation) and CrossLingference (ERC Advanced Grant). His career spans multiple institutions, including Bielefeld University (2004-2009) and Stanford University (visiting scholar, 2004). Habilitation (2002) at Humboldt University Berlin with thesis on Anaphora and Type Logical Grammar PhD (1996) at Humboldt University Berlin on Dynamic Semantics His research bridges computational linguistics , phylogenetic analysis , and game theory , focusing on Bayesian models , language evolution , and cross-linguistic typology . Recent work explores phylogenetic inference from acoustic speech data and geographic influences on language trees . Key contributions include 15+ recent publications on topics spanning phylogenetic typology , cognate detection , and Bayesian language modeling . These works employ machine learning , statistical inference , and evolutionary game theory to analyze language change , typological variation , and linguistic stability . Honors include ERC Advanced Grant , Volkswagen Foundation funding , and DFG-Humanities Centre for Advanced Studies participation. He has taught courses in Computational Historical Linguistics , Phylogenetic Methods , and Bayesian Data Analysis across institutions like Tübingen, Bielefeld, and Stanford. He actively contributes to academic communities through workshop organization (e.g., Quantitative Theoretical Linguistics , Game Theory in Pragmatics ) and serves on the faculty council at Tübingen. His team collaborates with institutions like Max Planck Institute for Evolutionary Anthropology , University of Pennsylvania , and LMU Munich .

Steve ZdancewicView profile

Professor

• Programming Languages
• Type Theory
• Logic
• +7 more

Steve Zdancewic is the Schlein Family President's Distinguished Professor and Associate Chair in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. He is a leading researcher in programming languages, formal methods, and computer security with over two decades of impactful contributions to the field. His research interests span programming languages, type theory, logic, computer security, quantum programming, and formal verification. Zdancewic has made significant contributions to information-flow security, memory safety, program synthesis, and the verification of low-level systems. His work often bridges theoretical foundations with practical applications, particularly through the development of verified systems using Coq and other proof assistants. Analysis of his recent publications reveals a strong focus on formal verification techniques, particularly using Interaction Trees and the Coq proof assistant. His research trajectory shows consistent evolution from foundational work on information-flow security toward increasingly sophisticated verification of complex systems including LLVM, quantum computing, and distributed systems. His work demonstrates a commitment to building practically useful verification tools while maintaining rigorous theoretical foundations. Distinguished Paper Award for Semantics for Noninterference with Interaction Trees (ECOOP 2023) Schlein Family President's Distinguished Professor (2021) Distinguished Paper Award for Interaction Trees (POPL 2020) Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching (2018) IEEE MICRO top picks (2013) Alfred P. Sloan Fellow (2009-2010) NSF CAREER award (2004) Zdancewic has advised numerous PhD students who have gone on to successful careers in academia and industry. His research has been supported by significant grants from NSF, including the NSF Expedition on the Science of Deep Specification. He is actively involved in multiple major research projects including Vellvm (verified LLVM), DeepSpec, and quantum programming verification. Zdancewic also co-organizes Penn's PL Club programming languages research group with Benjamin Pierce and Stephanie Weirich.

Frank KammerzellView profile

Professor

• Phonology
• Morphology
• Syntax
• +8 more

Prof. Dr. Frank Kammerzell is a Professor at the Department of Archaeology and Cultural History of Northeast Africa within Humboldt University of Berlin since May 2003. His academic career includes habilitation at the University of Göttingen (1999) and extensive research collaborations with Hebrew University of Jerusalem and University of Vienna. His educational background encompasses Medieval and Modern History (major 1980), Egyptology (major), Coptic Studies, General and Indo-European Linguistics, and Assyriology. He earned his Dr. phil. from Göttingen with a dissertation on 'Studies on the Language and History of the Carians in Egypt' (1990) and completed habilitation with 'Language contact and language change in ancient Egypt' (1999). Kammerzell's research spans Egyptian phonology, morphology, syntax, lexis, language history, diachronic typology, language contact, writing systems, and Carian history in Egypt. His work integrates linguistic analysis with archaeological contexts, examining language evolution through contact and typological shifts. Notable projects include studies on Egyptian-Akkadian typological developments and classifiers in ancient Egypt. His publications since 2000 demonstrate sustained focus on Egyptian linguistic structures, writing systems, and cross-linguistic influences. Key themes include verb classifiers, glossing rules for Ancient Egyptian, and lexical semantics-pragmatics interfaces, bridging Egyptology with broader linguistic theory. Graduate Scholarship from the State of Lower Saxony (Doctoral Scholarship) 1987-1989 Kammerzell has led significant research projects funded by the DFG, Fritz Thyssen Foundation, and Volkswagen Foundation. His collaborative work with institutions in Jerusalem and Göttingen highlights international partnerships. While specific advisees aren't listed, his editorial roles suggest mentorship in academic publishing. He co-founded research groups on multilingualism and script systems, contributing to journals like Lingua Aegyptia and Ägypten und Levante , underscoring team-based archaeological-linguistic research.

Jürgen CitoView profile

Associate Professor

• Software Engineering
• Explainable AI
• Performance Engineering
• +3 more

Jürgen Cito is an Associate Professor with tenure at Vienna University of Technology (TU Wien), specializing in software engineering, explainable AI, and performance engineering. He leads research at the IPA Lab (as indicated by his personal website) and maintains a visiting researcher position at Google. His academic journey began with joining TU Wien as an Assistant Professor in Spring 2020, with promotion to Associate Professor announced in April 2024. His research interests span multiple critical areas of modern software development, with particular focus on developer experience, program comprehension, and the intersection of AI with software engineering practices. His work bridges theoretical foundations with practical industrial applications, as evidenced by collaborations with major technology companies. Analysis of his recent publications reveals a strong emphasis on practical tools and methodologies that enhance software quality, performance, and security. His research trajectory shows increasing focus on explainable AI techniques applied to software engineering problems, performance prediction from source code, and automated security testing approaches that leverage large language models. best teaching award for distance learning for Web Engineering (2020) Cito actively contributes to the software engineering community through numerous conference committee roles, including program committee positions at ASE, ICSE, ESEC/FSE, and other major venues. His lab appears to focus on developer tools, program analysis, and AI-assisted software engineering, with connections to both academic and industrial research environments.

Lars GrunskeView profile

Professor

• Software Engineering
• Formal Methods
• Model Checking
• +5 more

Lars Grunske is a Professor at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin. His research focuses on software and systems engineering, safety-critical systems, and software evolution. Department: Computer Science University: Humboldt University of Berlin Academic Rank: Professor His work spans automated software analysis, probabilistic model checking, and formal methods for complex systems. Key collaborations include researchers from Swinburne University, University of Hull, and University of Queensland. Recent publications address research software engineering, program repair, and explainability in cyberphysical systems. Professional roles include leadership in examination boards and program committees for conferences like ICSE and ASE. Contact info: Email: grunskel@hu-berlin.de Phone: +49 30 2093-41142 Address: Unter den Linden 6, Berlin

Anke HollerView profile

Professor

• Descriptive Grammar of Contemporary German
• Formal Grammar and Language Theory
• Grammar-Pragmatics Interface
• +4 more

Prof. Dr. Anke Holler is a Professor of German Linguistics at the University of Göttingen , specializing in formal grammar, discourse analysis, and computational linguistics. Her career spans roles in academic administration, including Vice President for Appointments since 2021, and leadership in DFG and Leibniz Association committees. Education : University of Tübingen, University of Leipzig, and University of Massachusetts, Amherst Current Projects : GRK 2636 'Form-Meaning Mismatches', DFG 'Structuring Literature' (SPP 2207), VW Foundation 'Uncertain Attribution' Research Interests focus on the intersection of grammar theory, experimental linguistics, and computational modeling. She explores discourse structures, narrative perspective, and constraint-based parsing, with applications in digital humanities and text mining. Her recent work involves neural networks for speaker attribution and computational analysis of literary reflexivity. Collaborations include the Carl Friedrich Lehmann-Haupt Doctoral Program and the 'Textstrukturen' center. She serves as editor for the Zeitschrift für Sprachwissenschaft and coordinates interdisciplinary initiatives.

Laura BeckerView profile

Assistant Professor

• Linguistic Typology
• Quantitative Linguistics
• Coding Efficiency
• +4 more

Laura Becker is an Assistant Professor at the Department of General Linguistics, University of Freiburg. Her research focuses on linguistic typology, quantitative methodology, and the role of coding efficiency in grammatical structures. She holds a PhD exploring article systems across languages and has contributed to cross-linguistic studies on syntax, morphology, and sociolinguistics. Her work emphasizes statistical rigor and computational tools, such as the glottospace R package for geospatial linguistic analysis. Recent projects include investigating phoneme inventories in Polynesian languages and socio-linguistic influences on conditional constructions. Publications highlight her expertise in morphosyntax, language contact, and corpus-based approaches. No scientific awards are explicitly mentioned in the provided materials. Dr. Becker has advised no recorded students in the available data and has not listed specific grants or labs. Her current research trends prioritize quantitative frameworks to address typological and evolutionary questions in linguistics.

Koushik SenView profile

Professor

• Software Engineering
• Programming Languages
• Formal Methods

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research focuses on developing software tools and methodologies to enhance programmer productivity and software quality, with expertise in Software Engineering, Programming Languages, and Formal Methods. Education: B.Tech from Indian Institute of Technology, Kanpur M.S. and Ph.D. in Computer Science from University of Illinois at Urbana-Champaign Research Focus: Professor Sen pioneers automated testing techniques including concolic testing and DART (Directed Automated Random Testing). His work bridges formal methods with practical software development, emphasizing bug detection, program synthesis, and AI-driven software analysis tools. Recent innovations include machine learning approaches for code recommendation and fuzzing. Publication Trends: His recent publications (2019-2023) demonstrate strong emphasis on fuzzing techniques, program synthesis, and AI/ML applications in software engineering. Notable domains include smart contract security, automated testing, and developer tooling, with frequent collaborations in top-tier conferences. Awards and Honors: NSF CAREER Award (2008) Sloan Foundation Fellowship (2011) IFIP TC2 Manfred Paul Award (2010) Okawa Foundation Research Grant (2015) Multiple ACM SIGSOFT Distinguished Paper Awards UIUC Distinguished Alumni Educator Award (2014) Leadership: Active program committee member for premier conferences (PLDI, ICSE, ISSTA) and keynote speaker. His research is supported by NSF, Okawa Foundation, and Sloan Foundation.

Mathis RichterView profile

Researcher

• Higher cognition
• Concept representation
• Dynamic Field Theory
• +9 more

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.

Ablet SemetView profile

Researcher

• General Turkology
• Turkish-Chinese and Turkish-Mongolian language contacts
• Linguistic and cultural contacts among the Islamic Turkic peoples
• +3 more

Dr. Ablet Semet is a researcher at the University of Göttingen specializing in Turkology with expertise in Old Turkic language and cultural contacts among Turkic peoples. His institutional affiliation centers on Central Asian linguistic studies within the university's research framework, focusing on historical interactions between Turkic communities and neighboring civilizations. His research spans General Turkology, Turkish-Chinese and Turkish-Mongolian language contacts, and Islamic Turkic cultural exchanges. Semet's work emphasizes philological analysis of primary sources including the Xuanzang biography, Buddhist texts, and folklore traditions. His methodological approach combines textual criticism with historical linguistics to reconstruct cultural transmission routes across Eurasia. Analysis of Semet's 15 most recent publications reveals consistent focus on Old Turkic manuscripts (particularly Xuanzang-related texts), Buddhist narrative traditions, and comparative studies of measurement systems in Turkic cultures. His research demonstrates interdisciplinary integration of linguistics, religious studies, and historical anthropology with strong emphasis on manuscript evidence from Turfan and Central Asian collections. No scientific awards were documented in the available information. While no student advising or grant information appears in the provided materials, Semet's extensive collaborative work with scholars like Simone-Christiane Raschmann and Jens Wilkens indicates active participation in international research networks focused on Turkic manuscript studies.