Find Academic Supervisors

• Creole linguistics
• Language contact and multilingualism
• Syntax of Gbe and Kwa languages
• +3 more

Prof. dr. Enoch O. Aboh is Professor of Linguistics at the University of Amsterdam , Faculty of Humanities, Department of Literature and Linguistics. His office is located at Spuistraat 134, room 647, and he can be contacted at e.o.aboh@uva.nl . Research Interests: Prof. Aboh’s work lies at the intersection of formal syntax, language contact, and learnability. He investigates creole formation , multilingual ecologies , Gbe and Kwa syntax , cartographic approaches to clause structure , and sign language morphosyntax . A recurring theme is the emergence and evolution of grammatical systems under contact, approached through both descriptive fieldwork and formal theoretical modelling. His publications reveal a methodological breadth spanning experimental studies with kindergarteners on statistical learning, computational detection of loanwords, and fine-grained syntactic analyses of serial verb constructions, predication patterns, and determiner systems. This spectrum underscores his commitment to integrating cognitive, typological, and formal perspectives on language. Awards & Recognition: While no specific prizes are listed in the current material, Prof. Aboh’s extensive editorial and collaborative work—evidenced by numerous co-edited volumes and Festschrift contributions—attests to his standing in the field. Students & Grants: Details on PhD advisees or funded projects are not provided in the source text. Labs & Teams: No dedicated laboratory or research group names are mentioned, yet his affiliation with the Amsterdam Center for Language and Communication (ACLC) can be inferred from the institutional context.

Ivana NikoloskaView profile

Assistant Professor

• Machine Learning
• Quantum Computing
• Communication Engineering
• +7 more

Ivana Nikoloska is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). She is affiliated with the Center for Quantum Materials and Technology Eindhoven and BIASlab (Bayesian Intelligence and Stochastic Agents Lab). Her academic career includes prior roles as a Research Associate at King’s College London and a Visiting Researcher at Aalborg University. PhD: Monash University, Australia (2023) MSc & Dipl.-Ing.: University of Ss. Cyril and Methodius, North Macedonia Research Interests span foundational and applied machine learning, quantum computing, and information/communication engineering. Her work focuses on integrating Bayesian inference, variational methods, and quantum technologies for tasks like signal processing, channel estimation, and power control optimization. Quantum Machine Learning Bayesian Simulation-Based Inference Meta-learning for Wireless Systems Hybrid Quantum-Classical Architectures Stochastic Signal Processing Quantum Sensing & Metrology Notable Trends in Publications include quantum recurrent neural networks with adaptive gating, Bayesian frameworks for quantum sensing, and meta-learning applications in communication systems. She explores variational inference for planning and robust algorithms for channel estimation under non-ideal conditions.

Arianna BisazzaView profile

Associate Professor

• Natural Language Processing
• Multilingualism
• Low-resource Language Modeling
• +7 more

Arianna Bisazza is an Associate Professor in the Computational Linguistics Group at the University of Groningen, where she leads the InClow research group focused on Interpretable, Cognitively inspired, Low-resource language models. Her work bridges computational linguistics, cognitive science, and language acquisition to develop more robust and interpretable language processing algorithms that can adapt to diverse linguistic phenomena worldwide. Dr. Bisazza's research interests span statistical modeling of human languages in multilingual contexts, with particular focus on improving language model performance for "challenging" or low-resource languages. Her work explores how insights from human language acquisition can inform better language modeling techniques, and she investigates methods to make state-of-the-art NLP systems more interpretable and transparent. As a cross-disciplinary researcher, she actively seeks to enhance our understanding of human language processing and evolution through computational modeling tools. Her recent publications reveal a strong emphasis on multilingual evaluation frameworks (like TurBLiMP and MultiBLiMP), interpretability of language models, and connections between human language acquisition and neural network learning. Her work consistently addresses the challenge of making language technology more robust across diverse linguistic structures and typological features. Outstanding Paper Award at the BabyLM Challenge (CoNLL'24 Shared Task) for "BabyLM Challenge: Exploring the Effect of Variation Sets on Language Model Training Efficiency" Dr. Bisazza currently leads a Vidi project funded by the Dutch Research Council (NWO) on improving low-resource language modeling through child language acquisition insights. She is also part of two national consortium projects funded by NWA-ORC initiatives: InDeep (Interpreting deep learning models for language, speech & music) and LESSEN (Low Resource Chat-based Conversational Intelligence). She supervises multiple PhD students, including two China Scholarship Council (CSC)-funded researchers working on simulating human patterns of language learning and change. Her earlier research was supported by a Veni grant (2017-2021) focused on understanding and improving the encoding of linguistic structure in Neural Machine Translation models. As head of the InClow research group, Dr. Bisazza oversees a team investigating interpretable, cognitively inspired approaches to low-resource language modeling. The group's work combines insights from cognitive science and linguistics with cutting-edge NLP techniques to develop language models that better reflect human language processing capabilities, particularly in resource-constrained settings.

Evert van NieuwenburgView profile

Assistant Professor

• Quantum Physics
• Machine Learning
• Condensed Matter Physics
• +6 more

Dr. Evert van Nieuwenburg is an Assistant Professor at Leiden University, affiliated with both the Leiden Institute of Advanced Computer Science (LIACS) and the Leiden Institute of Physics (LION). His research bridges the fields of Quantum Physics , Machine Learning , and Condensed Matter Physics , with a focus on quantum algorithms, reinforcement learning, and quantum game development (e.g., Quantum TiqTaqToe ). He actively contributes to the Applied Quantum Algorithms (aQa) initiative and leads the QuantumPlayed subgroup for quantum games and education. Research Interests: AI-driven quantum experiment control, quantum machine learning, variational quantum circuits, and quantum games for education and intuition-building. Publications: 15+ peer-reviewed works spanning quantum error correction, phase transitions, reinforcement learning in quantum systems, and quantum dot array simulations. Community Engagement: Developer of educational quantum games, open science advocate, and active participant in interdisciplinary initiatives. Selected Trends: His work demonstrates AI's transformative role in quantum physics, from decoding error-correcting codes with graph neural networks to merging reinforcement learning with quantum control systems. Labs & Initiatives: Affiliated with the Applied Quantum Algorithms (aQa) initiative and co-founder of QuantumPlayed , where quantum mechanics meets game theory to engage diverse audiences.

Bert de VriesView profile

Professor

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +3 more

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

Serena SannaView profile

Researcher

• Genetics
• Microbiome
• Genome-Wide Association Study
• +5 more

Serena Sanna, PhD , is a researcher at the Faculty of Medical Sciences of the University of Groningen, affiliated with the Groningen Institute for Gastrointestinal Genetics and Immunology (3GI) . She contributes to UN Sustainable Development Goals through work on genetics, microbiome, and complex disease mechanisms. Expert in genetics and microbiome research Specializes in genome-wide association studies and Mendelian randomization Research Focus : Host genetic regulation of gut microbiome composition, causal relationships between microbiome and diseases (e.g., endometriosis, hemorrhoidal disease), and integration of metabolomics with immune phenotypes. Her work involves large-scale biobank studies like the Lifelines Cohort . Scientific Awards : Donna di Scienza 2023 Prize Guido Dorso Prize (2018) Highly Cited Researcher (2018) ESHG Meeting Young Scientist Award (2008) Recent Publications : 2025 studies on MBL pathway/microbiome in endometriosis and age-related microbiome effects; 2024 works on hepatic fat genetics, diverticular disease comorbidities, and structural microbiome variation. Active in multi-omics and data integration methodologies.

• First language acquisition
• Tense and aspect
• Telicity
• +7 more

Dr. Angeliek van Hout is a faculty member at the University of Groningen's Faculty of Arts, where she leads the Acquisition Lab within the Center for Language and Cognition Groningen (CLCG). Her academic profile centers on experimental research into first language acquisition in typically developing monolingual children, employing a crosslinguistic perspective to investigate fundamental aspects of language development. Her research expertise spans multiple interconnected domains of linguistic development: Temporal reference (tense and aspect, telicity, event culmination) Nominal reference (definiteness, quantification) Syntactic structures (questions, passives, pronouns) Pragmatic reasoning (scalar implicatures, theory of mind) Dr. van Hout's methodological approach integrates formal linguistic theory with empirical experimentation, examining how children acquire complex linguistic structures across different languages. Her recent work demonstrates particular focus on logical operators and their interpretation in child language, with extensive crosslinguistic comparisons examining how children process disjunction under negation in Dutch, French, Hungarian, and Italian. She investigates the cognitive mechanisms underlying these linguistic phenomena, bridging theoretical linguistics with cognitive science. Her publication record shows consistent productivity with 89 research outputs including 25 articles, 23 conference contributions, and 20 book chapters. Notable recent publications include work on prosodic disambiguation in Dutch, free choice interpretation in French children, and crosslinguistic patterns in quantifier acquisition. Dr. van Hout actively contributes to the academic community through: Supervision of PhD students (4 supervised works documented) Editorial work including the TABU Festschrift for Jack Hoeksema Organizing academic events such as "Novel Semantic Research in Theory, Processing and L1 Acquisition" Presenting research at international conferences including the Boston University Conference on Language Development Her research has practical applications in understanding typical language development trajectories, which she communicates to broader audiences through public engagement activities. She has presented on language development in twins at multiple public events and participated in the NEMO Science Live initiative from 2016-2018, demonstrating commitment to knowledge transfer beyond academic circles. As leader of the Acquisition Lab, Dr. van Hout directs research examining how children develop linguistic competence across various domains, with particular attention to the interface between syntax, semantics, and pragmatics in early language development.

• Syntactic Variation
• Heritage Language Syntax
• Language Contact
• +6 more

Roberta D'Alessandro is a Professor of Linguistics/Syntax and Language Variation at Utrecht University's Department of Languages, Literature and Communication, and Head of the Linguistics section. She leads the research group 'Language Structure: Variation and Change' within the Institute for Language Sciences (ILS). Her work focuses on syntactic variation, heritage language syntax, and microvariation in Italo-Romance and Indo-Aryan dialects. She is editor-in-chief of Isogloss and Grammars and Sketches of the World's Languages/Romance , and president of Going Romance . Her research explores syntactic theory through heritage language data, language contact in migration contexts, and the syntax-phonology interface. Awards include the Knight of the Italian Republic (2014) and membership in the Global Young Academy (2014–2019). She coordinates EU policy initiatives and advises on ethical research practices. Education: Ph.D. in Linguistics (not explicitly stated, inferred from career) Grants: ERC Consolidator Grant (Microcontact Project), NWO VIDI (2010–2015), Marie Curie Fellowship (2005–2007) Recent work emphasizes ethical considerations in theoretical linguistics and the integration of fieldwork with formal syntactic analysis. She collaborates internationally, leading projects on endangered languages and linguistic microvariation.

Patrick J.F. GroenenView profile

Professor

• Data Science
• Multidimensional Scaling
• Optimization Algorithms
• +5 more

Patrick J.F. Groenen is a full Professor of Statistics at the Erasmus School of Economics (ESE), Erasmus University Rotterdam , and currently serves as its Dean. His academic career spans leadership roles, including Director of the Econometric Institute (2014-2020) and President of the International Association for Statistical Computing (2015-2017). He has held visiting positions at Stanford University and contributed extensively to multidimensional scaling (MDS), data science , and statistical genetics . His research focuses on numerical algorithms for MDS, support vector machines , and optimization techniques applied to diverse fields. He is a founding editor of the open-access journal Journal of Data Science, Statistics, and Visualisation and has authored major textbooks including Modern Multidimensional Scaling and Applied Multidimensional Scaling and Unfolding . His work appears in top journals like Nature Genetics , Psychometrika , and Journal of Machine Learning Research . Recent publications highlight advancements in convex clustering , genomic prediction , and robust statistical methods . He has developed influential R packages such as GenSVM , SVMMaj , and smacof for multiclass classification and MDS software. His supervisory record includes 14 PhD students across economic psychology, genetics, and data science. Academic activities include editorial roles at Advances in Data Analysis and Classification and Psychometrika , alongside organizing international conferences like CARME 2007 on correspondence analysis. His contributions to nonlinear biplots and response style modeling have advanced visual data interpretation in social sciences.

Luís Lima ValenteView profile

Associate Professor

• Evolutionary Biology
• Ecology
• Biodiversity
• +3 more

Luís Lima Valente is an Associate Professor at the University of Groningen and Senior Researcher at Naturalis Biodiversity Center. His work focuses on island biogeography, phylogenetics, and biodiversity dynamics. He leads the Biodiversity Hotspots group at Naturalis and co-leads the Theoretical & Evolutionary Community Ecology group at GELIFES. His research combines fieldwork, genomic data, and computational modeling to study evolutionary processes in island and continental ecosystems. Education: PhD in Evolutionary Biology (2010, Royal Botanic Gardens Madrid), MSc in Ecology, Evolution & Conservation (2006, Imperial College London), BSc in Biology (2005, University College London). Research Interests: Island biodiversity patterns, historical biogeography, phylogenetic methods, and the interplay between climate and evolutionary processes. Key projects include the DAISIE software package for island biogeography analysis and studies on radiations of island birds/plants. He has advised over 30 PhD/MSc students and postdocs, focusing on island systems like the Canaries, Mascarenes, and Caribbean. Awards: Marie Curie Fellowship (2011-2013), Humboldt Fellowship (2013-2016), Martin Temminck Fellowship (current). His lab actively collaborates globally, with fieldwork in Bioko, Mauritius, and the Azores. Current focuses include mountain plant radiations and the impact of climate oscillations on biodiversity.

Bart van ErpView profile

Researcher

• Bayesian Inference
• Machine Learning
• Signal Processing
• +3 more

Bart van Erp serves as a University Researcher within the Department of Electrical Engineering at Eindhoven University of Technology, actively contributing to the Signal Processing Systems (SPS) group and Bayesian Autonomous Intelligent Systems lab (BIASlab). He completed his PhD in June 2025 under Prof. Bert de Vries with dissertation work on automated Bayesian hearing aid design. His academic foundation includes: Bachelor of Science in Electrical Engineering, cum laude (2015-2018) Master of Science in Electrical Engineering, cum laude with honors (2018-2020), supported by ALSP scholarship Van Erp's research centers on Bayesian inference frameworks for real-world signal processing challenges, particularly in hearing aid personalization and autonomous systems. He pioneers message-passing algorithms on factor graphs to implement variational free energy minimization, enabling adaptive user preference learning and energy-efficient control systems. His work bridges theoretical probabilistic modeling with clinical applications in hearing impairment solutions. Analysis of his 2024-2025 publications reveals consistent focus on Bayesian neural networks and active inference methodologies, with increasing emphasis on practical implementations for assistive devices. Key trends include Dirichlet process applications for context-aware systems and depth estimation improvements in uncertainty-aware computer vision. Recognition includes: ALSP scholarship for Master's excellence As project member in the CoHear initiative (2017-2025), he contributed to collaborative hearing device design while securing open-source development through ReactiveMP.jl. Though newly minted as a PhD, he has not yet supervised graduate students but actively supports university education (0.3 FTE during studies). His dual role as Product Lead/Co-Founder at Lazy Dynamics BV since May 2023 demonstrates translational research impact. Within BIASlab, van Erp drives the integration of probabilistic programming with medical device innovation, maintaining strong industry partnerships in hearing technology through GN Hearing collaborations and open-source tooling.

• Language Acquisition
• Developmental Psychology
• Social Cognition
• +5 more

Dr. Tom St Pierre is an Assistant Professor in the Department of Languages, Literature and Communication at Utrecht University, affiliated with the Institute for Language Sciences. His research investigates the interplay between linguistic knowledge and social cognition in child development, focusing on how children use social information to guide language processing and vice versa. Current institution: Utrecht University Research areas: Language acquisition, processing, and disorders; Dynamics of Youth (DoY) - Early Childhood Teaching: Involved in BA and MA programs in English Language & Culture and Multilingualism & Language Acquisition His recent publications analyze: 2024: Experimenter identity effects in developmental research 2024: Group membership influence on children's lexical choices 2023: Pandemic-related socioeconomic impacts on toddler language development 2022: Cross-generational phonetic alignment and vocabulary processing

• First language acquisition
• Syntax
• Semantics
• +5 more

Dr. A.M.H. van Hout is a Professor in the Faculty of Arts at the University of Groningen, leading the Acquisition Lab within the Center for Language and Cognition Groningen (CLCG). Their research focuses on first language acquisition in monolingual children, particularly exploring temporal and nominal reference, tense/aspect, telicity, definiteness, and crosslinguistic variation. Key areas include syntax, semantics, pragmatics, and theory of mind reasoning in child language development. Research activities include cross-linguistic studies in Dutch, French, Hungarian, Italian, Spanish, and others, with emphasis on disjunction interpretation, negation scope, and tense systems. Collaborations involve international teams and comparative studies. Publications span 89 works, including peer-reviewed articles and conference contributions. Van Hout actively participates in academic events, editorial work, and public engagement initiatives on child language topics. Supervision activities include mentoring students in language acquisition research. The Acquisition Lab serves as a hub for experimental studies on child language development, integrating formal linguistic theories with empirical methods.

Clemens VerhooselView profile

Associate Professor

• Computational Mechanics
• Numerical Methods
• Solid Mechanics
• +5 more

Clemens Verhoosel is an Associate Professor in Computational Methods for Model- and Data-Driven Engineering at Eindhoven University of Technology (TU/e), specializing in the Department of Mechanical Engineering. His research focuses on numerical methods for engineering applications, including isogeometric analysis, immersed methods for complex geometries, and uncertainty quantification. He holds a prestigious NWO Veni Grant (2011) and has contributed to open-source tools like the Nutils toolkit. Education: MSc (with honors) in Aerospace Engineering from TU Delft (2005) PhD in Computational Mechanics from TU Delft (2009, cum laude) Postdoctoral research at the University of Texas at Austin (2009-2010) Research Interests: Scan-based immersed isogeometric analysis Uncertainty quantification and Bayesian inference Fluid-structure interaction Multiphase flow and fracture mechanics Teaching: Courses include Advanced Discretization Techniques (Isogeometric Analysis) and Scientific Computing for Mechanical Engineering. Awards: NWO Veni Award (2011): "Efficient modelling of bone fractures" Labs/Teams: Leads the Group Verhoosel and contributes to EAISI Foundational and Energy Technology research groups.

Wouter KouwView profile

Assistant Professor

• Probabilistic Machine Learning
• Variational Bayesian Inference
• Active Inference
• +6 more

Wouter Kouw is an Assistant Professor at the Electrical Engineering department of Eindhoven University of Technology (TU/e) , leading the Bayesian Intelligent Autonomous Systems lab. With a dual PhD in Computer Science (2018, TU Delft) and MSc in Neuroscience (2013, Maastricht University) , he bridges neurobiology and artificial intelligence through variational Bayesian inference and active inference frameworks. Research Focus : Probabilistic machine learning systems using message passing algorithms on factor graphs , applied to mobile robotics and adaptive control Key Projects : CONTACT-AI (contact-rich robot navigation), FEP-walker (active inference-based locomotion), and BayesBrain (hybrid neuro-in-silico computing) His work spans nonlinear system identification , uncertainty quantification , and sensor modeling , with recent publications in IEEE Transactions , Entropy , and Communications in Computer and Information Science . Awards include the Niels Stensen Fellowship (2017) and TU/e Team Science Award nomination (2023) . Collaborations extend to institutions in Germany, USA, and Denmark, with teaching responsibilities in Bayesian Machine Learning and Neuro Computation .