Find Academic Supervisors

Ginie Servant-MiklosView profile

Assistant Professor

• Environmental Education
• Sustainability Education
• Problem-Based Learning (PBL)
• +6 more

Ginie Servant-Miklos is an Assistant Professor at the Erasmus School of Social and Behavioural Sciences , Erasmus University Rotterdam. A leading figure in environmental education and problem-based learning (PBL), she develops pedagogical frameworks like Experimental Pedagogics and founded the Bildung Climate School and FairFight Foundation , which supports girls and women in Zambia, Zimbabwe, and India through martial arts and education. Her work bridges sustainability education, societal impact, and educational innovation. Bachelor of Arts in Politics, Philosophy, and Economics – University of Kent LLM in International Law – Kent Law School MA in International Relations – Sciences Po Lille PhD in Education Philosophy and Psychology – Erasmus University Rotterdam Post-doctoral research grant – Aalborg University Her research focuses on innovative pedagogies for societal transformation, particularly addressing climate change through problem-based learning . She explores how educational frameworks can cultivate resilience, agency, and ethical responsibility in the face of global crises. Her book Pedagogies of Collapse challenges traditional educational paradigms, advocating for hope-driven learning in the context of existential threats. Recent publications highlight her contributions to climate education and sustainability literacy , analyzing trends in PBL engineering students' awareness and engagement. Her work spans interdisciplinary collaborations, including roles at Tyumen University as a visiting professor. Scientific Awards: Leadership Fellow – Comenius Network for educational innovators (Netherlands) As founder of the FairFight Foundation , she integrates martial arts with mental health support and education for women in marginalized regions. Her advocacy appears in TEDx talks, podcasts, and debates, emphasizing sustainability and gender equality .

Carlo CavicchiaView profile

Assistant Professor

• Statistics
• Data Science
• Machine Learning
• +6 more

Dr. Carlo Cavicchia is an Assistant Professor of Statistics at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam. He holds a PhD in Methodological Statistics from La Sapienza University of Rome and has held roles such as Research Fellow at UnitelmaSapienza University and Consultant for NGOs in Zanzibar. His research focuses on latent variable models, composite indicators, and unsupervised classification, with applications in environmental policy, sports analytics, and teacher job satisfaction. Cavicchia teaches statistics and data science courses at undergraduate and graduate levels and actively contributes to academic communities through journal reviewing, conference organizing, and editorial roles. Education: PhD in Methodological Statistics (La Sapienza University of Rome, 2020) MSc in Statistics and Decision Sciences (La Sapienza University of Rome, 2016) BSc in Statistics (La Sapienza University of Rome, 2013) Dutch University Teaching Qualification (BKO, 2022) Research Interests: Cavicchia’s work emphasizes hierarchical models, non-parametric statistics, and data science applications. He develops methodologies for composite indicators, including ultrametric Gaussian mixture models and disjoint principal component analysis. His research bridges theoretical advancements with real-world problems, such as waste management in Italian municipalities and ranking European football teams using composite metrics. Grants & Awards: 2024: IFCS Chikio Hayashi Award 2023: ESE Starter Grant (€300,000) 2017: Research Grant for Junior Researchers (€1,270) 2016: PhD Scholarship, La Sapienza University Academic Engagement: Cavicchia serves as IASC Data Analysis Competition Officer (2023–2025), co-edits the ISI Magazine , and organizes conferences like DSSV 2020 and DSSV-ECDA 2021. He is an elected member of the International Statistical Institute and contributes to SVQS’s Sustainability initiatives. Labs & Teams: He co-organizes the Econometrics internal seminars at Erasmus University and collaborates with researchers at University of Naples Federico II on hierarchical models and convex clustering.

Sabine RoeserView profile

Professor

• Ethics of Technology
• Risk Ethics
• Moral Emotions
• +7 more

Sabine Roeser is a Full Professor of Ethics at Delft University of Technology, working within the Ethics and Philosophy of Technology Section at the Faculty of Technology, Policy and Management. She has been with TU Delft since 2001 and has held several leadership positions including Head of the Ethics and Philosophy of Technology Section (2015-2020), Head of Department of Values, Technology and Innovation (2021-2024), and Acting Dean of the Faculty of TPM (November 2024-April 2025). As one of six Principal Investigators in the NWO Gravitation project on 'Ethics of Socially Disruptive Technologies' (ESDiT), she co-leads the emotions and art lines of this major research initiative. Her educational background spans multiple disciplines, with degrees in painting (BA, Maastricht Academy of Fine Arts, 1994), philosophy (MA, University of Amsterdam, cum laude 1997), political science (MA, University of Amsterdam 1998), and a PhD in metaethics from Vrije Universiteit Amsterdam (2002). During her PhD studies, she conducted research at the University of Notre Dame and University of Reading. Roeser's research focuses on the intersection of ethics, emotions, and technology, particularly in the context of risk assessment and decision-making. She has developed 'affectual intuitionism,' a metaethical theory combining ethical intuitionism with cognitive theories of emotions. Her work argues that emotions serve as forms of moral cognition that can alert us to ethically relevant aspects of risky technologies. She has published two monographs ( Moral Emotions and Intuitions , 2011; Risk, Technology and Moral Emotions , 2018) and co-edited eight books with major academic publishers. Her research spans multiple technological domains including nuclear energy, climate change, transportation, and public health. Analysis of her recent publications reveals a consistent focus on the role of emotions in ethical decision-making, particularly in technological contexts. Her work increasingly explores how art can scaffold moral-emotional deliberation about risky technologies. She has made significant contributions to engineering ethics education, developing the 'Delft approach' that emphasizes problem-based learning and integration of ethical reflection throughout engineering curricula. More than 200 academic talks, mostly invited Over 100 interviews for popular media Member of various national and international policy advisory committees Former integrity officer of TU Delft (2018-2021) Chair of TU Delft's Human Research Ethics Committee (2014-2019) Roeser has secured competitive funding from organizations including NWO and the EU, leading multiple research projects and supervising numerous PhD candidates and postdoctoral researchers. She has played a key role in developing TU Delft's integrity policy and Code of Conduct. Her leadership has significantly grown both the Ethics and Philosophy of Technology Section and the Department of Values, Technology and Innovation.

• Public Administration
• Collaborative Governance
• Crisis Management
• +4 more

Scott Douglas is an Associate Professor at the Utrecht School of Governance, Utrecht University, specializing in Public Administration , Collaborative Governance , and Crisis Management . He focuses on the dynamics of collaborations between governments, companies, and community organizations to address complex societal challenges such as radicalization, child abuse, and crisis response. Education: University of Oxford, DPhil (2011) University of Oxford, MPhil Comparative Government (2008) London School of Economics, BSc Industrial Relations (2005) His research emphasizes interdisciplinary collaboration , innovative tools like the Performance Management Game, and public value creation . He co-founded the Security in Open Societies platform and leads international consortia such as Horizon and Adapt! on crisis governance. Key publications analyze collaborative performance regimes, cognitive biases in public procurement, and frameworks for evaluating governance measures. His work spans journals like Public Administration Review , Public Management Review , and PLoS One . Scientific Awards Member of De Jonge Akademie (2023) He bridges research , education , and societal impact through projects with NWO, municipalities, and the Dutch Safety Investigation Board. Current initiatives include studying how University Medical Centers can lead in primary prevention networks.

• Statistics
• Applied Data Science
• Veterinary Epidemiology
• +2 more

Hans Vernooij is a Lecturer in Farm Animal Health at the Faculty of Veterinary Medicine, Utrecht University. He specializes in statistical methods and data science applications in veterinary epidemiology and animal health. His areas of expertise include: Statistical methods for veterinary research Applied Data Science in Life Sciences Epidemiological modeling Machine learning applications in animal health Vernooij has extensive experience in developing statistical models for animal health applications. His research focuses on applying advanced statistical techniques and data science methods to solve problems in veterinary epidemiology and farm animal health. He has particular expertise in Random Forest models, as demonstrated during his sabbatical at the Human Sciences Research Council in Pretoria where he developed a model for HIV status prediction based on demographic information and knowledge of HIV prevention from large-scale survey data. His publication record shows consistent contributions across veterinary epidemiology, with recent work emphasizing machine learning applications and big data analytics in animal health surveillance. The research demonstrates a clear trajectory from traditional statistical methods toward more advanced data science approaches. Vernooij is actively involved in teaching and mentoring: Teaches statistics to Bachelor students at the veterinary faculty Supports PhD candidates and Master students during data analysis phases of their research Provides statistics education for the Master of Epidemiology program at the Julius Centre of University Medical Centre

• Evolutionary Computation
• Genetic Algorithms
• Optimization
• +5 more

Dirk Thierens is an Associate Professor in the Department of Computer Science at Utrecht University's Faculty of Science, specializing in Intelligent Systems within AI & Data Science. His academic career spans over 25 years, with continuous publications from 1996 through 2025, demonstrating sustained research activity and leadership in his field. He maintains an active research program with numerous collaborations, most notably with Peter A.N. Bosman, indicating a long-standing productive research partnership. Thierens' research focuses on evolutionary computation, particularly model-based evolutionary algorithms, genetic algorithms, and optimization techniques. His work has evolved from foundational genetic algorithm research in the late 1990s and early 2000s to more specialized model-based approaches in recent years, including significant contributions to Gene-pool Optimal Mixing Evolutionary Algorithms (GOMEA). His expertise spans single-objective and multi-objective optimization, permutation problems, mixed-integer problems, and real-valued optimization. In recent years, his research has expanded into applications in machine learning, particularly semi-supervised learning and neural network optimization. His publication record shows a consistent output of high-quality research, with numerous papers in top conferences like GECCO and journals in evolutionary computation. His most recent work (2023-2025) demonstrates continued innovation in synthetic data generation, neural network combination techniques, and parameterless evolutionary algorithms. The breadth of his work spans theoretical algorithm development, benchmarking methodologies, and practical applications in healthcare and other domains. While no specific scientific awards are mentioned in the available information, his extensive publication record, tutorial contributions at major conferences, and sustained research productivity over multiple decades indicate recognition within the evolutionary computation community. His tutorial work at GECCO conferences suggests he is considered an authority on model-based evolutionary algorithms. Thierens maintains an active research laboratory focused on evolutionary algorithms and their applications, with recent work exploring the intersection of evolutionary computation and deep learning. His research continues to advance both theoretical understanding and practical applications of optimization techniques in complex problem domains.

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.

• Geo-information Science
• Socio-ecological Systems
• Agroforestry Management
• +3 more

Dr. Erika Speelman is an Associate Professor at the Laboratory of Geo-information Science and Remote Sensing within Wageningen University. She holds MSc and PhD degrees from Wageningen University, specializing in tropical agronomy. Her research focuses on developing simulation and gaming tools to enhance stakeholder collaboration in addressing socio-ecological challenges, particularly in the Global South. She leads the INREF SESAM programme (2020-2025), supervising 15 PhD candidates and 2 PostDocs, and coordinates MSc courses in geo-information science and interdisciplinary research methods. Her work spans agroforestry, water governance, and participatory tools for sustainable landscape management. Dr. Speelman has extensive experience collaborating with NGOs, UN agencies, and academic institutions across Asia, Latin America, and Africa. Her research emphasizes boundary objects like serious games to bridge stakeholder perspectives in contested landscapes. Recent projects include exploring water management in Kenya’s Ewaso Ng’iro Basin and land use dynamics in Peru’s Amazon. She teaches courses on spatial modeling, remote sensing integration, and geo-information science in socio-ecological contexts. Her international collaborations reflect a commitment to global sustainability challenges, integrating technical tools with community-driven solutions. Dr. Speelman’s lab is part of the Environmental Sciences group at Wageningen, fostering interdisciplinary approaches to complex environmental problems. She advocates for inclusive landscape governance through participatory tools, aiming to enhance resilience among smallholder farmers and marginalized communities. Her work combines academic rigor with practical impact, addressing issues like climate change, biodiversity loss, and equitable resource distribution.

• Educational Technology
• Programming Tutoring Systems
• Game-Based Learning
• +1 more

Johan Jeuring is Professor of Software Technology for Learning and Teaching at Utrecht University's Department of Information and Computing Sciences. His research focuses on intelligent tutoring systems, computational thinking education, and game-based learning environments. Research Interests: Prof. Jeuring's work explores computational thinking pedagogy, automated feedback systems, and educational game design. His research bridges artificial intelligence with educational psychology to develop effective learning tools. Publications: Recent publications focus on augmented reality learning environments, programming education methodologies, automated assessment systems, and AI applications in education. His work combines empirical studies of learning behaviors with technological innovations in educational tools.

• Stochastic Processes
• Operations Research
• Data-Driven Decision Making
• +4 more

Stella Kapodistria is an Associate Professor at Eindhoven University of Technology's Department of Mathematics and Computer Science, specializing in Stochastic Operations Research. She holds roles as EAISI High Tech Systems Associate Professor and editorial board member of journals like MCAP and PEIS. Her research focuses on data-driven decision-making, stochastic systems optimization, and maintenance policies, with applications in renewable energy, critical infrastructure, and cryptocurrency networks. She has secured grants including NWA-ORC, NWO Big Data, and TKI WoZ, and collaborates with industry partners in the Brainport region. Education: BSc (2003), MSc (2006, Hons.), and PhD (2009, summa cum laude) in Mathematics from the University of Athens. Postdoc at TU/e, followed by roles at Groningen University and TU/e's Stochastic Operations Research group. Teaching includes courses on Optimal Decision Making, Stochastic Performance Modeling, and Financial Mathematics. Research interests emphasize real-time learning, system resilience, and scalable algorithms for complex networks. Recent work addresses maintenance logistics, blockchain confirmation times, and wind energy prediction. She has published over 40 peer-reviewed articles and contributed to the 4TU Resilience Engineering Center. Awards include editorial leadership roles and grant funding. Advised 32 academic works and oversees industrial projects bridging theory and practice. Her labs and collaborations focus on adaptive systems, predictive analytics, and sustainable engineering solutions.

Guido StompffView profile

Lecturer

• Design Thinking
• Innovation Processes
• Education Methodology
• +3 more

Dr. Guido Stompff is a Lecturer in Design Thinking at Inholland University of Applied Sciences, working three days a week. He leads the Design Thinking Lectorate within the Applied Research x Creativity Research Center, focusing on methodological foundations and broad educational integration of Design Thinking. His research emphasizes living labs, such as the Urban Leisure & Tourism Lab addressing tourism pressures in Amsterdam. He collaborates with educational institutions, museums (e.g., Cube Design Museum), and organizations like Brightlands Innovation Factory to advance innovation processes. Stompff’s work bridges design practice and academic research, advocating for practitioner-driven methodologies. He holds a PhD from TU Delft and authored a best-selling book on Design Thinking. Key projects include the Students as Partners initiative (with Comenius Grant) and the Dutch Pop Music Sector Research Agenda. His research explores team dynamics, design inquiry in education, and systemic co-design approaches for societal challenges. Education: PhD in Innovation Processes (TU Delft) MSc Industrial Design Engineering (TU Delft) Research Interests: Design Thinking Methodology Interdisciplinary Collaboration Education Innovation Urban Social Challenges Practitioner-Academia Synergy Grants & Recognition: Comenius Grant (2023) for Students as Partners Project Author of bestseller Design Thinking; Radical Change in Small Steps (2018) Advising & Partnerships: Cube Design Museum (Kerkrade) Brightlands Innovation Factory (Limburg) Urban Leisure & Tourism Lab (Amsterdam-North) Expertisenetwerk Systemisch Co-design

Tijn FleurenView profile

Researcher

• Operations Research
• Supply Chain Management
• Production-Inventory Planning
• +7 more

Dr. Tijn Fleuren is a researcher and teacher at the Department of Econometrics and Operations Research within the Tilburg School of Economics and Management (TiSEM) at Tilburg University. His work focuses on optimizing production-inventory systems under uncertainty, with applications in high-tech, low-volume manufacturing supply chains. Institution: Tilburg University School: Tilburg School of Economics and Management Department: Department of Econometrics and Operations Research Email: T.W.A.Fleuren@tilburguniversity.edu ORCID: https://orcid.org/0000-0002-0925-6892 Office: Koopmans Building, Room K 423, Warandelaan 2, 5037 AB Tilburg, Netherlands His research lies at the intersection of operations research and supply chain management, with a strong emphasis on stochastic modeling, risk-aware decision-making, and integrated planning under uncertainty. Key themes include production-inventory optimization, customer portfolio selection, procurement planning, and dynamic supply chain configurations. His work often addresses real-world challenges in collaboration with industry leaders like ASML. The recent publications demonstrate a consistent focus on advanced optimization techniques applied to complex supply chain environments. These include multi-stage stochastic programming, conic quadratic programming heuristics, sampling-based methods, and deep reinforcement learning. The research spans both theoretical contributions—such as optimality conditions and bounds—and practical applicability, particularly in high-tech sectors with long lead times and customization requirements. Dr. Fleuren completed his doctoral studies at Tilburg University in January 2025, contributing significantly to the field through his dissertation on stochastic approaches in production-inventory planning. While no formal scientific awards are listed, his research outputs have been published in top-tier journals such as International Journal of Production Economics and Omega–International Journal of Management Science . He is actively involved in teaching courses such as Supply Chain Analytics and Introduction to Data Analysis. As a recent PhD graduate, he may be mentoring students informally, though no formal advisees are listed. His research has been supported through collaboration with industrial partners and academic grants, likely via CentER and the Operations Research Center at Tilburg University. Dr. Fleuren is affiliated with the Operations Research Center at TiSEM, where he contributes to a vibrant research environment focused on quantitative methods in economics and management. His ongoing work continues to advance methodologies for decision-making under uncertainty in complex, real-world supply chains.

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.

John M. CarrollView profile

Professor

• Human-Computer Interaction
• Community Informatics
• Collaborative Systems
• +6 more

John M. Carroll is a Professor at The Pennsylvania State University , affiliated with the College of Information Sciences and Technology . He co-directs the Collaboration and Innovation Laboratory and leads the Center for Human-Computer Interaction . Secondary appointments span Computer Science and Engineering , Learning, Design and Technology , and Psychology . Education : Mathematics and Information Science (undergraduate), Experimental Psychology (Ph.D.) Research Focus : Human-Computer Interaction (HCI), community informatics, scenario-based design, and minimalist instructional models. Key Projects : Mobile timebanking systems, smart city initiatives, community data analytics, and accessibility technologies for visually impaired users. Scientific Awards include lifetime honors from ACM, IEEE, and AAAS. He has led NSF-funded projects on collaborative sensemaking, educational technology, and disaster response systems. His work bridges social theory, design practice, and computational innovation.

Paula FikkertView profile

Professor

• Phonology
• First Language Acquisition
• Language Development
• +5 more

Paula Fikkert is a Professor of Language Acquisition and Phonology at Radboud University Nijmegen, where she is affiliated with the Centre for Language Studies and the Department of Modern Languages and Cultures within the Faculty of Arts. She currently serves as Dean of the Faculty of Arts and is a member of the Board of Deans at Radboud University. Her educational background includes a master's degree from the University of Groningen and a PhD from Leiden University (1994, cum laude), for which she received the AVT dissertation prize for the best dissertation in linguistics. Her doctoral work focused on "On the acquisition of prosodic structure." Professor Fikkert's research primarily investigates the acquisition of phonological representations in the lexicon and their role in speech perception and production. She explores how phonological representations mediate between acoustic signals and meaning in speech perception, and between meaning and articulatory output in speech production. Her work addresses fundamental questions about how babies learn language, how they process sounds and words, and how they store this information in their mental dictionaries. A significant portion of her research focuses on early indicators of developmental language problems and how children learn to monitor their own speech and that of others. Her research program has revealed important insights into language acquisition through behavioral and neurocognitive methods conducted at the Baby Research Center (BRC). She has contributed to several important databases of spontaneous speech, including CLPF for typically developing children, IPROSLA for children acquiring sign language, and VALID for children with speech disorders. Professor Fikkert has received numerous prestigious awards throughout her career, including: AVT dissertation prize for best linguistics dissertation Neil and Saras Smith Medal for lifetime achievement in the scholarly study of linguistics (2024) Synergy Award for research on phonology As a principal investigator, Fikkert has led significant research projects, including serving as PI in the BRC-lab and leading the research for the Radboud Language Development Fund established by Kino Jansonius. She previously held an Innovation Grant from NWO (2002-2007) and has been involved in numerous collaborative research projects with international partners. Her leadership extends to administrative roles, having served as research director of the Centre for Language Studies (CLS) at Radboud from 2011 to 2015, and as a member of the Humanities Board and later the Social Sciences and Humanities board of NWO. Professor Fikkert leads the First Language Acquisition research group at the Baby and Child Research Center (BRC), which conducts scientific research on children from pregnancy to age six. The BRC has three locations on the Radboud University campus and investigates the development of language, social interaction, thinking, and well-being in mothers and children. Her work has practical applications in early identification of language development disorders and developing interventions to support children with language acquisition challenges.