David Bamman is an Associate Professor in the School of Information at UC Berkeley, specializing in applying Natural Language Processing (NLP) and machine learning to cultural and social science questions. He leads research in born-literary NLP, computational humanities, and cultural analytics, with affiliated roles in EECS, Linguistics, and Computational Precision Health. Bamman holds degrees from Carnegie Mellon (Ph.D., 2015), Boston University (M.A., 2006), and University of Wisconsin-Madison (B.A., 1998). His work is supported by NEH, NSF, and industry grants. Educations: Ph.D. in Computer Science (2015), Carnegie Mellon University M.A. in Applied Linguistics (2006), Boston University B.A. in Classics (1998), University of Wisconsin-Madison Research Interests: NLP for underserved domains (e.g., literature, social media), coreference resolution, cultural analytics, and computational methods for studying literature and culture. Projects include LitBank and BookNLP datasets. Grants & Awards: Hellman Fellow (2019), Amazon Research Award (2017), NSF CAREER Award, and NEH funding. Teaching: Courses include Natural Language Processing (Info 159/259), Computational Humanities (INFO 190), and Applied NLP (INFO 256). His research group explores topics like racial representation in high school literature, Hollywood diversity metrics, and the sociocultural implications of LLMs. Bamman advises multiple PhD students and collaborates on datasets like CMU Book Summaries and 11K Latin Books.
Karsten Lambers is Professor of Digital and Computational Archaeology at the Faculty of Archaeology, Leiden University, where he leads research and teaching in the application of computational methods to archaeological data. His work integrates machine learning, remote sensing, text mining, and citizen science to advance archaeological prospection and heritage management. He is affiliated with the Department of Archaeological Sciences and plays key roles in research groups and university-wide initiatives such as SAILS and ARCHON. His research interests span Digital Archaeology , Machine Learning in Archaeology , Remote Sensing , Geoarchaeology , and Human-Environment Interaction . He investigates how computational tools can extract meaningful archaeological information from large datasets, including LiDAR imagery and excavation reports. His fieldwork spans Central Europe and Latin America, with a focus on prehistoric landscapes and cultural heritage. The analysis of his recent publications reveals a strong trend toward automated detection using deep learning (e.g., R-CNN, WODAN), named entity recognition in archaeological texts (e.g., ArcheoBERTje), and citizen science integration for data validation. His work bridges archaeology with computer science, geomatics, and environmental science, emphasizing interdisciplinary collaboration and methodological rigor. His scientific awards include: Best Thesis Award (University of Zurich, 2005) EUROPA NOSTRA Award (2020, 2022) Membership in the German Archaeological Institute (since 2022) Lambers actively supervises students and leads major research projects such as ABMA, EXALT, and Heritage Quest. He has secured substantial research funding and collaborates widely with computer scientists, geophysicists, and palaeoecologists. His teaching includes digital methods, modeling, and simulation, often linked to ongoing research. He has also contributed to open educational resources and digital textbooks in archaeology. He leads or participates in several research labs and teams, including the Digital Archaeology Research Group (which he chairs), the Heritage Quest citizen science project, and interdisciplinary teams focusing on alpine terraces and Iraqi prospection. His work emphasizes the integration of digital tools into practical archaeological workflows, advocating for complementary human-computer strategies.
Verena Zimmermann serves as Assistant Professor (Tenure Track) for Security, Privacy and Society at ETH Zurich within the Department of Humanities, Social and Political Sciences. She leads the Security, Privacy and Society research group, focusing on human-centered approaches to safety, IT security, and privacy challenges in emerging technologies. Her academic foundation includes a PhD in Usable Security from TU Darmstadt, where her dissertation From the Quest to Replace Passwords towards Supporting Secure and Usable Password Creation earned dual awards from the German Association for Data Protection and Data Security (GDD) and the Ernst-Ludwigs-Hochschulgesellschaft. Zimmermann's research pioneers the shift from viewing humans as security vulnerabilities to recognizing them as integral solutions. Her work spans password security, phishing interventions, smart home privacy, and cybersecurity education, consistently applying human factors principles to design systems that align with natural user behavior. Current projects explore emotional dimensions of security engagement, quantum governance frameworks, and LLM-related privacy concerns through interdisciplinary lenses combining computer science, psychology, and safety science. Recent publications reveal strong thematic trends toward understanding user motivations in security behavior, developing personalized training through augmented reality and adaptive systems, and translating safety science principles to cybersecurity incident management. Her work increasingly addresses societal implications of emerging technologies like quantum computing and generative AI. Her distinguished recognitions include: GDD Dissertation Award for Usable Security research Ernst-Ludwigs-Hochschulgesellschaft Dissertation Award IANUS Award (2nd place) for Moving from a 'Human-as-Problem' to a 'Human-as-Solution' Cybersecurity Mindset Zimmermann actively mentors through ETH's Human-Centered Security and Privacy Lab while collaborating internationally with institutions including ATHENE (German National Center for Applied Cybersecurity), Abertay University's Cybersecurity Division, and the Safety Science Innovation Lab. Her research receives support from Swiss and European funding bodies focused on privacy-preserving technologies and organizational security behavior. At ETH Zurich, she directs the Security, Privacy and Society group which employs design thinking, LEGO Serious Play, and mixed-methods research to tackle real-world security challenges. The team partners with industry stakeholders to develop practical solutions for phishing resistance, smart home privacy, and cybersecurity education while maintaining strong ties to the Research Training Group 2050 Privacy and Trust for Mobile Users.
Professor Sara Baker is a Professor of Developmental Psychology and Education at the University of Cambridge's Faculty of Education and a Fellow at Darwin College, where she served as Vice Master from 2021-2024. She is also a 2022 Senior Fellow in the Science of Learning with UNESCO-IBE/IBRO. Her work bridges cognitive science and educational practice, focusing on how children develop executive functions and self-regulation skills. Baker leads the Early Years Library project, co-founded the Research Centre for Play in Education, Development and Learning (PEDAL), and is a founding member of the Global Executive Functions Initiative. Sara Baker specializes in the science of learning, with research aimed at improving children's lives by identifying factors at home and school that support their agency over learning. Her work emphasizes developing executive functions and self-regulation through playful learning approaches. She uses lab-based experiments and collaborates with educators to translate cognitive science research into educational contexts. Her research spans multiple countries including the UK, USA, Mexico, Denmark, Slovakia, South Korea, Ghana, Rwanda, Nigeria, Kenya, South Africa, and more, reflecting a strong commitment to culturally relevant and globally applicable educational practices. Analysis of Professor Baker's recent publications reveals a strong focus on executive functions, self-regulation, and playful learning across diverse cultural contexts. Her work increasingly addresses cultural adaptation of assessment tools and educational practices, particularly for Global Majority countries. There's a clear trajectory from basic cognitive research toward practical applications in educational settings, with growing emphasis on teacher training, culturally relevant assessment, and the role of play in early childhood development. Her interdisciplinary approach connects developmental psychology, educational theory, and practical classroom applications. 2022 Senior Fellow in the Science of Learning with UNESCO-IBE/IBRO Professor Baker leads the doctoral program in the Faculty of Education and serves as an Academic Project Director in the School of Humanities and Social Sciences. She is the Cambridge academic lead on the Close the Gap partnership between Cambridge and Oxford, focused on postgraduate widening participation. Her research has been funded by prestigious organizations including the Newton Trust, Cambridge Humanities Research Grant, Economic and Social Research Council, LEGO Foundation, Nuffield Foundation, and Office for Students/Research England. She actively supervises doctoral students and seeks highly motivated candidates for October 2026 entry whose research aligns with her focus areas. Professor Baker co-founded and is actively involved with the Research Centre for Play in Education, Development and Learning (PEDAL), which investigates how children's play affects their development. She leads the Early Years Library project, a curated collection of evidence-based practices for early years educators, and is a founding member of the Global Executive Functions Initiative. Her work with the Connections international professional learning network focuses on self-regulation, while the Close the Gap project addresses widening participation in postgraduate education between Oxford and Cambridge.
Shiri Azenkot is an Associate Professor at the Jacobs Technion-Cornell Institute at Cornell Tech and Cornell University, affiliated with the Information Science Department and Technion’s Computer Science Department. Her research focuses on accessibility innovations in emerging technologies, particularly addressing needs of people with vision impairments and neurodiverse populations. She holds a PhD from the University of Washington, advised by Richard Ladner and Jacob Wobbrock, and has been recognized with prestigious awards including the NSF Graduate Research Fellowship. Education: PhD in Computer Science & Engineering from University of Washington (advisors: Richard Ladner, Jacob Wobbrock). Research interests include VR/AR accessibility, assistive technology design, inclusive education tools, and ethical AI applications. Current projects explore social VR avatars for invisible disabilities, AR navigation aids, and AI moderation systems against ableist hate speech. Her work is funded by NSF, AOL, Verizon, and Facebook. Recent publications address video accessibility for ADHD users, AI-driven scene descriptions for blind users, and tactile learning materials co-designed with educators. She leads the XR Access initiative promoting inclusive virtual/augmented reality. Awards include the UW Graduate Medal (2020), NSF CRII Award (2017), and AT&T Labs Fellowship (2014). Her research bridges academic innovation with industry impact through collaborations with tech companies and disability advocacy groups.
Karin Allor Pfeiffer is a Professor in the Department of Kinesiology at Michigan State University (MSU) and Director of the Institute for the Study of Youth Sports. She holds additional membership in the Center for Physical Activity and Health. With a Ph.D. from MSU, her research focuses on physical activity measurement methodologies and population health interventions, particularly among children and adolescents. Her work addresses obesity prevention, environmental design impacts on activity levels, and sociocultural factors influencing youth sport participation. Education: Ph.D. in Kinesiology from Michigan State University Her research interests emphasize: - Quantitative methods for physical activity assessment - Schoolyard redesign strategies and their health impacts - Cardiometabolic risk factors in pediatric populations - Longitudinal tracking of physical fitness and health outcomes Recent work explores accelerometer fragmentation metrics, GPS-linked activity tracking, and disparities in sedentary behavior across demographic groups. She has pioneered interdisciplinary approaches integrating spatial analysis, wearable technology, and policy evaluation. Key contributions include developing the Observational System for Recording Physical Activity in Children and advancing consensus methods for accelerometer data interpretation. Her studies frequently highlight socioeconomic and environmental determinants of health behaviors. Dr. Pfeiffer collaborates with public health agencies and urban planners to translate research into actionable policies. Her lab focuses on scalable interventions for underserved communities, leveraging community-engaged methods to address greenspace accessibility and safety concerns.
Felicity McArdle is a Professor in the Department of Early Childhood Education within the Faculty of Education at Queensland University of Technology. With a distinguished career spanning over two decades, her work centers on reimagining early childhood pedagogy through critical lenses of social justice, art education, and play-based learning. Her research has significantly influenced Australian early childhood policy and practice. McArdle's research interests demonstrate a consistent commitment to transformative education. She critically examines how art and play function as vehicles for social justice, challenging neoliberal discourses in early childhood education. Her work on refugee children's artistic expression and anti-bias curriculum development reveals her dedication to equity-oriented pedagogy. Through collaborative drawing methodologies and visual research approaches, she has pioneered innovative ways of understanding children's perspectives. Her publication trends reveal a sophisticated evolution from foundational work on visual arts in education (2001-2010) toward increasingly critical examinations of power, policy, and social justice (2011-2021). The consistent citation impact of her work—particularly her 2002 paper 'Early Childhood Art Education: A Palimpsest' with over 13,000 citations—demonstrates her field-defining contributions to reconceptualizing art education as critical praxis. McArdle has held significant editorial roles including co-editing the influential 2013 volume 'Young Children, Pedagogy and the Arts' and serving on the editorial board of Australian Journal of Early Childhood. Her collaborations with leading scholars like Susan Grieshaber, Jennifer Sumsion, and Linda Knight have produced seminal work on intentional teaching and play-based learning. Her research methodology expertise centers on visual and arts-based approaches, particularly collaborative drawing techniques that engage children as active research participants. This methodological innovation reflects her commitment to ethical research practices that honor children's agency while generating meaningful insights about early childhood experiences.
Katherine Isbister is a full professor in the Department of Computational Media at the University of California, Santa Cruz, where she directs the Center for Computational Experience. She was previously an associate professor jointly appointed between the Computer Science department at New York University’s Tandon School of Engineering and the NYU Game Center, and served as the founding Research Director of the Game Innovation Lab at NYU. Her research lies at the intersection of Human-Computer Interaction and digital games, focusing on emotion, social connection, and playful experiences. Key research themes include emotion in games , social play , fidget technologies , social VR , and digital characters . Her work combines technical prototyping, design research, and empirical evaluation to understand how interactive systems can support emotional and social experiences. Her publications span top venues such as CHI, DIS, and IEEE Transactions on Affective Computing. Trends in her recent work show a strong emphasis on embodied interaction, affective design, and socio-technical systems for emotional regulation and social connection. She explores how movement, touch, and presence in virtual spaces can enhance human experience. MIT Technology Review TR100 Young Innovator (1999) Best Paper Award, ACM CSCW (2018) New Voices New Visions Award (for SimWorks art series) She has advised numerous students and led research projects involving social wearables, movement-based games, and mental health interventions. Her lab has received recognition from media outlets including NPR, Scientific American, and The Guardian. She has also collaborated with industry partners such as Microsoft, Electronic Arts, and Ubisoft. She leads the Center for Computational Experience at UCSC and has previously directed the Game Innovation Lab at NYU. Her team has produced over 100 peer-reviewed publications and several exhibition-ready games and art installations.
Raquel Fernández is Full Professor of Computational Linguistics and Dialogue Systems at the University of Amsterdam, where she leads the Dialogue Modelling Group at the Institute for Logic, Language & Computation (ILLC). As Vice-Director for Research at ILLC and a Fellow of the ELLIS Society, she bridges computational linguistics, cognitive science, and artificial intelligence through her research on language use in multimodal and conversational contexts. PhD in Computational Linguistics from King's College London Prior research positions at University of Potsdam and Stanford University's CSLI Her work explores how cognitive constraints, social interaction, and perception shape language use, with a focus on: Visually-grounded language processing Multimodal dialogue modeling Model uncertainty and calibration Language grounding in multimodal data Language learning and semantic change Dialogue reference resolution Recent publications analyze multimodal reasoning limitations, cross-lingual knowledge consistency, and uncertainty modeling in dialogue systems. She has received multiple accolades including an ERC Consolidator Grant , NWO VENI/VIDI/Aspasia fellowships , and EMNLP/GenBench awards . Outstanding Paper Award (EMNLP 2023) Best Data Award (GenBench Workshop 2023) ELLIS Society Fellow ERC Consolidator Grant #819455 recipient NWO VENI/VIDI/Aspasia awardee As a leader in academic service, she serves on the SIGDAT Executive Committee and chairs multiple conference committees. Her lab develops models for multimodal dialogue, visual storytelling, and grounded language understanding.
Elaine J. Francis is a Professor of English and Linguistics at Purdue University, where she also serves as the Associate Head of the Department of English. She holds affiliate appointments in the Department of Linguistics and the Department of Speech, Language, and Hearing Sciences. At Purdue, she directs the Experimental Linguistics Lab and teaches linguistics courses at both graduate and undergraduate levels. Francis completed her B.A. in Linguistics at the College of William and Mary in 1993, followed by her M.A. (1995) and Ph.D. (1999) in Linguistics at the University of Chicago under the direction of Salikoko Mufwene. Her dissertation examined variation among members of the same lexical category in English using Sadock's Autolexical Grammar framework. Prior to joining Purdue in 2003, she served as an Assistant Professor at the University of Hong Kong from 1999 to 2002, where she collaborated with Stephen Matthews on research concerning syntactic categories and relative clauses in Cantonese. Her research focuses on syntax and its interfaces with semantics, discourse information structure, and language processing in production and comprehension. Francis employs experimental methods to investigate syntactic, semantic, discourse-pragmatic, and cognitive factors underlying the grammar and usage of complex sentence structures. Her specific interests include word order alternations, filler-gap dependencies, resumptive pronouns, relative clauses, grammatical categories, and syntactic alternations. She has published extensively in top linguistics journals including Language and Cognition, Glossa Psycholinguistics, Linguistics, Lingua, Cognitive Linguistics, and the Journal of Psycholinguistic Research. Analyzing her recent publications reveals a consistent focus on experimental approaches to syntactic phenomena. Her work demonstrates a strong interest in gradient acceptability, syntactic priming, cross-linguistic comparison (particularly involving English and Cantonese), and the relationship between grammatical theory and language processing. Her 2022 book Gradient Acceptability and Linguistic Theory represents a major contribution that synthesizes experimental findings with theoretical linguistics frameworks. Francis plays an active role in the broader linguistics community. She regularly teaches short courses at the Linguistic Society of America Linguistic Institutes, serves on the LSA Ethics Committee, and is on the editorial board of Glossa Psycholinguistics. She has also edited several books and special journal issues, including Mismatch: Form-Function Incongruity and the Architecture of Grammar (2003) and Polymorphous Linguistics: Jim McCawley's Legacy (2005). As an educator and administrator, Francis has supervised numerous graduate students and currently serves as Associate Head of the Department of English at Purdue. Her Experimental Linguistics Lab provides research opportunities for students interested in the intersection of theoretical syntax and experimental methodology. While she recently announced she will not be accepting new graduate students for the 2025-2026 cycle, her established mentorship record demonstrates her commitment to training the next generation of linguists. The Experimental Linguistics Lab, which she directs, serves as a hub for research combining theoretical linguistics with experimental methods. Her collaborative work extends across disciplines, including collaborations with researchers in speech-language pathology, cognitive science, and computational linguistics, reflecting the interdisciplinary nature of modern linguistic research.
Andre Wibisono serves as Assistant Professor in Yale University's Department of Computer Science with a secondary appointment in Statistics & Data Science, joining the faculty in 2021 after postdoctoral research at University of Wisconsin-Madison and Georgia Institute of Technology. His educational background includes: Ph.D. in Computer Science, UC Berkeley M.A. in Statistics, UC Berkeley M.Eng. in Computer Science, MIT S.B. in Mathematics and Computer Science, MIT Wibisono's research focuses on algorithm design for machine learning through optimization, sampling, and game theory , leveraging dynamical systems and information theory to develop accelerated discrete-time algorithms from continuous dynamics. His work provides theoretical foundations for efficient machine learning systems with applications in generative modeling and constrained optimization. Recent publications (2023-2025) demonstrate consistent innovation in Hamiltonian-based optimization , constrained-space sampling , and min-max game convergence , characterized by rigorous mathematical analysis connecting continuous dynamics to discrete algorithms. Key trends include randomized integration for acceleration, phi-divergence convergence guarantees, and symplectic geometry applications to mirror descent. Scientific recognition includes: NSF CAREER Award for developing algorithmic frameworks bridging continuous and discrete dynamics He actively mentors current students (Siddharth Mitra, Kaylee Yang, Jane Lee, Qiang Fu, Peter Wang) and has guided two postdocs to faculty positions. Research is funded through the NSF CAREER award and collaborative CIF grants focused on Hamiltonian dynamics for sampling and optimization. His Yale research group develops theoretical foundations for next-generation machine learning algorithms, emphasizing mathematical rigor in optimization and sampling with applications to generative modeling and constrained inference problems.
Erik Learned-Miller is a Professor and Chair of the Faculty at the Manning College of Information and Computer Sciences (CICS), University of Massachusetts Amherst. He is based in the Department of Computer Science and leads the Computer Vision Lab, with strong affiliations to the Center for Data Science. His work bridges machine learning and computer vision, focusing on foundational and ethical aspects of visual recognition systems. Education: PhD in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2002 MS in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 1997 BA in Psychology, Yale University, 1988 Learned-Miller's research centers on machine learning methods for computer vision problems, particularly in scenarios with limited labeled data. His work includes one-shot learning , face detection and recognition , image and video segmentation , joint image alignment , and text recognition . He emphasizes unsupervised, self-supervised, and semi-supervised learning paradigms, and is actively involved in addressing societal concerns around the regulation of face recognition technology. His contributions have had a major impact on the computer vision community, most notably through the creation of widely used benchmarks such as Labeled Faces in the Wild and the Face Detection Database and Benchmark , which have become standard evaluation tools in the field. Scientific Awards and Honors: NSF CAREER Award (2006) Mark Everingham Award (2019) Microsoft-MIT Graduate Student Fellowship Learned-Miller has played significant roles in the academic community, including serving as Program Chair for the 2015 Conference on Computer Vision and Pattern Recognition (CVPR) and as a member of the editorial board of the Journal of Machine Learning Research . He has secured competitive research funding, including the NSF CAREER award, supporting his long-term research agenda. While specific advisees are not listed, he mentors graduate students through his lab and departmental roles. He leads the Computer Vision Lab at UMass Amherst, a research group focused on advancing the state of the art in visual understanding through machine learning. The lab is part of the broader research ecosystem within CICS and collaborates with the Center for Data Science, contributing to interdisciplinary efforts in AI and data-driven science.
Yongmin Liu is a Professor in Mechanical and Industrial Engineering and Electrical & Computer Engineering at Northeastern University, and a member of the Cross-College Magnetics Center. He holds a PhD in Applied Science and Technology from UC Berkeley (2009), with earlier degrees from Nanjing University. His research focuses on nano-optics, metamaterials, plasmonics, and their applications in optical devices and systems. His interdisciplinary work bridges engineering, physics, and AI, with notable contributions to metasurface design and optical neural networks. Education: PhD, Applied Science and Technology, UC Berkeley (2009) M.S. and B.S., Physics, Nanjing University (2003, 2000) Research Interests: Nano-optics, nanoscale materials engineering, metamaterials, plasmonics, and applied physics. His group develops novel optical materials and devices for applications like super-resolution imaging, efficient light harvesting, and biomedical detection. Recent projects include AI-driven photonic materials design and meta-optical neural networks. Key Achievements: Recipient of the Søren Buus Outstanding Research Award (2024) NSF CAREER Award (2017) and ONR Young Investigator Award (2016) Elected SPIE Fellow (2023) and Optica Fellow (2023) Lab & Collaborations: Head of the Yongmin Liu Research Group, collaborating with institutions like Georgia Tech and Purdue University. Recent grants include a $1.5M NSF DMREF grant for AI-driven photonic materials and a $468K NSF grant for meta-optical neural networks.
Dr. Michelle Cannon is a Lecturer in Digital Arts and Media Education at the University College London (UCL) Institute of Education's Culture, Communication & Media department. She co-leads the Digital Storytelling module and serves as a dissertation supervisor for the MA Digital Media: Education program. Co-investigator, ESRC/AHRC-funded Play Observatory project Editorial board member: Film Education Journal, Learning, Media and Technology Executive Committee Member, Media Education Association International collaborations: British Film Institute, EU cultural agencies Her research explores digital media production in educational settings, focusing on film literacy, postdigital theory, and pandemic-related learning adaptations. Utilizing ethnographic and participatory visual methods, she investigates how children's creative practices intersect with social and cultural learning. Recent publications highlight her work on: Digital storytelling and transludic practices in pandemic contexts Ethnographic studies of postdigital play environments Critical media education frameworks Comparative analysis of European film literacy programs Scientific contributions include: ESRC/AHRC grant for children's play research International film literacy framework development Leadership in EU-funded scoping studies She trains teachers in digital media integration and has evaluated school film programs for the BFI. Her longitudinal study on lower-achieving children's learning experiences included documentary film production.
Valentina Mazzucato is Professor of Globalisation and Development at the Faculty of Arts and Social Sciences, Maastricht University, where she teaches and leads research in transnational migration and development. She founded and directed the research programme on Globalisation, Transnationalism and Development (2012–2020), co-founded the MA Globalisation and Development Studies, and led the development of the interdisciplinary BSc Global Studies. She is a member of the Royal Netherlands Academy of Arts and Sciences (KNAW) and has held leadership roles in major research initiatives including the ERC Consolidator Grant project MO-TRAYL. Her educational background includes a BA in Political Science and French Literature from Williams College, an MSc in Agricultural Economics from Michigan State University, and a PhD cum laude from Wageningen Agricultural University on indigenous soil and water conservation in Burkina Faso. Her research focuses on transnational migration between Africa and Europe, particularly the socio-economic and cultural impacts on migrants, their families, and communities. She employs mixed methods and multi-sited research designs, pioneering the simultaneous matched sample methodology. Her recent work explores transnational youth mobility, return visits, remittances, and temporalities of migration. The articles from 2024–2025 reveal a strong thematic consistency in migrant youth, transnational identity, methodological innovation, and policy implications, reflecting her leadership in interdisciplinary migration scholarship. ERC Consolidator Grant (2017–2023) for MO-TRAYL project Elected member of the Royal Netherlands Academy of Arts and Sciences (KNAW), 2019 Prof. Mazzucato has secured multiple international grants from NWO, NORFACE, and the ERC, enabling her to build transnational research teams and mentor PhD candidates and early-career researchers. She supervises Bachelor’s and Master’s theses and externally examines PhDs internationally. She is actively involved in policy engagement, having advised Queen Beatrix and participated in EU and NGO forums on migration and development. She also co-created a play with Ghanaian migrants to translate research into public dialogue. She leads the Transnational Links and Livelihoods Group and collaborates across institutions including Princeton University (Center for Migration and Development), African universities, and policy organizations. Her work bridges academic research, teaching innovation, and societal impact.
