جست‌وجوی استاد و پژوهشگر

Antoine Bosselutمشاهده پروفایل

استادیار

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Antoine Bosselut is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he leads the EPFL NLP group. His research focuses on developing AI reasoning agents that can model, represent, and reason about human and world knowledge, with applications in health, education, and global fairness. His research interests span multiple critical areas in modern AI: LLM Representations of Knowledge: Understanding what language models know and how they represent that knowledge internally Reasoning Algorithms: Developing methods to improve LLMs' reasoning capabilities through symbolic systems, neuroscience, and cognitive science Large-scale AI Development: Creating open-source foundation models with multilingual capabilities AI Democratization: Ensuring equitable access to AI technologies across different cultural and regulatory contexts His recent publications reveal a strong focus on the intersection of language models and cognitive science, with multiple studies examining how LLMs align with human cognition. He's also deeply engaged in practical applications of NLP technology, particularly in education and multilingual settings, as evidenced by his work on evaluating AI's impact on higher education and developing culturally-aware language models. His scientific achievements have been recognized with several prestigious awards: Outstanding Paper Award at NAACL 2025 ELLIS Scholar designation in 2024 Outstanding Paper Award at ACL 2023 Inclusion in Forbes 30 Under 30 list for Science & Healthcare in 2021 Bosselut actively mentors numerous PhD students across diverse NLP research areas and has secured significant recognition for his work in both academic and media circles. His lab has been featured in major publications including Communications of the ACM, The Atlantic, and Quanta Magazine, highlighting the societal impact of his research on commonsense reasoning and AI capabilities.

Robert Westمشاهده پروفایل

دانشیار

• Natural Language Processing (NLP)
• Machine Learning
• Computational Social Science
• +۴ مورد دیگر

Robert West is an Associate Professor at EPFL (École polytechnique fédérale de Lausanne) in the School of Computer and Communication Sciences , leading the Data Science Lab (dlab) . His research focuses on Natural Language Processing , Machine Learning , and Computational Social Science , analyzing human-generated data from the web, social media, and online platforms. Education : PhD in Computer Science (2016) - Stanford University MSc in Computer Science (2010) - McGill University BSc in Computer Science (2007) - Technische Universität München Research Interests : West develops algorithms for analyzing large-scale web data, with emphasis on multilingual NLP , social network analysis , and AI ethics . His work bridges machine learning with social science to understand digital human behavior. Scientific Awards : ICWSM’22 Adamic–Glance Distinguished Young Researcher Award Google Faculty Research Award Facebook Research Award Multiple Outstanding Paper Awards at ICWSM and WWW Advising & Grants : He advises 12 PhD students and has secured funding from the Swiss National Science Foundation , Swiss Data Science Center , and industry partners. His lab maintains collaborations with Microsoft Research and CROSS . Labs & Collaborations : West leads the Data Science Lab at EPFL, which focuses on web-scale data analysis , privacy-preserving machine learning , and AI for social good . The lab develops tools like Wikispeedia and Quotebank for public data exploration.

Konrad Schindlerمشاهده پروفایل

استاد

• Photogrammetry
• Remote Sensing
• Computer Vision
• +۳ مورد دیگر

Prof. Konrad Schindler holds the position of Full Professor at the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich. He is also the Head of the Institute of Geodesy and Photogrammetry (IGP), leading research and educational activities in geomatics and computer vision. His career spans roles as a Photogrammetric Engineer, scientific assistant, postdoc researcher, and academic faculty across institutions including Graz University of Technology, Monash University, and TU Darmstadt before joining ETH Zürich in 2010. Education: Undergraduate studies in Geodesy (1992–1995), Graz University of Technology, Austria MEng in Photogrammetry and Geoinformation (1995–1999), Vienna University of Technology, Austria PhD in Computer Science (2001–2003), Graz University of Technology, Austria Research focuses on Photogrammetry , Remote Sensing , Computer Vision , and Image Understanding with interdisciplinary applications in environmental monitoring, geospatial analysis, and disaster response. He develops computational methods for 3D reconstruction, fusion of multi-modal data, and AI-driven solutions for satellite imagery interpretation. His work bridges geomatic engineering and machine learning to address challenges in urban mapping, climate modeling, and biological systems analysis. Publications reflect expertise in geospatial AI, diffusion models, and benchmarking datasets for disaster resilience. Notable works include Marigold (image analysis adaptation) and BRIGHT (building damage assessment). His research emphasizes practicality and scalability, such as affordable depth estimation and global biomass datasets. He has received the 2013 Marr Prize Honourable Mention (IEEE) and the 2012 U.V. Helava Award (ISPRS), alongside several Best Presentation Awards. His contributions span technical leadership, editorial roles (ISPRS Journal), and service to Swiss remote sensing commissions. Advising and grants: While no specific advisee names or grant details are listed, his career trajectory includes mentoring postdocs and junior faculty. He teaches advanced courses in Photogrammetry , Image Interpretation , and Machine Vision , integrating cutting-edge AI techniques into curricula. His research group collaborates on global-scale projects like canopy height mapping and satellite-based climate variable assessments. Labs/Teams: As Institute Head, he oversees the IGP lab at ETH Zürich, with prior affiliations including the Digital Perception Lab (Monash University) and the Computer Vision Lab (ETH Zurich). His work often involves multi-institutional collaborations focused on geospatial AI and environmental science.

Adrian Wellerمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Machine Learning
• Explainability
• +۹ مورد دیگر

Adrian Weller is a prominent researcher and academic at the University of Cambridge, serving as a Director of Research in Machine Learning within the Department of Engineering. He holds multiple significant leadership roles including Programme Director for Trust and Society at the Leverhulme Centre for the Future of Intelligence (CFI), and previously served as Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI. His work bridges theoretical machine learning research with practical applications and societal implications of artificial intelligence. Weller's research interests span a broad spectrum of AI and machine learning topics with a particular focus on ensuring beneficial societal outcomes. His work encompasses explainability, fairness, robustness, scalability, privacy, safety, and ethics in AI systems. He has made significant contributions to trustworthy machine learning, including developing frameworks for AI governance, certification, and human-AI collaboration. His research group actively investigates neuro-symbolic approaches, privacy-preserving techniques, and methods for improving the reliability and interpretability of AI systems. His recent publications demonstrate a strong trend toward addressing the practical challenges of deploying AI systems in real-world contexts, particularly focusing on certification frameworks, governance mechanisms, and human-centered approaches. His work spans theoretical advances in machine learning architectures while maintaining a strong connection to societal impact, with publications appearing in top venues across AI, machine learning, and interdisciplinary applications. Scientific Awards: MBE for services to digital innovation (2022 Queen's Birthday Honours) Turing AI Fellowship for Trustworthy Machine Learning Weller actively supervises a large group of PhD students and postdocs, with current students including Juyeon Heo, Yanzhi Chen, Katie Collins, Isaac Reid, Yichao Liang, Herbie Bradley, and Shoaib Siddiqui. His former students have gone on to positions at leading institutions including Google DeepMind, ETH Zurich, NYU, and MPI-IS Tübingen. He has served on numerous advisory boards including the Centre for Data Ethics and Innovation, UNESCO's expert group on AI ethics, and the World Economic Forum's Global Future Council on AI. His research has been supported through his Turing AI Fellowship and various collaborative projects focused on safe and ethical AI development. Weller leads a vibrant research group focused on trustworthy machine learning, which actively organizes workshops and conferences including ICML 2024 (where he served as Program Chair), multiple workshops on responsible AI, and events through the ELLIS network. His group collaborates extensively across disciplines, working with researchers in computer science, social sciences, law, and policy to address the multifaceted challenges of developing beneficial AI systems.

Aniket Kitturمشاهده پروفایل

استاد

• AI-Augmented Cognition
• Collective Intelligence
• Social Computing
• +۷ مورد دیگر

Aniket (Niki) Kittur is a Professor in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University's School of Computer Science. His research focuses on AI-augmented cognition, exploring how humans and computational systems can partner to accelerate knowledge acquisition and innovation. With over 100 peer-reviewed publications and 17 best paper awards or honorable mentions, Dr. Kittur has established himself as a leader in human-computer interaction and social computing. Dr. Kittur's research spans multiple interconnected areas focused on enhancing human cognition through technology. His work on crowd-augmented cognition examines how crowds and computation can collectively enhance human intellect. In social computing, he investigates how sociotechnical architectures can motivate and coordinate large groups for complex tasks. His research in data visualization and sensemaking explores how people collect, organize, and make decisions with online information. Most recently, his work has shifted toward LLM-augmented cognition, investigating how humans and large language models can work together in partnership to achieve better decisions and greater creativity than either could alone. Dr. Kittur's publications reveal a consistent trajectory toward increasingly sophisticated human-AI collaboration systems. Early work focused on crowdsourcing complex tasks (CrowdForge, CrowdSynthesis), then evolved to knowledge acceleration systems (Knowledge Accelerator, Fuse), and has recently centered on LLM-integrated cognition (Selenite, InkSpire, BioSpark). His research consistently demonstrates practical impact, with systems influencing products used by millions and receiving coverage in major media outlets including Nature News, The Economist, and The Wall Street Journal. Kavli fellow NSF CAREER award recipient Allen Newell Award for Research Excellence Inductee into the CHI Academy 17 best paper awards or honorable mentions across his publications Dr. Kittur has advised numerous students, including Andrew Kuznetsov, and has secured major research funding from NSF, NIH, Google, Microsoft, Bosch, Toyota, and other organizations. His Skeema browser extension project, which addresses tab overload through innovative project-based organization, has shown remarkable user retention and represents a practical application of his research on knowledge acceleration. His work with industry partners has influenced products used by millions, including Semantic Reader, Google Shopping, and Wikipedia features.

Ceren Budakمشاهده پروفایل

دانشیار

• Computational Social Science
• Social Media Analysis
• News Media Production and Consumption
• +۷ مورد دیگر

Ceren Budak is an Associate Professor at the University of Michigan School of Information and holds a joint appointment as Associate Professor of Electrical Engineering and Computer Science in the College of Engineering. Her work bridges computer science, statistics, and social sciences through computational social science approaches. Her educational background includes a PhD in Computer Science from the University of California, Santa Barbara (2012) and a Bachelors degree in Computer Science from Bilkent University in Turkey (2007). Prior to joining the University of Michigan faculty, she was a Postdoctoral Researcher at Microsoft Research New York. Professor Budak's research centers on computational social science, with particular emphasis on analyzing large-scale datasets to address questions with social, political, and policy implications. Her work spans several interconnected domains: News Media Production & Consumption (examining bias in news outlets and reader preferences), Social Movements & Media (using social media data to study collective action), Social Networks (understanding information diffusion processes), and Measuring and Promoting the Quality of Online Discussions (developing tools to improve online conversations). She teaches SI 608 (Networks) and SI 618 (Data Manipulation and Analysis) at the School of Information. Her publication record demonstrates consistent contributions to understanding how online information ecosystems operate, with recent work focusing on AI-human collaboration, misinformation dynamics, social movement framing, and the application of computational methods to political communication. Her research shows a clear trajectory from foundational work on social network diffusion to increasingly sophisticated analyses of contemporary information challenges. Among her service activities, she has served as Registration chair for COSN (ACM Conference on Online Social Networks) 2015 and as Program Committee Member for numerous prestigious conferences including WWW, ICWSM, WebSci, AAAI, and others. She has also been involved in organizing the MSR NYC Data Science Seminar Series and instructing the Microsoft Research Data Science Summer School.

Yvonne Rogersمشاهده پروفایل

استاد

• Ubiquitous Computing
• Interaction Design
• Human-Computer Interaction
• +۱ مورد دیگر

Yvonne Rogers is a Professor of Interaction Design and Director of the UCL Interaction Centre (UCLIC), with a joint appointment as Deputy Head of the Department of Computer Science at University College London. She joined UCL in 2011 after holding professorships at the Open University (2006-2011) and Indiana University (2003-2006). Her pioneering work spans ubiquitous computing, interaction design, and human-computer interaction, with a current focus on human-centered AI. She co-authored the definitive 'Interaction Design' textbook (6 editions, 300,000+ copies) and serves as CTO of LetThink.com. Research interests center on designing technologies that enhance human cognition and daily activities: Ubiquitous Computing: Augmenting learning/work activities through pervasive technologies Human-AI Interaction: Developing AI systems that enhance human decision-making Health Technologies: Creating VR therapies and ADHD support systems Community Resilience: Designing tools for environmental monitoring and sustainable practices Publication analysis reveals three dominant trends: (1) VR applications for mental health (emotion regulation, ADHD support), (2) AI systems for cognitive augmentation, and (3) community-centered tools for healthcare/environmental challenges. Recent work demonstrates strong emphasis on vulnerable populations including children with ADHD, older adults, and postoperative patients. Major scientific recognition includes: International Member, National Academy of Engineering (2024) ACM SIGCHI Lifetime Research Award (2022) Royal Society Robin Milner Medal (2022) Royal Society Fellowship (2022) Microsoft Outstanding Collaborator Award MRC Suffrage and Science Award (2020) Triple Fellow status (ACM, BCS, CHI Academy) Advises PhD students including Leon Reicherts, Sheena Visram, and Tu Duong. Secured major grants including EPSRC Dream Fellowship on ageing/computing and led the Intel Collaborative Research Institute on Sustainable Connected Cities (2012-2018). Directs UCLIC research center and previously established the Pervasive Interaction Lab at Open University.

Lauren A. Delisioمشاهده پروفایل

دانشیار

• Special Education
• Inclusive Education
• Autism Spectrum Disorders
• +۵ مورد دیگر

Lauren A. Delisio is an Associate Professor of Special Education at Rider University's Department of Teacher Education. She has taught graduate and undergraduate courses in special education, inclusive practices, and assistive technology since 2015. Ph.D. in Exceptional Student Education (2015, University of Central Florida) Graduate Certificate in Autism Spectrum Disorders (2012, University of Central Florida) M.S. in Teaching (2005, Pace University) B.A. in Communications (2000, Rider University) Her research focuses on universal design for learning (UDL) , assistive technology , and inclusive education practices for students with autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), and intellectual disabilities. She has explored trauma-informed instruction, STEM accessibility, and evidence-based practices in inclusive classrooms. Her recent publications analyze UDL implementation, video prompting for independence, and pandemic impacts on inclusive education. She has received grants through the Department of Education's Office of Special Education Programs (OSEP) for Project LEAD and served as a doctoral intern with OSEP. Delisio has contributed to STEM research via video game integration for students with disabilities and supported alumni engagement through data collection. She collaborates with service providers, universities, and policymakers to improve educational outcomes for neurodiverse learners.

Paulo Bliksteinمشاهده پروفایل

دانشیار

• Technology in teaching and learning
• Learning design
• Computer modeling in Social and Behavioral Sciences
• +۶ مورد دیگر

Paulo Blikstein serves as Associate Professor of Communications, Media and Learning Technology Design at Columbia University. Previously, he was Assistant Professor of Education and (by courtesy) Computer Science at Stanford University and co-founded the Lemann Center for Brazilian Education (2008-2018). Education: Ph.D. in Learning Sciences, Northwestern University (2009) M.A. in Media Arts & Sciences, MIT Media Lab (2002) M.Eng. in Electronic Engineering, University of São Paulo (2000) B.S. in Metallurgical Engineering, University of São Paulo (1998) His research pioneers constructionist learning environments through digital fabrication, educational robotics, and tangible interfaces—focusing on equitable access for underserved communities. Inspired by Paulo Freire and Seymour Papert, he develops open-source tools like the GoGo Board robotics platform and leads the global FabLab@School initiative establishing fabrication labs in schools across four continents. Current work emphasizes multimodal learning analytics to study student interactions in maker-centered classrooms. Publications reveal strong focus on democratizing invention through maker education, with recurring themes in constructionist theory application, multimodal assessment, and context-specific technology adaptation. Brazilian education reform and low-cost computational solutions form significant threads, particularly in 2016-2017 publications. Scientific Awards: Two Google Faculty Awards National Science Foundation Early Career Award (highest U.S. government honor for early-career scientists) Blikstein directs the Transformative Learning Technologies Lab (TLTL) and co-founded Stanford's Center for Educational Entrepreneurship and Innovation in Brazil. His FabLearn conference established the first academic forum on Maker Movement applications in education. While specific grant details aren't listed, the NSF CAREER Award signifies major federal research funding. He spearheads the FabLab@School project deploying advanced fabrication labs in K-12 institutions worldwide and founded the FabLearn conference series. His work integrates teams of engineers, educators, and designers to create scalable solutions for resource-constrained learning environments.

Chaitanya Swamyمشاهده پروفایل

استاد

• Combinatorial Optimization
• Approximation Algorithms
• Algorithmic Game Theory
• +۴ مورد دیگر

Chaitanya Swamy is a Professor and University Research Chair in the Department of Combinatorics & Optimization at the University of Waterloo, Canada. His primary affiliation is within the Faculty of Mathematics, and he holds positions in both the Department of Combinatorics & Optimization and the School of Computer Science. He obtained his Ph.D. in Computer Science from Cornell University under the supervision of David Shmoys, followed by postdoctoral research at Caltech's Center for the Mathematics of Information. Swamy’s research focuses on algorithms, particularly in combinatorial optimization, approximation algorithms, algorithmic game theory, stochastic optimization, network design, scheduling, and online algorithms. His work spans theoretical contributions and practical applications, including algorithm design for facility location, network routing, and mechanism design. He has contributed to foundational results in approximation algorithms, such as the development of primal-dual methods and LP-rounding techniques. Swamy has held significant editorial roles, including as an associate editor for Discrete Optimization and SIAM Journal on Computing . He has organized major conferences like CanaDAM 2021 and sessions at ISMP 2018. His teaching record includes courses on combinatorial optimization, scheduling, and algorithmic game theory. He has advised numerous Ph.D. and Master’s students, many of whom have gone on to prestigious academic and industry positions. Swamy’s research has been recognized through awards for his students, including the University of Waterloo Alumni Gold Medal. He actively contributes to the academic community through committee work for conferences like STOC, APPROX, and SODA, and his publications reflect a deep engagement with both theoretical and applied aspects of algorithms and optimization.

Ira Kemelmacher-Shlizermanمشاهده پروفایل

استاد

• Computer Vision
• Computer Graphics
• Generative AI
• +۶ مورد دیگر

Ira Kemelmacher-Shlizerman is a Full Professor of Computer Science at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and Director of the UW Reality Lab. She also serves as a Principal Scientist at Google, where she leads the Shopping Gen AI visuals teams focusing on Virtual Try-On, 3D, and product videos. Her research spans computer vision, computer graphics, and Generative AI, with particular contributions to virtual try-on technology, 3D modeling, and augmented reality applications. Professor Kemelmacher-Shlizerman's research interests focus on Generative AI applications in visual computing. Her work bridges the gap between theoretical computer vision and practical applications, particularly in e-commerce and virtual reality. She has made significant contributions to virtual try-on technology, 3D editing with generative models, and AI applications for shopping experiences. Her research combines deep learning with traditional computer vision techniques to solve challenging problems in image and video synthesis. Her recent publications demonstrate a strong trend toward Generative AI applications for visual shopping experiences, virtual try-on technology, and 3D content creation. The work spans multiple top conferences including CVPR, SIGGRAPH, and ICCV, with a focus on practical applications of computer vision and graphics. Her research has evolved from foundational work in face reconstruction and aging to current applications in virtual shopping and 3D content generation. Google faculty award Madrona prize GeekWire Innovation of the Year Award Covers of CACM and SIGGRAPH Best student paper honorable mention at CVPR'21 Best demo runner up MobiSys'22 Senior member of IEEE Distinguished Member of ACM Professor Kemelmacher-Shlizerman has successfully tech-transferred multiple research projects to industry. She founded Dreambit, a startup acquired by Meta, and previously built and launched the Face Movies feature at Google. She currently leads Google's Shopping Gen AI visuals teams, focusing on 10x improvements to shopping journeys. Her UW Reality Lab serves as a hub for AR/VR research with industry partnerships. She has mentored numerous PhD students who have become researchers in both academia and industry, with several publications featuring student co-authors receiving recognition at top conferences. Professor Kemelmacher-Shlizerman leads the Graphics and Imaging Laboratory (GRAIL) and the UW Reality Lab, which focuses on augmented and virtual reality research with industry partnerships including Google. The labs work on cutting-edge projects in virtual try-on, 3D modeling, and immersive experiences, bridging academic research with real-world applications.

Bertrand Schneiderمشاهده پروفایل

دانشیار

• Assessment
• Cognitive Development
• Evidence-Based Intervention
• +۱۰ مورد دیگر

Bertrand Schneider is an Associate Professor of Education at Harvard University's Graduate School of Education (GSE). He holds a Ph.D. in Learning Sciences and Technology Design from Stanford University (2015) and previously served as a postdoctoral researcher at Stanford's Transformative Learning Technologies Laboratory. His research focuses on educational interfaces (e.g., augmented reality, tangible tools) and multimodal learning analytics, particularly in collaborative and informal learning environments. He investigates how technologies like gaze-tracking and motion sensors can assess student learning trajectories and improve instructional strategies in makerspaces and remote teaching contexts. Education : Ph.D., Learning Sciences and Technology Design, Stanford University (2015) Postdoctoral Researcher, Transformative Learning Technologies Laboratory, Stanford University Research Interests : Educational technologies (AR, tangible interfaces, multitouch) Multimodal data analysis (gaze, body movement, speech) Collaborative learning in formal/informal settings Remote teaching strategies using shared gaze visualizations AI applications in personalized feedback and misinformation discernment Key Contributions : Developed methodologies for capturing joint visual attention in collaborative learning Advocated for ethical implementation of multimodal learning analytics Explored AR's dual-edged impact on student engagement and collaboration Labs/Teams : Current research aligns with GSE's focus on innovative learning technologies Prior affiliation with Stanford's Transformative Learning Technologies Lab

• Artificial Intelligence
• Computational Game Theory
• Multi-Agent Systems
• +۴ مورد دیگر

Michael P. Wellman is a Professor of Computer Science and Engineering at the University of Michigan, specializing in computational game theory and its applications to economics and finance. He has advised 28 PhD graduates and currently mentors 6 students, emphasizing independent research and tailored advising approaches. His work focuses on multi-agent systems, strategic interactions, and agent-based modeling of financial markets. He holds the endowed Lynn A. Conway Professorship and created the Morris Wellman Faculty Development Professorship. His research group meets weekly for progress reports, paper discussions, and practice presentations. Wellman encourages internships, teaching experience, and conference participation (e.g., ICAIF, AAMAS, EC) to foster career readiness. His scientific contributions span empirical game-theoretic analysis (EGTA), market manipulation detection, and cybersecurity strategies. He prioritizes student independence, collaborative problem-solving, and ethical considerations in AI-driven financial systems.

Hyowon Gweonمشاهده پروفایل

دانشیار

• Computational Approaches
• Developmental Approaches
• Education
• +۶ مورد دیگر

Hyowon Gweon is an Associate Professor in the Department of Psychology at Stanford University. As the leader of the Social Learning Lab, her research focuses on how humans learn from others and help others learn, employing interdisciplinary methods including developmental, computational, and neuroimaging approaches. She holds a PhD in Cognitive Science from MIT (2012) and joined Stanford in 2014 after a postdoc at MIT. Her research interests span computational approaches to social learning, developmental psychology, neuroimaging, and education. She has received notable awards such as the APS Janet Spence Award (2020), James S. McDonnell Scholar Award (2018), and Marr Prize (2010). Her work explores topics like counterfactual reasoning, social cognition in infants, and embodied AI benchmarks. Labs/Teams: Social Learning Lab Key Themes: Prosocial behavior, theory of mind, cognitive development, and human-AI interaction. Her recent articles investigate infant gaze behavior, temporal reasoning in children, and strategic communication in preschoolers. Grants and advising details are not explicitly listed in the provided text.

• Sustainable Food System Governance
• Environmental Policy
• Biodiversity Recovery
• +۴ مورد دیگر

Prof. Hens Runhaar is a Full Professor of Sustainable Food System Governance at Utrecht University's Copernicus Institute of Sustainable Development. His research focuses on reconciling food production with biodiversity recovery, environmental sustainability, and health through innovative governance frameworks. He emphasizes connectivity issues in food systems, such as disconnects between production and environmental conditions, and advocates for transformative practices like agroecology and nature-inclusive agriculture. Key roles include chairing the Board of Examiners for Sustainable Development and membership in Future Food Utrecht. His projects include NWO-funded initiatives like COMBINED (grassland biodiversity) and REWIRE (circular agricultural missions). He actively engages in policy dialogues, such as advising BirdLife Netherlands and contributing to the Dutch Biodiversity Council. Research highlights systemic barriers to sustainability transitions in agriculture, with recent work analyzing dairy farming and farmer collectives. His outreach includes media appearances on nitrogen policy, nature restoration, and sustainable food systems. Professional memberships span international networks like Earth System Governance and the Wageningen School of Social Sciences.