جست‌وجوی استاد و پژوهشگر

Julia Hahnمشاهده پروفایل

پژوهشگر

• Technology Assessment
• Responsible Research and Innovation
• Participatory Procedures
• +۴ مورد دیگر

Dr. Julia Hahn is a Scientific Associate at the Karlsruhe Institute of Technology (KIT), working within the Institute for Technology Assessment and Systems Analysis (ITAS) in the Research Group 'Sociotechnical Futures and Policies'. She serves as co-project leader for the 'Participatory Procedures and Processes in Research Organizations' (PaFo) project and leads the HGF project 'Airborne transmission of the SARS coronavirus – from basic research to efficient air purification systems (CORAERO)'. Her work spans across multiple institutions including German Electron Synchrotron (DESY), German Aerospace Center (DLR), and other Helmholtz Association members. Dr. Hahn completed her doctorate in 2019 at KIT's Faculty of Humanities and Social Sciences with her thesis 'Towards a Global Technology Assessment - Insights from Cases in Germany, China, India and Beyond'. She earned her Master's degree in Applied Cultural Studies from Leuphana University Lüneburg in 2010, followed by a research assistant position there before joining ITAS in 2011. Her research focuses on the intersection of technology, society, and governance, with particular emphasis on global technology assessment frameworks. She examines how participatory procedures can enhance technology assessment processes and influence research agendas. Her work explores responsible research and innovation (RRI) from both theoretical and practical perspectives, analyzing how different institutional contexts shape approaches to responsibility in science and technology. Dr. Hahn investigates policy engagement mechanisms that connect scientific knowledge with decision-making processes, particularly during crises and periods of rapid technological change. Her research often addresses the challenges of transnational technology governance in an increasingly interconnected world. Analysis of Dr. Hahn's recent publications reveals strong thematic continuity in technology assessment methodology, with increasing attention to crisis contexts and pandemic response. Her work demonstrates a clear evolution from national to global technology assessment frameworks, with growing emphasis on comparative international studies. The publications show consistent interdisciplinary collaboration across social sciences, engineering, and health disciplines, reflecting her commitment to transdisciplinary approaches. Recent work increasingly integrates digital methods like bibliometric analysis while maintaining strong theoretical grounding in sociotechnical systems theory. Dr. Hahn has been instrumental in several significant projects including 'Piloting RRI in Industry' (PRISMA), 'Responsible Industry', 'Responsible Research and Innovation in Practice' (RRI Practice), and the 'Citizens' Dialogue on Future Technologies'. Her project work demonstrates consistent engagement with both theoretical frameworks and practical implementation of technology assessment methodologies. She has contributed to multiple European collaborative projects including PACITA (Parliaments and Civil Society in Technology Assessment), showing her commitment to strengthening democratic technology governance across borders. As part of her role at ITAS, Dr. Hahn contributes to the institute's mission of conducting integrated technology assessment that provides 'continuous reflection' for research projects, analyzing social, legal, and ethical implications while considering public trust and acceptance. Her work with the globalTA network demonstrates her commitment to international collaboration in technology assessment.

Patrick Christieمشاهده پروفایل

استاد

• Environmental Justice
• Political Ecology
• Marine Protected Areas
• +۷ مورد دیگر

Patrick Christie is a Professor at the University of Washington's School of Marine and Environmental Affairs (SMEA) with a joint appointment in the Jackson School of International Studies. His research focuses at the intersection of environmental justice, sustainability science, and marine conservation, emphasizing Indigenous leadership in environmental recovery across the Salish Sea and Great Lakes regions. His research interests center on justice-centered environmental governance, with particular focus on Indigenous-led environmental recovery , petroleum infrastructure resistance movements , and tribal rights in marine resource management . Christie employs participatory action research and digital storytelling methods, working closely with communities like the Tulalip Tribes and Puyallup Chief Leschi Schools to develop collaborative approaches that integrate local, Indigenous, and scientific knowledge systems. His work challenges technocratic approaches to conservation by centering social justice and equity. Christie's recent publications reveal a strong trend toward transdisciplinary collaboration and decolonizing conservation practices , with increasing emphasis on Indigenous knowledge systems, social justice frameworks, and participatory governance models. His work spans marine protected areas, climate adaptation, and coastal community resilience, with significant focus on the Philippines, Indonesia, and North American Indigenous communities. Pew Fellowship in Marine Conservation Christie actively mentors students through SMEA capstone projects and co-teaches specialized courses like Environmental Justice and Political Ecology Field Course and Environmental Justice, Social Movements, and Collaboration in the Time of Climate Change . His research is supported by collaborations with organizations including Future Earth, Painel Mar (Brazil), and tribal governments. He has provided technical advice to the UN Food and Agricultural Organization, World Bank, and USAID. Christie leads projects using participatory research methods to engage tribal communities in environmental recovery efforts, including work with the Tulalip Tribes on coastal squeeze issues and with Winona LaDuke on sustainable agriculture alternatives to petroleum-based economies. He co-hosts workshops exploring human dimensions of environmental change and is developing learning networks to foster collaborative ocean governance.

Laura Stateمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• AI Ethics
• Explainable AI
• +۳ مورد دیگر

Laura State serves as a Research Fellow at the Humboldt Institute for Internet and Society (HIIG) in Berlin, Germany, where she contributes to the AI & Society Lab's Impact AI project. This initiative develops transdisciplinary auditing methodologies to evaluate artificial intelligence systems' contributions to societal transformation and ecological sustainability through rigorous impact assessment frameworks. Her academic credentials include: PhD in Data Science from Scuola Normale Superiore, Pisa, Italy (Advised by Salvatore Ruggieri and Franco Turini) MSc in Neural Information Processing from the University of Tübingen BSc in Physics from the University of Rostock State's research synthesizes hard sciences with social perspectives to investigate AI's societal and planetary implications. She specializes in transparency and accountability mechanisms for non-interpretable machine learning models, developing assessment methodologies to determine how AI can foster sustainable futures. Her interdisciplinary approach integrates technical AI development with regulatory frameworks and ecological impact analysis, emphasizing real-world applicability through industry-academia collaboration. Her 2023-2025 publications reveal a cohesive research trajectory centered on explainable AI and regulatory compliance, particularly regarding GDPR requirements. Key themes include legal-technical alignment for explanation systems, bias/fairness policy frameworks, and innovative evaluation tools like REASONX. The work consistently bridges machine learning theory with societal accountability, demonstrating methodological rigor in translating technical capabilities into public-interest applications. As a core member of HIIG's AI & Society Lab, State collaborates on transdisciplinary teams examining AI's role in sustainability transitions. The Impact AI project coordinates researchers from computer science, law, and social sciences to develop evaluation frameworks that measure AI's contribution to UN Sustainable Development Goals, with active engagement in policy dialogues and public science initiatives like Lange Nacht der Wissenschaften.

Quan Zhouمشاهده پروفایل

استادیار

• Markov chain Monte Carlo sampling
• Bayesian methodology
• Variable selection
• +۷ مورد دیگر

Quan Zhou is an Assistant Professor in the Department of Statistics at Texas A&M University, part of the College of Arts & Sciences. His research focuses on developing advanced sampling methods, particularly Markov chain Monte Carlo (MCMC) algorithms, with applications in Bayesian methodology, variable selection, stochastic optimization, and statistical genetics. He holds a BS from Fudan University and a PhD from Baylor College of Medicine, followed by a postdoctoral fellowship at Rice University. He teaches courses such as Mathematical Probability, Multivariate Analysis, and Advanced Stochastic Processes. Notable contributions include work on informed MCMC samplers, Schrödinger bridge theory, and high-dimensional structure learning. He advises PhD students like Hyunwoong Chang (now at UT Dallas) and Guanxun Li (Beijing Normal University). Active in academic service, he served as President of the Southeastern Texas Chapter of the American Statistical Association (SETCASA).

• Air Pollution
• Particulate Matter Source Apportionment
• Chemometrics
• +۵ مورد دیگر

Philip K. Hopke, Ph.D., serves as an Adjunct Professor in both the Department of Public Health Sciences and Department of Environmental Medicine at the University of Rochester School of Medicine and Dentistry. With a distinguished career spanning over five decades since earning his Ph.D. from Princeton University in 1969, Dr. Hopke has established himself as a global leader in environmental chemistry and air pollution research. Ph.D. in Chemistry, Princeton University (1969) M.A. in Chemistry, Princeton University (1967) B.S. in Chemistry, Trinity College (1965) Dr. Hopke's pioneering work focuses on particulate matter source apportionment , where he developed innovative methodologies like dispersion-normalized positive matrix factorization (DN-PMF). His research integrates chemometrics , atmospheric chemistry , and environmental epidemiology to address critical air quality challenges worldwide. Recent projects span China's megacities, Iran's water crisis, and New York State's vehicle emission regulations, with particular emphasis on health impacts of source-specific pollutants. Analysis of his 15 most recent publications reveals consistent focus on advanced source apportionment techniques , health outcomes linked to air pollution , and policy evaluation using sophisticated statistical modeling. His work increasingly incorporates machine learning approaches while maintaining rigorous chemical characterization of environmental samples. Scientific Recognition Fellow of both the Air and Waste Management Association (2021) and American Association for Aerosol Research Recipient of the Lifetime Achievement Award in Chemometrics (2014) Albert Nelson Marquis Lifetime Achievement Inductee (2018) Multiple international awards including the Fissan-Pui TSI International Aerosol Research Award (2018) Dr. Hopke maintains an exceptionally active research program with collaborators across six continents, evidenced by his 2025 publications from China, Iran, Kazakhstan, and the United States. His work bridges fundamental atmospheric science with practical public health applications, particularly in evaluating regulatory impacts on air quality and health outcomes.

Stuart Johnstoneمشاهده پروفایل

استاد

• Biological psychology
• Psychophysiology
• ADHD assessment and diagnosis
• +۷ مورد دیگر

Professor Stuart Johnstone is a prominent researcher and educator in the School of Psychology at the University of Wollongong. He has held academic positions at UOW since 1999, progressing from Lecturer to his current role as Professor since 2018. He previously served as Deputy Head of School (Teaching and Learning) from 2020-2023 and Acting Head of School in 2024. He also maintains a Visiting Professor position at Zhejiang Normal University's Faculty of Special Education since 2018. His educational background includes a PhD and Bachelor of Science (Honours Class I) from the University of Wollongong, followed by post-doctoral work at the University of Sydney's Department of Psychological Medicine. He is a Registered Psychologist with the Australian Health Practitioner Regulation Agency (2001-2022). Johnstone's research focuses on neurophysiological approaches to understanding and treating ADHD, particularly using brain electrical activity measures to improve assessment and diagnosis. His work spans biological psychology, psychophysiology, and developmental psychology, with emphasis on neurocognitive training interventions for children with ADHD. He has developed innovative approaches to ADHD assessment that incorporate EEG measurements alongside traditional clinical evaluations. His publication record demonstrates consistent focus on ADHD neurophysiology, with recent work expanding into cross-cultural applications, portable EEG technology for educational settings, and animal-assisted interventions. His research shows growing emphasis on practical applications of neurocognitive assessment and training, with increasing attention to remote delivery methods and cross-cultural validity of interventions. UOW Vice-Chancellors Award for Outstanding Achievement in Research Commercialisation (2013) UOW Vice-Chancellors Award for Global Strategy (2018) Johnstone actively supervises numerous PhD students, with current projects examining sleep patterns in ADHD, human-dog interactions for wellbeing, and test anxiety in school children. His research is supported by multiple grants including external funding from the Prevention Research Support Program and internal University of Wollongong grants focused on neurocognitive assessment and training. His work has strong international collaboration, particularly with Chinese institutions. He coordinates courses in Biological Psychology and Psychophysiology and has developed international educational programs in Singapore. His research group focuses on translating neurophysiological findings into practical assessment tools and interventions for ADHD, with recent work emphasizing portable technology and cross-cultural applications.

Brigitte Pientkaمشاهده پروفایل

استاد

• Programming Languages
• Verification
• Type Theory
• +۶ مورد دیگر

Brigitte Pientka is a Professor at McGill University's School of Computer Science , where she leads the Computation and Logic group . She earned her PhD from Carnegie Mellon University in 2003 and previously studied at the University of Edinburgh and Technical University of Darmstadt. Education PhD in Computer Science, Carnegie Mellon University (2003) University of Edinburgh Technical University of Darmstadt Research Interests Her work focuses on the theoretical and practical foundations for building reliable software systems, combining logic, type theory, and verification with system-building. Key areas include: Type Theory and Dependent Types Logical Frameworks and Mechanized Metatheory Session-Typed Concurrency and Linear Logic Metaprogramming and Contextual Type Systems Theorem Proving and Formal Verification Functional Programming and Language-Based Security Professional Roles She has served as: PC Chair for ICFP'24 and CPP'24 General Chair for POPL'20 Executive Editor of Logical Methods in Computer Science Steering Committee Member for LICS, POPL, and ESOP Scientific Awards Dr. Pientka has received: Test of Time Award at PPDP'18 Humboldt Fellowship for research at MPI-SWS, Germany Labs & Teams She actively develops the Beluga programming language , a tool for mechanizing meta-theory proofs and type-driven program manipulation.

Tomer Galantiمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Large Language Models
• +۵ مورد دیگر

Tomer Galanti is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on machine learning, deep learning, large language models, and artificial intelligence. He holds a B.S., M.S., and Ph.D. in Computer Science and Mathematics from Tel Aviv University (2015–2021), followed by a postdoctoral position at MIT (2021–2024). His work spans theoretical foundations of neural networks, optimization, generalization bounds, and practical applications in language modeling and self-supervised learning. Education: Postdoctoral Associate, Massachusetts Institute of Technology (MIT), 2021–2024 Ph.D., Computer Science, Tel Aviv University, 2021 M.S., Computer Science, Tel Aviv University, 2017 B.S., Mathematics and Computer Science, Tel Aviv University, 2015 Research Interests: Machine and deep learning, large language models, artificial intelligence, generalization bounds, neural collapse phenomena, and self-supervised learning. His recent work explores optimization techniques (e.g., SGD with weight decay), distributed inference systems, and theoretical guarantees for neural network performance. Articles Trends: His publications emphasize theoretical advancements in neural network dynamics, generalization, and optimization. Notable themes include sparse neural networks, speculative inference acceleration, and fairness in language models. He also investigates representation learning and decision tree integration in language modeling frameworks. Advising & Grants: No advising or grant details are explicitly listed in the provided materials. His research is supported through institutional and collaborative efforts in computational and theoretical machine learning.

Zhuang Liuمشاهده پروفایل

استادیار

• Deep Learning
• Computer Vision
• Natural Language Processing
• +۳ مورد دیگر

Zhuang Liu is an Assistant Professor of Computer Science at Princeton University, where he leads a research group focused on deep learning and computer vision. His work spans vision and language, unified by a focus on deep learning methods, representations, and architectures. Prior to joining Princeton, he was a Research Scientist at Meta AI Research (FAIR) in New York City. He received his Ph.D. from UC Berkeley and his B.E. from Tsinghua University, both in Computer Science. His educational background includes: Ph.D. in Computer Science, University of California, Berkeley, 2022 B.E. in Computer Science, Tsinghua University (Yao Class) Liu's research focuses on empirical approaches to understanding how deep learning models work and behave. He explores simple approaches to gain empirical insights into neural networks, often challenging existing beliefs in architectures, training, pruning, and datasets. His work spans multiple domains including computer vision, natural language processing, and multimodal learning. He has made significant contributions to the field, including DenseNet and ConvNeXt architectures, which have influenced modern neural network design. His recent publications reveal a strong focus on understanding and improving large language models and vision-language systems. His work examines idiosyncrasies in LLMs, pruning approaches for efficient inference, visual shortcomings of multimodal systems, and bias in large-scale visual datasets. He also investigates fundamental questions about neural network architectures, exploring the relationship between ConvNets and Transformers, and developing normalization-free transformer variants. His research consistently bridges theoretical insights with practical applications, as evidenced by his numerous conference publications and industry collaborations. His notable scientific achievements include: CVPR Best Paper Award NeurIPS'18 Compact Neural Networks Workshop Best Paper Award Professor Liu actively mentors students and postdoctoral researchers, currently advising seven Ph.D. students including Wenhao Chai, Tony Chen, Sachin Konan, Taiming Lu, Zhuorui Ye, David Yin, and Boya Zeng. He has successfully guided graduates such as Jiachen Zhu (now at Skild AI) and Mingjie Sun (now at Thinking Machines Lab). His research has practical implications for improving the efficiency, interpretability, and fairness of deep learning systems, with applications across multiple domains. His research group maintains active collaborations with industry partners including Meta FAIR, NVIDIA Research, and Adobe, and regularly hosts research interns. The group's work has established Zhuang Liu as a leading voice in empirical deep learning research, with invitations to speak at top academic institutions including Harvard, Stanford, Columbia, and Boston University.

Stefano Martinianiمشاهده پروفایل

استادیار

• Computational and Statistical Physics
• Materials Science
• Artificial Intelligence for Science
• +۵ مورد دیگر

Stefano Martiniani is an Assistant Professor of Physics, Chemistry, Mathematics, and Neuroscience at New York University, affiliated with the Center for Soft Matter Research and the Simons Center for Computational Physical Chemistry. His interdisciplinary research explores computational physics of complex systems, including neural circuit theories, non-equilibrium statistical mechanics, and AI-driven materials discovery. He has pioneered methods for analyzing high-dimensional energy landscapes and received prestigious awards like the NSF CAREER Award (2024) and IUPAP Early Career Prize (2023). Education: PhD in Physics (2017), University of Cambridge MPhil in Physics (2013), University of Cambridge BSc in Physics (2012), Imperial College London Research Interests: His work bridges statistical physics and artificial intelligence, focusing on: Engineering disordered materials with tailored spectral properties Quantifying entropy production in active matter Developing open science frameworks like ColabFit for machine learning interatomic potentials Neural circuit models for cortical communication Grants & Collaborations: Funded by NSF, NIH, Chan Zuckerberg Initiative, and Simons Foundation. Leads interdisciplinary teams in computational physics, AI, and materials science. Labs/Initiatives: Core member of NYU's Center for Soft Matter Research; develops software tools like FReSCo and KLIFF-Torch for computational materials science.

Peter Dybjerمشاهده پروفایل

استاد

• Intuitionistic Type Theory
• Categorical Type Theory
• Proof Assistants
• +۹ مورد دیگر

Peter Dybjer is a Professor of Computing Science at the Department of Computer Science and Engineering, Chalmers University of Technology in Sweden. He is a leading researcher in the field of type theory, with a focus on intuitionistic type theory, categorical semantics, and proof assistants. His work bridges foundational aspects of mathematics and computer science, emphasizing constructive methods and formal verification. Research Interests: Intuitionistic Type Theory and its categorical semantics Proof assistants and formal verification Inductive and inductive-recursive definitions Game semantics and normalization techniques Dependent type systems and their applications Homotopy Type Theory and univalent foundations Activities & Contributions: Editor of the Bulletin of Symbolic Logic Member of program committees for conferences like TYPES, FSCD, and MFPS Keynote speaker at events including the European Congress of Mathematics and the Hausdorff Research Institute's Summer School on Types, Sets, and Constructions Initiated and directed the Master's Program in Computer Science – Algorithms, Languages, and Logic at Chalmers Teaching & Outreach: Professor Dybjer has taught advanced courses at international summer schools, including: Inductive Definitions in Constructive Type Theory (TYPES Summer School, 2005) Dependent Types at Work (LerNet Summer School, Uruguay, 2008) Normalization by Evaluation (Midlands Graduate School, 2009 and 2015)

Shenyue Jiaمشاهده پروفایل

استادیار

• Climate Change
• Geospatial Analysis
• Remote Sensing
• +۳ مورد دیگر

Dr. Shenyue Jia is an Assistant Professor of Geography and Director of the Geospatial Analysis Center at Miami University, Ohio. Her research focuses on leveraging satellite and crowdsourced data to analyze climate change impacts in semi-arid ecosystems and human adaptation strategies. She also innovates GIS education to democratize geospatial analysis tools beyond traditional software. Education: Ph.D. in Geography (UCLA), M.S. in Cartography (Nanjing University), B.S. in GIS (Nanjing Normal University) Her research interests include: Wildfire risk assessment using SMAP soil moisture and vegetation indices GIS applications in disaster response (e.g., power outage analysis during wildfires) Social media data utilization for crisis management GIS curriculum development emphasizing R/Python tools Recent projects include NASA DEVELOP's Kentucky tornado power outage analysis and collaborative work with CrisisReady on real-time geolocation data platforms. She has presented at AGU Annual Meetings and received grants from CADS and Miami University's CTE. Key Collaborations: CrisisReady, Thriving Earth Exchange, Google Geo for Good Teaching initiatives include a Climate Science Communication course and 3D urban modeling projects funded by the Humanities Center. She advises Slade Laszewski, whose 2024 ERC publication on WUI population trends earned recognition.

Hedieh Hashemi Hosseinabadمشاهده پروفایل

استادیار

• Cleft Palate Speech Assessment
• Velopharyngeal Insufficiency (VPI)
• Speech Intelligibility
• +۵ مورد دیگر

Hedieh Hashemi Hosseinabad is an Assistant Professor in the Department of Audiology and Speech Language Pathology at the University of North Texas. She holds a Ph.D. in Speech and Hearing Science from the University of Cincinnati, a Master’s in Speech Language Pathology from Tehran University of Medical Sciences, and a Bachelor of Science from Isfahan University of Medical Sciences. Certified by the American Speech-Language-Hearing Association (CCC-SLP), she has 14+ years of clinical experience specializing in children with cleft palate and velopharyngeal insufficiency (VPI). Her research focuses on two core areas: (1) factors influencing speech intelligibility in VPI, including acoustic and perceptual measures, and (2) persistent speech disorders in children with cleft palate, particularly those with co-occurring syndromic conditions. She employs multidisciplinary methods such as ultrasound biofeedback, high-speed nasopharyngoscopy, and acoustic analysis to assess and treat speech disorders. Her work analyzes speech characteristics across vowel contexts, velopharyngeal mechanisms, and surgical outcomes. Recent studies explore the impact of noise environments, listener expertise, and lexical factors on speech intelligibility. She has contributed to improving clinical protocols for speech assessment and therapy in cleft palate populations. Her research and clinical practice emphasize translational approaches to enhance speech outcomes and quality of life for affected children. Collaborations include cleft care teams in Iran, as reflected in studies involving the Isfahan Cleft Care Team.

• Sports Criminology
• Violence in Sports
• Social Perspectives of Sports
• +۴ مورد دیگر

Dr Victoria Silverwood is a Researcher in Criminology at the School of Social Sciences, Swansea University . Her work uniquely bridges criminology with sports studies, focusing on the cultural and social dimensions of sports-related head injuries and legitimised violence in contact sports. She is affiliated with the Swansea Centre of Research into Sports and Society (SCORSS) , a multidisciplinary group examining sports and leisure cultures. Research Interests include: Sports-related concussion as a social issue Critical Sports Criminology Violence and harm in professional ice hockey (NHL, UK Elite Ice Hockey League) Legitimisation of violence in sports subcultures Policy implications for child protection and fostering wellbeing Her publications over 16 years reveal a consistent focus on sports violence , public health , and social justice . She utilizes mixed-method research designs and ethnographic approaches to dissect spectator and athlete behaviors. Silverwood actively engages the public, as evidenced by her Hay Festival 2023 talk and collaborations with projects like StreetSnap and Flip the Streets . Contact: v.s.m.silverwood@swansea.ac.uk

Sinan Sarpcaمشاهده پروفایل

استاد

• Public Economics
• Economics of Education
• Industrial Organization
• +۱ مورد دیگر

Sinan Sarpca is a Professor of Economics at Koc University, serving as Director of the Graduate School of Social Sciences and Humanities. He maintains an affiliation with École Normale Supérieure de Lyon (currently on leave), with research spanning public economics, economics of education, industrial organization, and applied econometrics. His work examines market competition in education systems and policy impacts on educational access. Education: PhD in Economics, Carnegie Mellon University Sarpca investigates how market structures in educational choice systems affect outcomes through theoretical, computational, and empirical methods. His research analyzes peer effects, price discrimination, voucher programs, and residential sorting due to school quality, focusing on income-ability dynamics in educational equity and efficiency. His 15 most recent publications (2023-2006) consistently explore higher education markets and K-12 school choice systems. Dominant themes include university market power, peer effects in high schools, housing-education welfare linkages, and voucher policy impacts. Methodologically, he integrates industrial organization theory with econometric analysis to evaluate real-world educational systems. Funded by TUBITAK (Turkey) and IDEXLyon (France), Sarpca's research examines competition and policy design in education. As Graduate School Director, he oversees graduate programs though specific advisees aren't listed. He holds additional affiliations including CESifo Research Fellow status.