جست‌وجوی استاد و پژوهشگر

• Educational Leadership
• Comparative Research
• Innovation in Education
• +۳ مورد دیگر

Dr. Dong Nguyen is an Associate Professor in Leadership Management and Change in Education at Durham University's School of Education. He serves as Director of the Master’s Programme in Educational Leadership and Change, which focuses on leadership, management, and research in education. Additionally, he is Editor-in-Chief of the International Journal of Educational Management (IJEM), a core journal in educational leadership. His career includes roles as a lecturer (Assistant Professor) and Programme Leader at the University of Glasgow, a Research Associate at Nanyang Technological University, and a teacher in Vietnam. Nguyen’s research emphasizes building leadership capacity in the Global South, comparative education studies, and innovation in education. He has led projects such as an impact evaluation of a Rwanda school leadership development program (2023–2026) funded by VVOB and a review of school leadership’s role in teacher retention funded by the Education Endowment Foundation (EEF). His work explores leadership practices across sectors like education, business, and healthcare, with a focus on equitable systems and professional learning. Nguyen has received a Discretionary Award from Durham University (2023) and has delivered numerous invited talks, including at the Chinese University of Hong Kong (2024), the Asian Conference on Business and Economic Studies (2024), and Stockholm institutions (2023). He has served as an external examiner for UK universities (e.g., Leeds, Newcastle) and evaluator for grants like UK Research & Innovation and Swiss National Science Foundation. His supervision focuses on topics like school leadership, inter-organizational collaboration, and professional development. Nguyen’s recent articles highlight leadership’s role in teacher retention, autonomy, and PLCs in the Global South. He advocates for leadership practices that foster teacher collaboration, instructional support, and participatory decision-making, particularly in contexts like Singapore and Vietnam. His funded projects and editorial roles underscore his commitment to evidence-based educational policy and practice.

• Management Education
• Project Management
• Information Management
• +۳ مورد دیگر

Prof. Dr. Frank Ulbrich is a Lecturer and Programme Director for the BSc Business Administration at the Lucerne School of Business (HSLU). He holds a PhD in Business Administration from the Stockholm School of Economics. His academic career spans roles at universities in Sweden, the UK, Canada, and Switzerland, alongside IT & Management consulting experience. Research focuses on management education, project management, information management, and organizational change. He has published extensively in areas like shared services, digital transformation, and curriculum development. Notable awards include multiple Emerald Literati Awards and a Fellowship from the Higher Education Academy. Education: PhD in Business Administration (Stockholm School of Economics) Affiliations: Institute of Business and Regional Economics at HSLU Teaching Subjects: Academic Methods, Higher Education Management, Project Management, Digital Transformation Recent presentations include discussions on bridging academia-industry gaps, curriculum integration of SDGs, and data-driven learning strategies. His work emphasizes aligning education with labor market needs and advancing evidence-based teaching practices.

Antonio Rangelمشاهده پروفایل

استاد

• Neuroeconomics
• Decision Neuroscience
• Behavioral Economics
• +۴ مورد دیگر

Antonio Rangel is the Bing Professor of Neuroscience, Behavioral Biology, and Economics at the California Institute of Technology (Caltech), where he also serves as Head Faculty in Residence. He is a faculty member in the Division of Humanities and Social Sciences (HSS) with research focusing on the computational and neurobiological basis of value-based decision-making. Dr. Rangel received his educational training at prestigious institutions: B.Sc. from Caltech in 1993 M.S. from Harvard University in 1996 Ph.D. in 1998 Professor Rangel's research lies at the intersection of neuroscience, economics, and psychology, with a focus on understanding how the brain makes decisions. His work investigates the neural mechanisms underlying value computation, choice processes, self-control, and social decision-making. Using a multidisciplinary approach that combines functional magnetic resonance imaging (fMRI), eye-tracking, computational modeling, and behavioral experiments, his lab has made significant contributions to the field of neuroeconomics. His research has revealed how value signals are represented in the brain, how attention influences choice, and the neural basis of self-control failures. Professor Rangel has pioneered methods for studying decision processes with high temporal resolution using eye-tracking data, demonstrating how fixation patterns relate to value computations and choice outcomes. His work spans from theoretical frameworks of value-based decision-making to practical applications in behavioral public economics. Professor Rangel's work has been recognized with prestigious awards: 2019 NOMIS Distinguished Scientist Award 2018 Fellow of the Association for Psychological Science As an academic leader, Professor Rangel has mentored numerous students and researchers who have gone on to make their own contributions to neuroscience and economics. His lab, the Rangel Neuroeconomics Laboratory at Caltech, serves as a hub for interdisciplinary research, bringing together students and scholars from neuroscience, economics, psychology, and computer science. The lab has received significant funding to support its research on the neural basis of decision-making, including support from the NOMIS Foundation. The Rangel Neuroeconomics Laboratory is equipped with state-of-the-art facilities including fMRI analysis capabilities, eye-tracking systems, and computational resources for modeling decision processes. The lab fosters a collaborative environment where researchers apply methods from experimental economics and cognitive neuroscience to unravel the complexities of human decision-making.

LEONG Tze Yunمشاهده پروفایل

استاد

• Responsible AI
• Dynamic Decision-Making
• Neurocognitive Modeling
• +۳ مورد دیگر

LEONG Tze Yun is a Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). She holds S.B., S.M., and Ph.D. degrees in Computer Science from the Massachusetts Institute of Technology (MIT). Her academic career spans both research and industry experience, with significant contributions to the fields of artificial intelligence and health informatics. Dr. Leong's educational background includes: Ph.D. in Electrical Engineering & Computer Science, Massachusetts Institute of Technology S.M. in Electrical Engineering & Computer Science, Massachusetts Institute of Technology S.B. in Computer Science & Engineering, Massachusetts Institute of Technology Her primary research interests focus on responsible AI, dynamic decision-making, neurocognitive modeling, reinforcement learning, artificial general intelligence, and biomedical and health informatics. Her work bridges the gap between theoretical AI development and practical healthcare applications, with an emphasis on ethical considerations and human-centered design. She directs the Medical Computing Laboratory at NUS, a multidisciplinary research program exploring human-aware decision modeling in complex environments. Analysis of her recent publications reveals a strong trend toward responsible AI development, with significant contributions to reinforcement learning techniques, causal inference methods, and applications of AI in healthcare. Her work increasingly integrates ethical considerations with technical AI development, particularly evident in her 2024 publications on medical AI and human values. Her scientific recognition includes: Fellow of the American College of Medical Informatics (ACMI) Founding Fellow of the International Academy of Health Sciences Informatics (IAHSI) Member of Eta Kappa Nu (Honor Society for Electrical Engineers) Dr. Leong has supervised numerous doctoral and master's students throughout her career, many of whom have gone on to prominent positions at institutions like Google, Netflix, Mayo Clinic, and academic institutions worldwide. Her advisory work extends to significant policy development, including contributions to WHO guidance on ethics and governance of AI for health. She currently serves on the World Health Organization (WHO) Expert Group on Ethics and Governance of AI for Health, the World Economic Forum (WEF) AI Governance Alliance, and the Advisory Council on AI in Uzbekistan. Her laboratory work focuses on developing adaptive systems that evolve with changing technical functionalities, system infrastructures, usage patterns, and operational contexts, with applications spanning prediction and decision analytics, human-aware robotics, game artificial intelligence, personalized education, and assistive care for elderly with neurocognitive disorders.

Mariana Gkliatiمشاهده پروفایل

استادیار

• International Law
• EU Law
• Refugee Law
• +۳ مورد دیگر

Mariana Gkliati is an Assistant Professor of International and EU Law at Radboud University, Nijmegen. She holds a Graduate Diploma in Law (Magna Cum Laude) from the National and Kapodistrian University of Athens and a Legal Research Master (Summa Cum Laude) from Utrecht University. Her PhD from Leiden University focused on Frontex accountability, supervised by Professors Rodrigues and Besselink, and was supported by the Meijers Research Institute. Education: PhD in Immigration Law, Leiden University (2016-2020) Legal Research Master, Utrecht University (Summa Cum Laude) Graduate Diploma in Law, National and Kapodistrian University of Athens (Magna Cum Laude) Her research interests center on migration, refugee law, and human rights, particularly the accountability of the European Border and Coast Guard Agency (Frontex). She leads the externally funded project 'European Border and Coast Guard Agency: Systemic Accountability in Practice,' involving an 8-member team. Her work emphasizes evidence-based policy-making and anti-smuggling policies. Professional Activities: Research Affiliate, Refugee Law Initiative (RLI), University of London Teaches on the RLI MA in Refugee Protection and Forced Migration Studies Former visiting Research Fellow at the School of Advanced Study (2016) and Amsterdam Centre for Migration and Refugee Law (2019-2020) Awards: Magna Cum Laude, Graduate Diploma in Law Summa Cum Laude, Legal Research Master Her grants and projects include systemic accountability research on Frontex. She advises NGOs, law firms, and the European Parliament, and contributes to expert reports on migration and borders. Labs/Teams: Leads an 8-member research team for her funded project on Frontex accountability.

Alison Ledgerwoodمشاهده پروفایل

استاد

• Social Psychology
• Open Science
• Methodology
• +۴ مورد دیگر

Alison Ledgerwood is a Professor in the Department of Psychology at the University of California, Davis, and Principal Investigator of the Attitudes and Group Identity Lab. Her research examines how social context shapes attitudes and preferences, with a focus on open and inclusive scientific practices. Ph.D., Social Psychology, New York University (2008) M.A., Psychology, New York University (2006) B.A., Psychology, Amherst College (2003) Her research explores psychological distance , framing effects , and system justification theory , while methodologically advancing preregistration , collaborative science , and equity in publishing . She also investigates group identity dynamics and implicit/explicit bias measurement . Recent publications highlight her work on racial bias methodology , open science reform , and contextual framing . Awards include the 2024 Distinguished Service to the Society award, 2021 UC Davis Advising and Mentoring Award, and 2017 SPSP Service to the Field award. 2024 Distinguished Service to the Society, SPSP 2021 UC Davis Graduate Advising and Mentoring Award 2017 Service to the Field, SPSP Hellman Fellowship (2010-2011), UC Davis UC Davis Chancellor's Fellow APS Fellow SESP Fellow Ledgerwood advises on scientific integrity through roles like Chair of the Transparency and Openness Promotion (TOP) II Guidelines Task Force and Anti Colorism and Eurocentrism in Methods and Practices (ACEMAP) Task Force. Her lab fosters contextual evaluation studies and psychological distance frameworks .

Daniel E. Hoمشاهده پروفایل

استاد

• Artificial Intelligence Policy
• Regulatory Governance
• Fairness in AI
• +۳ مورد دیگر

Daniel E. Ho holds multiple prestigious positions at Stanford University: William Benjamin Scott and Luna M. Scott Professor of Law Professor of Political Science Professor of Computer Science (by courtesy) Senior Fellow, Stanford Institute for Economic Policy Research Senior Fellow, Stanford Institute for Human-Centered Artificial Intelligence Faculty Fellow, Center for Advanced Study in the Behavioral Sciences He serves on the National Artificial Intelligence Advisory Commission (NAIAC), as Senior Advisor on Responsible AI at the U.S. Department of Labor, and as a Public Member of the Administrative Conference of the United States (ACUS). Ho earned his J.D. from Yale Law School and Ph.D. from Harvard University, completing a clerkship with Judge Stephen F. Williams on the U.S. Court of Appeals for the District of Columbia Circuit. His research bridges artificial intelligence, law, and public policy with emphasis on: Regulatory governance frameworks for AI systems Fairness and bias mitigation in algorithmic decision-making Environmental enforcement using satellite imagery and computer vision Methods for estimating racial disparities without direct demographic data Legal AI reliability and statutory research systems Analysis of his 2025 publications reveals a consistent focus on practical AI governance tools addressing real-world regulatory challenges. Key themes include developing benchmarks for legal applications, mitigating hallucination in legal AI tools, and creating systems for statutory research. His work demonstrates strong integration of technical AI methods with policy implementation, particularly in environmental enforcement and fairness assessment. As Director of the Regulation, Evaluation, and Governance Lab (RegLab), Ho leads interdisciplinary research partnerships with government agencies. While specific grant details aren't provided, RegLab's operational model indicates substantial research funding for policy-relevant AI projects. No student advisees are mentioned in available materials. Ho's leadership extends to national advisory roles where he shapes federal AI policy through evidence-based recommendations, particularly regarding environmental protection and civil rights enforcement mechanisms.

• Behavioral Economics
• Intertemporal Choice
• Risky Choice
• +۲ مورد دیگر

Charles D. Sprenger is a Professor of Economics at the California Institute of Technology (Caltech), where he has served since 2020 and held the position of Executive Officer from 2022 to 2025. He is affiliated with Caltech's Division of the Humanities and Social Sciences (HSS) and holds key roles at the Ronald and Maxine Linde Institute of Economic and Management Sciences and the Center for Theoretical and Experimental Social Sciences (CTESS). His external appointments include Board of Editors for the American Economic Review and Associate Editor roles for the Journal of the European Economic Association and Quantitative Economics . His educational background includes a B.A. from Stanford University (2002), an M.Sc. from University College London (2005), and a Ph.D. from the University of California, San Diego (2011). These credentials established his foundation in economic theory and experimental methodology. Sprenger is a leading behavioral and experimental economist specializing in intertemporal decision making and choices under uncertainty. His research designs innovative experiments across diverse contexts—from food deserts in the United States to polio vaccination drives in Pakistan—to test the validity of standard economic models. His work consistently reveals significant deviations from rational choice theory, particularly regarding time inconsistency, risk preferences, and reference-dependent behaviors. He has pioneered methods for measuring time preferences and testing cumulative prospect theory, with implications for public policy and behavioral interventions. Analysis of his 15 most recent publications (2015-2024) shows a cohesive research program centered on behavioral anomalies in decision making. His work bridges laboratory precision with real-world field applications, demonstrating how psychological factors like procrastination and loss aversion manifest in high-stakes environments. Key trends include the development of tailored incentive structures, validation of rank-dependent utility models, and exploration of dynamic inconsistency across domains including health, finance, and public policy. His notable recognition includes: Sloan Foundation Fellowship (2016-2018) Sprenger actively contributes to the academic community through editorial leadership and collaborative research. His work has been featured in Caltech news for projects like "Reducing Procrastination with Tailored Incentives" (2023) and the graduate summer program "Experimental Economics in Theory and Practice" (2023). Though specific advisees aren't listed, his teaching of advanced courses like Experimental Economics (SS 212 abc) indicates mentorship of graduate researchers. He secures significant research funding through fellowships and institutional support, enabling large-scale field experiments. As a core member of CTESS, Sprenger leads a multidisciplinary team conducting cutting-edge experimental economics research. His lab integrates theoretical modeling with empirical validation, focusing on how behavioral insights can improve policy design in areas like tax compliance, vaccination programs, and financial decision making. Current work emphasizes scalable interventions for procrastination and preference-based incentive customization.

• Labor Economics
• Health Economics
• Public Economics
• +۳ مورد دیگر

Atsuko Tanaka is an Associate Professor in the Department of Economics at the University of Calgary. Her research focuses on labor markets, health economics, and public policy, particularly examining topics such as female labor supply, skill investment, and pension reforms. She holds a Ph.D. in Economics from the University of Wisconsin-Madison (2013), alongside advanced degrees from Cornell University and the University of Tokyo. Education Ph.D. Economics, University of Wisconsin-Madison (2013) M.S. Economics, University of Wisconsin-Madison (2010) M.S. Applied Economics and Management, Cornell University (2007) B.A. Agricultural Economics, University of Tokyo (2004) Research Interests Tanaka’s work explores how health shocks, financial constraints, and policy interventions influence labor market outcomes. She investigates topics such as post-educational skill accumulation via college loans, strategic medical treatment choices under reimbursement reforms, and the macroeconomic effects of pension system transitions. Her research combines rigorous econometric methods with real-world administrative data to inform evidence-based policy. Awards and Grants SSHRC Connection Grant (2022, co-PI: Apostolos Serletis) National Science Foundation Extreme Science Grant (2021) SSHRC Insight Development Grant (2016) Susan Jane Blake Kocin Award, University of Wisconsin-Madison (2011) Grants and Collaboration Her research has been supported by major grants, including SSHRC and NSF funding. She collaborates with scholars on projects like analyzing physician behavior under reimbursement reforms, auditing firm dynamics, and international aid allocation strategies. Her work bridges theoretical models with empirical evidence to address complex socio-economic challenges.

• Health economics
• Health policy
• Health services and management
• +۲ مورد دیگر

Professor Shaun Larkin is a part-time academic at the School of Public Health , University of Sydney, specializing in Health Policy and Financing . He is affiliated with the Leeder Centre for Health Policy, Economics and Data and a member of the Charles Perkins Centre . With a career spanning executive roles at HCF and non-executive directorships in health startups, his work bridges academia and industry. Education : Harvard Business School alumnus with a HlthScD, MBA, MHSc, and BHA. His research focuses on health economics , health policy , and health services management , emphasizing: Translational research in healthcare financing Trends in private-public healthcare partnerships Price transparency in private health insurance Leadership in health systems Chronic disease management Quality use of medicines His publications reveal a trajectory from foundational work in: Psychiatric services data standardization (2000) Heart disease and diabetes management (2013-2015) Telehealth interventions (2017-2018) Private sector policy frameworks (2019-2020) Saudi Arabian health reforms (2022-present) Private equity in healthcare (2025) As an advisor, he currently supervises research students on topics including: Quality use of medicines in Saudi Arabia Sustainable financial models for private hospitals Patient-reported outcome measures in Australia He also contributes to the Leeder Centre and engages with global health startups as an investor and advisor.

Emily Soمشاهده پروفایل

استاد

• Disaster Risk Reduction
• Earthquake Engineering
• Urban Resilience
• +۵ مورد دیگر

Professor Emily So serves as Deputy Head of the School of Arts and Humanities at the University of Cambridge and directs the Cambridge University Centre for Risk in the Built Environment (CURBE). A chartered civil engineer with extensive field experience, she holds leadership roles in the Open-Oxford-Cambridge AHRC Doctoral Training Partnership and chairs the Faculty EDI Committee. Her research focuses on urban risk and resilience , particularly in earthquake-prone regions. Combining structural engineering with epidemiological approaches, she develops innovative casualty estimation models and engages directly with affected communities worldwide. Her work spans seismic safety, disaster epidemiology, and remote sensing applications for rapid damage assessment. Professor So's publication trends reveal strong emphasis on machine learning for disaster risk modeling , with recent work featuring graph neural networks, deep clustering for urban morphology, and LSTM-based population forecasting. Her research bridges engineering, social sciences, and data science to address resilience in developing nations. 2010 Shah Family Innovation Prize (Earthquake Engineering Research Institute) Fellow of the Institution of Civil Engineers (FICE) Scientific Advisory Group for Emergencies (SAGE) member advising UK government As Director of CURBE, she leads interdisciplinary collaborations with EEFIT, Global Earthquake Model (GEM), World Bank, and USGS. Her field investigations following major earthquakes inform practical solutions for vulnerable communities, notably contributing to the 2017 World Building of the Year design in China. Current work includes sabbatical research for 2025-2026 focused on decolonizing architectural approaches to disaster resilience. Professor So maintains active roles in professional organizations and international disaster response frameworks, with her CURBE team developing methodologies now implemented globally for seismic safety improvements.

• Statistical Reinforcement Learning
• Mobile Health (mHealth)
• Clinical Trials
• +۳ مورد دیگر

Susan A. Murphy is the Mallinckrodt Professor of Statistics and of Computer Science at Harvard University, with affiliations to the Kempner Institute. She leads the Statistical Reinforcement Learning Lab, focusing on developing algorithms to inform sequential decision-making in health, particularly for Just-in-Time Adaptive Interventions (JITAIs) and micro-randomized trials (MRTs). Her work is funded by NIH institutes, including NIDA, NHLBI, and NIBIB. Dr. Murphy has been awarded a MacArthur Fellowship (2013) and is a member of the National Academy of Medicine (2014) and the National Academy of Sciences (2016). Her research integrates statistical methods with computer science techniques to optimize mobile health interventions. She collaborates with d3Lab and mDOT on projects like HeartSteps and Sense2Stop, evaluating real-time treatment policies. Notable contributions include advancing MRT designs, sample size calculations, and reinforcement learning algorithms for personalized healthcare. Dr. Murphy advises a large team of postdocs, graduate students, and undergraduates, many of whom hold academic and industry roles globally. She emphasizes engagement in digital interventions, balancing personalization with ethical considerations. Her lab’s work spans algorithm development, clinical trial design, and causal inference, aiming to improve health outcomes through adaptive interventions.

Arvind Narayananمشاهده پروفایل

استاد

• AI Policy
• Societal Impact of Digital Technologies
• Fairness in Machine Learning
• +۶ مورد دیگر

Arvind Narayanan is a Professor of Computer Science at Princeton University and Director of the Center for Information Technology Policy (CITP). His research focuses on the societal impact of digital technologies, particularly artificial intelligence, with emphasis on policy implications, fairness, and privacy. He leads interdisciplinary efforts connecting technical research with real-world policy challenges. Dr. Narayanan earned his Ph.D. from the University of Texas, Austin in 2009. His academic journey has established him as a leading voice in the critical examination of AI systems and their societal consequences. Narayanan's research spans multiple domains where technology intersects with society. His work on AI includes critical analysis of AI capabilities versus marketing claims (AI Snake Oil), fairness in machine learning systems, and the reproducibility crisis in ML-based science. In privacy research, he led the Princeton Web Transparency and Accountability Project which uncovered how companies track users online, developing the OpenWPM tool used in over 100 studies. His early work demonstrated fundamental limits of de-identification techniques and how machine learning reflects cultural stereotypes. His recent publications reveal a consistent focus on demystifying AI capabilities while identifying genuine opportunities and risks. Narayanan's work bridges technical computer science with policy relevance, emphasizing the importance of evidence-based approaches to AI governance. His research increasingly addresses the limitations of prediction systems, the challenges of evaluating AI systems, and the need for transparency in foundation models. Presidential Early Career Award for Scientists and Engineers (PECASE) Privacy Enhancing Technologies Award (twice recipient) Privacy Papers for Policy Makers Award (three-time recipient) TIME's inaugural list of 100 most influential people in AI 2025 Graduate Mentoring Award Narayanan is recognized as an exceptional mentor, receiving Princeton's Graduate Mentoring Award in 2025. His policy engagement extends to congressional testimony, advisory roles, and frequent media commentary. He has secured significant research funding supporting his work on web transparency, AI policy, and cryptocurrency analysis. His research group has produced influential tools like OpenWPM for web privacy studies and contributed to foundational textbooks on cryptocurrencies and fairness in machine learning. At Princeton, Narayanan leads the Web Transparency and Accountability Project, a major research initiative that has conducted large-scale measurements of online tracking across millions of websites. He also co-founded and directs the CITP's AI Policy Initiative, which brings together researchers from multiple disciplines to address pressing AI governance questions. His work frequently involves collaboration with social scientists, legal scholars, and policymakers to develop practical solutions to technology governance challenges.

Tracey Evans CHANمشاهده پروفایل

دانشیار

• Biomedical Law
• Medical Ethics
• Healthcare Policy
• +۴ مورد دیگر

Tracey Evans Chan is an Associate Professor and Director of the NUS Law Academy at the National University of Singapore's Faculty of Law. His expertise lies in biomedical law and ethics, with a focus on issues such as surrogacy, transplant ethics, and human-animal research. He has held significant roles, including a secondment to Singapore's Ministry of Health, where he contributed to the Human Biomedical Research Act 2015. He currently serves on the National Medical Ethics Committee and the Advisory Committee on Restricted Research under the same Act, and is a member of NUS's Institutional Review Board. Education: LLM (Harvard University) LLB (National University of Singapore) Research Interests: Chan's work bridges legal and ethical dimensions of biomedical advancements. Key areas include regulatory challenges in mitochondrial replacement technology, consent frameworks for minors, and the ethical implications of emerging medical technologies. His contributions to Singapore's legal committees reflect his commitment to balancing innovation with societal values. Publications & Trends: His recent works explore themes like advance care planning, the placebo effect in clinical practice, and cross-jurisdictional comparisons of healthcare dependency laws. These publications underscore his interdisciplinary approach to legal and biomedical challenges. Awards & Grants: No specific awards or grants are listed, but his policy contributions and academic output highlight his impactful work in regulatory frameworks. Advising & Teams: As a faculty member, he teaches courses like Medical Law and Ethics. His involvement in NUS's Institutional Review Board and Singapore's advisory committees demonstrates his role in shaping research ethics and healthcare policy.

• Mental Health Policy
• Implementation Science
• Health Equity
• +۳ مورد دیگر

Briana S. Last is an Assistant Professor of Clinical Psychology at Stony Brook University, with a PhD from the University of Pennsylvania (2022). Her work focuses on improving mental health equity through policy research, implementation science, and community-based approaches. She examines social determinants of mental health, mental health workforce development, and clinical decision-making in public systems. Dr. Last leads the Mental Healthcare for All Lab, collaborating with governments, agencies, and clinicians to strengthen public mental health systems. Her research emphasizes workforce sustainability, anti-transgender policy impacts, and clinician well-being. She has published in high-impact journals like The Milbank Quarterly and Psychiatric Services . Her interdisciplinary methods combine qualitative and quantitative approaches, including mixed methods and implementation science frameworks. Current projects address workforce retention strategies, telehealth policy implications, and the sociopolitical context of gender-affirming care. Education: PhD in Clinical Psychology, University of Pennsylvania (2022) Labs: Mental Healthcare for All Lab Key Themes: Behavioral health policy, health equity, clinician-patient dynamics, LGBTQ+ mental health