Emma Brunskill is an Associate Professor of Computer Science at Stanford University, with a courtesy appointment in Education. She holds a PhD in Computer Science from MIT (2009). Her research focuses on reinforcement learning, educational technology, and healthcare applications, aiming to develop AI systems that support human learning and decision-making. Notable projects include AI tutoring systems, policy evaluation methods, and behavior change interventions using large language models. Her work bridges theory and practice, addressing challenges in off-policy evaluation, fairness-aware decision making, and scalable educational tools. Brunskill has contributed to foundational research in reinforcement learning algorithms and their applications in real-world scenarios such as healthcare, education, and human-AI collaboration. She also leads initiatives to improve equity and efficiency in educational technologies through data-driven approaches. Brunskill's research has been supported by grants such as the NSF RI: Small grant for data-efficient reinforcement learning. She actively explores the ethical implications of AI systems, particularly in healthcare and education settings. Her recent work emphasizes leveraging large language models (LLMs) for personalized feedback and simulated training environments, as seen in studies like GPTCoach and LLM-based counselor upskilling.
Dustin Tingley is a Professor of Government at Harvard University and holds a joint appointment at the Harvard Kennedy School of Public Policy . He serves as Interim Vice Provost for Advances in Learning and directs the Data Science and Technology Group and the Harvard Initiative on Learning and Teaching . He earned a PhD in Politics from Princeton and a BA in political science and math from the University of Rochester. Key Roles : Deputy Vice Provost (past), Chair of Harvard's Standing Committee on Climate Education Research Focus : Climate change politics, data science, causal inference, and international political economy His recent work explores the political economy of climate transitions , public opinion on carbon policies , and machine learning applications in social sciences . He co-founded ABLConnect , a repository for active learning pedagogy, and organized conferences on causal mechanisms , teaching with AI , and equitable classrooms . Awards : Gladys M. Kammerer Award (2015) for co-authored book Sailing the Water’s Edge Notable Publications : Uncertain Futures: How to Unlock the Climate Impasse (2023, with Alex Gazmararian) The Political Economy of the Clean Energy Transition (2025)
James S. Kim is a Professor of Education at Harvard University's Graduate School of Education, where he conducts policy-relevant research focused on improving literacy outcomes for low-income students and struggling readers. With an Ed.D. from Harvard University (2002), he leads the READS Lab (Research Enhances Adaptations Designed for Scale in Literacy), a research team that partners with school districts to solve literacy challenges through evidence-based interventions. Dr. Kim's research centers on understanding how building students' domain knowledge and reading engagement can foster long-term improvements in reading comprehension. His work emphasizes experimental design and evidence-based interventions, with a particular focus on addressing educational inequality. His research interests include early education, education policy, evidence-based intervention, human development, inequality and education gaps, informal and out-of-school learning, language and literacy development, and teachers and teaching. Kim's most significant contribution is the Model of Reading Engagement (MORE), a spiraled and sustained content literacy intervention co-developed with schoolteachers that has been shown to improve first to third-grade students' reading comprehension in science, English language arts, and math. Notably, research on MORE meets WWC (What Works Clearinghouse) standards without reservation, and long-term follow-up suggests the intervention's impact persists through fourth grade. His publications reveal a consistent focus on content literacy, domain knowledge development, and transfer effects in reading comprehension. Research on MORE meets WWC standards without reservation Long-term effects of MORE persist through fourth grade Commitment to Open Science principles (open data, open materials, preregistration) As a servant leader, Kim builds long-term partnerships with school districts to implement literacy interventions at scale. His READS Lab promotes open science practices while developing practical solutions to literacy challenges. His research on summer reading interventions, parental text messaging, and classroom-based content literacy approaches demonstrates his commitment to translating research into practice. Kim's current work includes scaling the MORE intervention to improve reading comprehension for high-needs students in moderate to high poverty schools through a Department of Education-funded project (2024-2028).
Bo Wu is an Associate Professor in the Department of Computer Science at Colorado School of Mines. His research focuses on compilers and programming systems, particularly program optimizations for heterogeneous computing and emerging architectures, with applications in machine learning and graph processing. He joined Mines in 2014 after earning a Ph.D. from The College of William and Mary and earlier degrees from Central South University in China. Education : B.S. in Computational Science and Technology (Central South University, 2005) M.S. in Computer Science (Central South University, 2008) Ph.D. in Computer Science (The College of William and Mary, 2014) Research Interests : Wu's work emphasizes enhancing data locality in heterogeneous systems, GPU scheduling, and optimizing applications for emerging architectures. His contributions include frameworks like GraphZero for efficient graph mining and FLEP for GPU preemption. Awards & Grants : NSF SPX Award (2018) NSF CAREER Award (2018) Supercomputing Best Paper Award (2015) Multiple NSF grants for GPU-related research Advising & Grants : Wu has led several NSF-funded projects and actively participates in conference program committees (e.g., PPoPP, SC, ICS). His research spans compiler optimizations, parallel computing, and high-performance systems. Labs & Teams : While specific labs aren’t named, his work involves collaborations on GPU-based systems, graph processing frameworks, and compiler toolchains.
Dr. Tristan A.F. Long is an Associate Professor in the Department of Biology at Wilfrid Laurier University's Faculty of Science in Waterloo, Ontario. A behavioral ecologist and evolutionary geneticist, he focuses on sexual selection and the role of female mate preference variation in evolutionary change. With teaching responsibilities for large introductory biology courses like BI111 and BI393, he has developed innovative active learning techniques using playing cards, iClickers, and role-playing games to teach population genetics and ecological principles. University of Western Ontario - BSc in Honours Ecology and Evolution (1999) University of Guelph - MSc in Zoology (2001) Queen’s University - PhD in Biology (2005) University of California Santa Barbara - Postdoctoral Fellow (2005-2009) University of Toronto - Postdoctoral Fellow (2009-2010) His research examines how female Drosophila melanogaster vary in their mating preferences and how these differences shape evolutionary trajectories. He has published extensively on reproductive plasticity, sexual conflict, and environmental interaction effects. His laboratory combines experimental evolution with computational modeling to explore genetic trade-offs and behavioral adaptations. Scientific awards include the Laurier Teaching Award for Sustained Excellence (2017). He has developed innovative classroom techniques like the Battle of the Beaks exercise for teaching adaptive evolution and an iClicker-based population genetics simulation using playing cards. His 2024 BI393 biostatistics course policy strongly discourages generative AI use due to concerns about educational integrity and environmental impact.
Professor Michael Naef is the Head of the Department of Economics and a Professor at Durham University's Business School. His research focuses on Experimental and Behavioral Economics and Neuroeconomics , exploring topics such as trust dynamics, cultural influences on cooperation, and neurochemical effects on decision-making. He leads the Department of Economics within a triple-accredited business school, emphasizing academic excellence and global connections. Key research interests include investigating how dopamine receptors modulate trust behavior, the origins of cooperative behavior in rice-farming cultures, and the role of testosterone in social interactions. His work combines experimental economics with neuroscience and psychology, often employing pharmacological interventions and neuroimaging techniques. Publications highlight contributions to understanding volatility in trust beliefs (2023), the neurobiological basis of social learning (2019), and testosterone's influence on competitiveness (2017). He advises PhD students Angel Li and Zekun Lin, focusing on advancing behavioral economic theory and applications. Prof. Naef's research has implications for understanding cultural economic differences, mental health impacts on decision-making, and the biological underpinnings of social preferences. His work bridges disciplines, fostering interdisciplinary collaborations in economics, neuroscience, and endocrinology.
Ronald D. Haynes is a Full Professor and Chair of Scientific Computing Graduate Programs in the Department of Mathematics and Statistics at Memorial University of Newfoundland. He leads research in numerical methods for PDEs and industrial-scale optimization problems. His work develops advanced domain decomposition techniques, adaptive mesh methods, and parallel computing approaches for solving complex physical systems. Applications include modeling pitting corrosion of materials, predicting rock strength for drilling optimization, and simulating multiphase fluid flows in porous media. Recent publications demonstrate innovations in mesh adaptation, parallel algorithms, and machine learning applications for industrial problems. Collaborative projects have addressed reservoir simulation, drill bit analysis, and corrosion prediction through integrated computational approaches. Professor Haynes has received the President's Award for Outstanding Research (2018) and Dean of Science Distinguished Teaching Award (2017). He serves as Co-editor-in-chief of the CAIMS Mathematics in Science and Industry Journal and was President-Elect of the Canadian Applied and Industrial Mathematics Society (2023-2025). He maintains active doctoral supervision with current research groups focusing on domain decomposition methods, closest point algorithms, and optimization techniques. Industry partnerships include projects with ExxonMobil and Global Maritime addressing drilling optimization and mooring design challenges.
Prof. Dr. Katja Scharenberg is a faculty member at the Ludwig-Maximilians-Universität München (LMU) , affiliated with the Faculty of Psychology and Education. Her research focuses on inclusive education, heterogeneity in classrooms, teacher training, science education, and sustainability education. She leads and collaborates on multiple projects funded by the German Federal Ministry of Education and Research (BMBF) and the European Union’s Horizon 2020 program. Her work examines how heterogeneous learning environments impact student outcomes, particularly in science and sustainability education. She investigates teacher diagnostic competence in inclusive settings and develops digital learning environments to support accessible experimentation. Current projects include evidence-based modular continuing education programs for teachers and studies on ethnic school segregation’s effects on educational attainment in Germany and Switzerland. Key publications include empirical analyses of sustainability competencies in schools, inclusive pedagogy in primary and vocational education, and classroom dynamics affecting students with special educational needs. She serves on editorial boards and collaborates with networks like the European Association for Research on Learning and Instruction (EARLI) and the Deutsche Gesellschaft für Erziehungswissenschaft (DGfE) . Her research is supported by grants from the BMBF and EU Horizon 2020 . She supervises students in inclusive education and teacher training, and her work integrates research-based learning with practical school reforms in the Freiburg region.
Inci Dirim is a Professor at the Department of German Studies within the Faculty of Philology and Cultural Studies at the University of Vienna . Her work focuses on German as a Second Language (DaZ) , multilingualism, migration pedagogy, and educational equity. She has developed diagnostic tools for language assessment, contributed to curriculum design, and critically analyzed discrimination mechanisms in language education. Education : Magistra Artium (MA) in Linguistics and German Studies from the University of Bremen (1991); PhD in Educational Science from the University of Hamburg (1997) Her research emphasizes language diagnostics , cultural identity , and reflexive pedagogy , particularly in contexts of linguistic and social heterogeneity. She has led projects like TESSLA (language support for multilingual children) and Unterrichtsbegleitende Sprachstandsbeobachtung DaZ (classroom language assessment). Recent publications explore inter- and transdisciplinary approaches to DaZ, normative foundations in language teaching, and separation practices in language promotion. She serves as a key figure in the Austrian Association for German as a Foreign/Second Language (ÖDaF) and the German Society for Educational Science (DGfE) , advocating for critical perspectives on language, migration, and education. Her teaching includes courses on Basics of German as a Foreign and Second Language , Modern German Literature , and Language Diagnostics .
Michael J. Kieffer is a Professor of Literacy Education at New York University’s Steinhardt School of Culture, Education, and Human Development. His research focuses on language and literacy development for linguistically diverse students, particularly multilingual learners in urban schools. He has published over 50 articles and secured significant grants, including a $1.4 million IES grant for a study on heterogeneous grouping’s impact on English learners. He leads the Center for the Success of English Learners (IES-funded) and co-directs NYU’s IES-funded Predoctoral Interdisciplinary Training program. Dr. Kieffer’s work emphasizes interdisciplinary collaboration, spanning developmental psychology, applied statistics, special education, and policy. His research has been funded by the Institute of Education Sciences (IES), Spencer Foundation, American Educational Research Association, and International Reading Association. He advocates for policies and instructional practices that enhance access to the general curriculum for secondary English learners. Key research interests include the effects of classroom composition, academic vocabulary instruction, and the role of supportive relationships in academic success. He has explored longitudinal reading development, morphological awareness, and the intersection of executive functions with literacy skills in bilingual adolescents. Dr. Kieffer has received awards from the American Educational Research Association and International Reading Association. His current projects include evaluating algebra curricula for English learners and analyzing system-level practices affecting their educational outcomes. He collaborates with policymakers to translate research into actionable strategies for schools and districts.
Kristy Robinson is an Associate Professor in the Department of Educational and Counselling Psychology at McGill University , where she investigates classroom teaching practices and contextual factors that enhance student motivation and wellbeing. Her research program focuses on creating theoretical and empirical frameworks to support equitable instructional strategies for students' goal achievement. SSHRC-funded researcher FQRSC grant recipient Key Research Areas Motivational climate theory Expectancy-value-cost models STEM education equity Self-determination theory Emotion dynamics in learning Awards & Recognition Canadian Psychological Society President's New Researcher Award AERA Division C Outstanding Early Career Scholar AERA Motivation SIG Wilbert C. McKeachie Early Career Award Top-Producing Educational Psychology Scholar (2024) Research Platforms Director of MILES Lab (Motivation, Instructional, and Learning Experience Study) Developer of "mFlip" flipped classroom framework
Alejandro J. Ganimian is an Associate Professor of Applied Psychology and Economics (with tenure) at New York University's Steinhardt School of Culture, Education, and Human Development, and a Visiting Associate Professor of Education at the Harvard Graduate School of Education. His interdisciplinary research bridges economics, psychology, and education policy to address critical challenges in educational systems, particularly in low- and middle-income countries, with a focus on transitioning from providing schooling to ensuring learning for all. Education: Doctorate in Quantitative Policy Analysis in Education (with concentration in economics) from Harvard University, where he was a fellow in the Multidisciplinary Program in Inequality and Social Policy Master's in Educational Research from the University of Cambridge, where he was a Gates Scholar Bachelor's in International Politics from Georgetown University Postdoctoral fellow at the Abdul Latif Jameel Poverty Action Lab (J-PAL) Ganimian's research centers on addressing educational challenges for "first-generation learners" in low- and middle-income countries. His methodology combines cutting-edge experimental designs from economics with innovative measures from education and psychology to evaluate causal effects of policies at scale. He specifically investigates how to prepare children for educational transitions, support teachers in large heterogeneous classrooms, and encourage principals to allocate resources to students who need them most. His work spans educational assessment, technology in education, teacher policies, and school management, with fieldwork conducted primarily in Latin America and South Asia. His research has been published in top journals including Nature , American Economic Review , Journal of Political Economy , and Review of Educational Research . Scientific Awards and Affiliations: Jacobs Foundation Research Fellow National Academy of Education/Spencer Foundation Post-Doctoral Fellow Gates Scholar Advisory-Board member at the Organization of Ibero-American States for Education, Science, and Culture (OEI) Non-Resident Fellow at the Center for Universal Education at the Brookings Institution Invited Researcher at the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT Member of the CESifo Network on Economics of Education Ganimian actively mentors doctoral students at NYU, with primary advisee Verónica Mesalles and secondary or co-advisees including Sorana Acris, Berta Bartoli, Arja Dayal, Trenel Francis-Porter, and Jessica Siegel. His former advisees have secured prestigious positions at institutions including Oxford University, UC Irvine, Duke University, and Stanford University. He has consulted for major international organizations including the Bill & Melinda Gates Foundation, World Bank, and Inter-American Development Bank, and co-founded educational initiatives "Enseñá por Argentina" and "Educar y Crecer" in Argentina.
Gigi Luk is Professor and Program Director for M.Ed. Concentrations in Educational Psychology and Human Development within the Department of Educational and Counselling Psychology at McGill University's Faculty of Education. Her research program investigates the cognitive consequences of bilingualism across the lifespan, bridging scientific understanding with practical educational applications to cultivate inclusive environments for linguistically diverse learners. Her educational background includes: Ph.D. in Psychology (Developmental and Cognitive Processes) from York University M.A. in Psychology (Developmental and Cognitive Processes) from York University Specialized Honors B.A. in Psychology from York University Dr. Luk's research centers on bilingualism's cognitive and neural mechanisms, with three interconnected thrusts: (1) characterizing bilingualism beyond English proficiency in communities, (2) examining cognitive skills supporting language/literacy outcomes, and (3) establishing neural correlates of learning in diverse language learners. Her work integrates cognitive neuroscience with educational practice to address real-world challenges in multilingual classrooms, emphasizing culturally responsive pedagogy that respects linguistic diversity. This dual focus on basic science and practical implementation defines her contributions to understanding how bilingual experiences shape cognitive development and educational equity. Analysis of her 15 most recent publications (2022-2024) reveals consistent interdisciplinary investigation of bilingualism through cognitive, neural, and sociocultural lenses. Her work spans educational psychology, cognitive neuroscience, and sociolinguistics, with growing emphasis on neural correlates of language processing, methodological rigor in bilingual assessment, and equity implications of bilingual research. Key trends include examination of multilingual children's cognitive development, critical reframing of the "bilingual advantage" discourse, and innovative approaches like music-based literacy interventions. Scientific recognition includes: National Academy of Education/Spencer Postdoctoral Fellowship (2013-2014) Dr. Luk actively supervises graduate students (accepting new students for 2025-2026) and secures competitive research funding, currently supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Fonds de recherche Société et culture (FRQSC). Her grant portfolio demonstrates sustained commitment to advancing understanding of bilingual cognition and its educational applications through rigorous empirical work. She directs the Bilingualism.Experience.Education Lab, which functions as an interdisciplinary hub for investigating how language experiences shape cognitive development and educational outcomes. The lab employs diverse methodologies including neuroimaging, behavioral experiments, and classroom-based research to address questions about bilingualism's cognitive effects and practical implications for educators.
Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement. Her academic credentials include: PhD in Electrical Engineering from Stanford University (2019) MS in Electrical Engineering from Stanford University (2015) BS in Electrical Engineering and Computer Science from UC Berkeley (2013) Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education. Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses. She received recognition through: The Faculty Award for Outstanding Mentorship of GSIs (2024) Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations. Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.
Kyra Renftel is a Professor in Empirical Educational Research in Mathematics Didactics at Leuphana University of Lüneburg. Her research focuses on mathematics education, particularly in inclusive educational settings, formative assessment, and feedback mechanisms. Her work investigates how diagnostic strategies and feedback practices are implemented in inclusive mathematics classrooms, addressing challenges like time constraints and student engagement with written feedback. Recent projects include analyses of learning materials for the Pythagorean Theorem and studies on the impact of feedback types on student performance. Kyra’s publications from 2023–2025 highlight her contributions to inclusive teaching methodologies, curriculum design, and classroom processes in secondary mathematics education.
