Empowering Discovery Through Data
The Innovative Statistics and Data Research Center (ISDRC) is a U.S.-based research institution committed to advancing statistical science and data analytics for the public good. Founded in 2014, our mission is to bridge the gap between raw data and real-world decision-making by developing rigorous, innovative, and applicable statistical research.
We serve as a hub for researchers, policymakers, educators, and industries seeking to understand and leverage data in meaningful ways. From exploring social trends to developing predictive models in healthcare and economics, ISDRC stands at the intersection of methodology and impact.
Our Mission
Our Vision
What We Do
Conduct High-Impact Research
We develop and apply advanced statistical methodologies to analyze complex datasets, generating insights that matter.
Build Tools for Public Use
We create data platforms, visualization tools, and open-access resources that help others harness the power of statistics.
Support Evidence-Based Decision Making
Our research directly supports public and private institutions in developing smarter policies and strategies.
Train the Next Generation
Through workshops, fellowships, and internships, we prepare future statisticians and data scientists with practical and ethical foundations.
Our Values
Scientific Integrity – We adhere to the highest standards of accuracy, transparency, and reproducibility.
Collaboration – We believe in the power of interdisciplinary partnerships and shared knowledge.
Innovation – We constantly explore new techniques and methodologies to expand the frontiers of statistical research.
Accessibility – We are committed to making data and findings available and understandable to diverse communities.
Ethics – We advocate for the responsible use of data that respects privacy, context, and social implications.
Leadership
Dr. Nathaniel Chambers
Executive Director
Ph.D. in Statistics, University of Chicago
M.S. in Applied Mathematics, Columbia University
B.Sc. in Mathematics and Computer Science, Yale University
Dr. Nathaniel Chambers brings over two decades of experience at the intersection of statistical research, public policy, and applied data science. As Executive Director of ISDRC, he leads the organization’s mission to advance statistical innovation for social impact and scientific discovery.
Before joining ISDRC in 2017, Dr. Chambers served as Senior Advisor for Quantitative Research at the U.S. Department of Health and Human Services, where he oversaw national health survey analytics and developed statistical models to track healthcare access disparities. Earlier in his career, he was a tenured professor of statistics at the University of California, Berkeley, where he co-founded the Center for Computational Policy Analytics.
Dr. Chambers has authored over 40 peer-reviewed publications and was the lead architect behind two widely adopted tools for real-time data analysis in public sector environments. He has consulted for global institutions including the World Bank, UNICEF, and several state governments on topics ranging from predictive modeling in crisis response to statistical auditing of education systems.
A recipient of the ASA Award for Excellence in Public Statistical Practice, Dr. Chambers is known for advocating data ethics, transparency, and inclusivity in algorithm design. Under his leadership, ISDRC has expanded into key areas like AI fairness, civic tech, and climate data modeling while growing its education and fellowship programs nationwide.
Dr. Isaac Morrell
Director of Research
Ph.D. in Applied Mathematics, University of Chicago
M.S. in Econometrics and Quantitative Economics, London School of Economics
B.Sc. in Mathematics, University of Toronto
Dr. Isaac Morrell serves as the Director of Research at ISDRC, where he oversees the center’s multidisciplinary research agenda and ensures that all projects align with scientific excellence and public value. With a strong foundation in both theoretical statistics and applied econometrics, Dr. Morrell brings a deep commitment to research that advances policy, innovation, and social equity.
Before joining ISDRC in 2019, Dr. Morrell was Lead Quantitative Analyst at the Federal Reserve Board, where he developed macroeconomic forecasting models and risk-assessment tools used during fiscal crises. He later joined the private sector as Chief Data Scientist at an international consulting firm specializing in data-driven policy evaluation, where he led large-scale analytics projects for governments in North America, Europe, and Sub-Saharan Africa.
Dr. Morrell’s research spans causal inference, spatial statistics, high-dimensional modeling, and algorithmic transparency. His work has appeared in The Annals of Applied Statistics, Econometrica, and Policy Analysis Today. He is also known for his leadership in developing statistical frameworks that integrate administrative, survey, and big data sources.
An advocate for open science and reproducible research, Dr. Morrell has helped ISDRC launch initiatives in data ethics, civic statistics, and environmental analytics. He regularly advises doctoral students, serves on peer-review panels for NSF and NIH, and lectures globally on statistical infrastructure in public policy systems.
Dr. Rachel Lin
Director of Strategic Initiatives
Ph.D. in Quantitative Sociology, Stanford University
M.S. in Applied Statistics, University of Michigan
B.A. in Economics, University of Pennsylvania
Dr. Rachel Lin is a nationally recognized leader in applied statistics, computational social science, and strategic data innovation. As Director of Strategic Initiatives at ISDRC, she leads the development of high-impact, cross-sector collaborations and oversees initiatives that align the center’s research with public needs and policy relevance.
Before joining ISDRC in 2018, Dr. Lin served as Principal Data Scientist at the Brookings Institution, where she led multi-agency evaluations on employment policy, economic mobility, and housing access. Her contributions played a key role in designing inclusive economic indicators and improving the accessibility of government datasets.
Earlier in her career, Dr. Lin was on the faculty at NYU’s Center for Urban Science and Progress, where she taught courses on machine learning for public policy and mentored graduate students in interdisciplinary data analysis. She also served as a technical advisor to the United Nations Development Programme, focusing on data science applications for crisis forecasting and humanitarian aid distribution.
Dr. Lin’s research spans causal modeling, algorithmic fairness, and civic data systems. Her work has been featured in Nature Human Behaviour, Sociological Methodology, and The Washington Post. She is known for her ability to bridge academic insight with practical implementation, and her leadership has helped ISDRC launch new programs in digital equity, participatory data governance, and responsible AI.
