William Adler, Kyle Novak, and Jiayang Sun were selected as fellows for the inaugural ASA/ACM/AMS/IMS/MAA/SIAM 2019-2020 Science and Technology Policy Fellowship and will begin their appointments this month.
Adler earned his PhD in computational neuroscience from New York University in 2018. He has been working with the Princeton University Gerrymandering Project in the role of computational research specialist to develop tools to help citizens understand district maps and fairness in redistricting. His community service includes working as a data scientist with DataKind on a project with an education startup to track college persistence. Adler will serve as a congressional fellow.
Novak earned his PhD in applied mathematics from the University of Wisconsin – Madison in 2006. Since 2017, he has worked with the US Agency for International Development as a AAAS Science and Technology Policy Fellow researching the use and impact of emerging and digital technologies like machine learning, blockchain, big data, open data, and real-time data in low-income countries. He also has worked with DataKind, collaborating with other data scientists to analyze air quality data and assess impacts of humanitarian aid. Additionally, Novak contributed to the OpenStreetMap’s Missing Maps project to help digitally map countries such as Côte d’Ivoire. He will serve as a congressional fellow.
Sun earned her PhD in statistics from Stanford University in 1989 and is a fellow of the ASA. Until recently, she was a professor at Case Western Reserve University in the department of population and quantitative health sciences. She will begin a new position as professor and chair of the department of statistics at George Mason University at the conclusion of her fellowship. Her interdisciplinary work includes cancer epidemiology, environmental science, imaging, neuroscience, surgery, wound care, astronomy, computer science, energy, and law. Her service includes work with the Caucus for Women in Statistics (CWS), for which she was the 2016 president. As president, she led an effort to modernize the CWS web presence. Her fellowship placement is with the US Department of Agriculture.
When asked what he hopes to achieve, Adler responded, “I hope that I will be able to use my technical skills to help whichever office I join make meaningful changes to policy. I also hope to gain a stronger understanding of how statistical findings and ways of thinking can have an impact in Congress.”
As the fellowship name indicates, the ASA collaborated with the Association for Computing Machinery (ACM), American Mathematical Society (AMS), Institute for Mathematical Statistics (IMS), Mathematical Association of America (MAA), and Society for Industrial and Applied Mathematics (SIAM) to recruit applicants with expertise in statistics and data science. These partners used their networks to promote the program through organizations devoted to increasing diversity in the mathematical sciences.
The fellows will help realize a future envisioned by the Commission on Evidence-Based Policy Making: A future in which rigorous evidence is created efficiently as a routine part of government operations and used to construct effective public policy.
The fellows are supported by a grant from the Alfred P. Sloan Foundation and will help establish the “learning agenda” for the federal government envisioned by the commission’s 2017 report by bringing expertise to such areas as data science, machine learning, data visualization, and causal inference.
The selection committee was chaired by ASA Past President Lisa LaVange, ASA President Karen Kafadar, and ASA President-elect Wendy Martinez. Also serving on the committee were representatives from the ASA Committee on Minorities in Statistics, Government Statistics Section, and Section on Statistical Learning and Data Science, along with representatives from the AAAS, AMS, ACM, IMS, MAA, and SIAM.
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