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Data Science for Undergraduates: Opportunities and Options (2018)

Chapter: Appendix A: Biographies of the Committee

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Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
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A

Biographies of the Committee

LAURA HAAS, Co-Chair, joined the University of Massachusetts Amherst in August 2017 as dean of the College of Information and Computer Sciences, after a long career at IBM, where she was accorded the title IBM Fellow in recognition of her impact. At the time of Dr. Haas’s retirement from IBM, she was director of IBM Research’s Accelerated Discovery Lab (2011-2017), after serving as director of computer science at IBM’s Almaden Research Center from 2005 to 2011. She had worldwide responsibility for IBM Research’s exploratory science program from 2009 through 2013. From 2001 to 2005, she led the Information Integration Solutions architecture and development teams in IBM’s Software Group. Previously, Dr. Haas was a research staff member and manager at Almaden. She is best known for her work on the Starburst query processor, from which the database server DB2 LUW was developed, on Garlic, a system that allowed integration of heterogeneous data sources, and on Clio, the first semiautomatic tool for heterogeneous schema mapping. She has received several IBM awards for Outstanding Innovation and Technical Achievement, an IBM Corporate Award for Information Integration Technology, the Anita Borg Institute Technical Leadership Award, and the Association for Computing Machinery (ACM) Special Interest Group on Management of Data Edgar F. Codd Innovation Award. Dr. Haas was vice president of the Very Large Data Bases Endowment Board of Trustees from 2004 to 2009 and served on the board of the Computing Research Association from 2007 to 2016 (vice chair, 2009-2015). She currently serves on the National Academies Computer Science and Telecommunications Board

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

(2013- 2019). She is an ACM fellow, a member of the National Academy of Engineering, and a fellow of the American Academy of Arts and Sciences.

ALFRED O. HERO III, Co-Chair, is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and R. Jamison and Betty Williams Professor of Engineering at the University of Michigan. Dr. Hero’s primary appointment is in the Department of Electrical Engineering and Computer Science, and he also has appointments, by courtesy, in the Department of Biomedical Engineering and the Department of Statistics. In 2008, Dr. Hero was awarded the Digiteo Chaire d’Excellence, sponsored by Digiteo Research Park in Paris, located at the Ecole Supérieure d’Electricité, Gif-sur-Yvette, France. He is an Institute of Electrical and Electronics Engineers (IEEE) fellow, and several of his research articles have received best paper awards. Dr. Hero was awarded the University of Michigan Distinguished Faculty Achievement Award (2011). He received the IEEE Signal Processing Society Meritorious Service Award (1998) and the IEEE Third Millennium Medal (2000). He was president of the IEEE Signal Processing Society (2006-2008) and was on the board of directors of the IEEE (2009-2011), where he served as director of Division IX (Signals and Applications). Dr. Hero’s recent research interests have been in detection, classification, pattern analysis, and adaptive sampling for spatiotemporal data. Of particular interest are applications to network security, multimodal sensing and tracking, biomedical imaging, and genomic signal processing. Dr. Hero received a B.S. (summa cum laude) from Boston University in 1980 and a Ph.D. from Princeton University in 1984, both in electrical engineering.

ANI ADHIKARI is a senior lecturer in statistics at the University of California, Berkeley. Dr. Adhikari has received the Distinguished Teaching Award at Berkeley and the Dean’s Award for Distinguished Teaching at Stanford University. While Dr. Adhikari’s research interests are centered on applications of statistics in the natural sciences, her primary focus has always been on teaching and mentoring students. She teaches courses at all levels and has a particular affinity for teaching statistics to students who have little mathematical preparation. Dr. Adhikari received an undergraduate degree from the Indian Statistical Institute and a Ph.D. in statistics from the University of California, Berkeley.

DAVID CULLER joined the faculty of the University of California, Berkeley, in 1989 and is currently the interim dean for Data Sciences. He was associate chair (2010-2012) and chair (2012-June 2014) of the Electrical Engineering and Computer Sciences department, the founding director of Intel Research, Berkeley, and co-founder of Arch Rock Corp.

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

Dr. Culler won the Okawa Prize in 2013. He is a member of the National Academy of Engineering, an Association for Computing Machinery fellow, and an Institute of Electrical and Electronics Engineers fellow. He has been named one of Scientific American’s “Top 50 Researchers” and the creator of one of MIT Technology Review’s “10 Technologies That Will Change the World.” Dr. Culler’s research addresses distributed systems for the built environment, networks of small, embedded wireless devices; planetary-scale Internet services; parallel computer architecture; parallel programming languages; and high-performance communication. Dr. Culler received a B.A. from the University of California, Berkeley, in 1980, and an M.S. and a Ph.D. from the Massachusetts Institute of Technology in 1985 and 1989, respectively.

DAVID DONOHO is an Anne T. and Robert M. Bass Professor of Humanities and Sciences and a professor of statistics at Stanford University. He is a member of the National Academy of Sciences and Foreign Associate of the French Académie des Sciences. He has worked in industrial research in oil exploration (Western Geophysical), in empirical finance (Renaissance Technologies), and co-founded a successful information technology start-up, BigFix, acquired by IBM. Dr. Donoho received an A.B. from Princeton University and a Ph.D. from Harvard University. He received a Macarthur Fellowship and was recipient of the 2013 Shaw Prize in Mathematical Sciences.

E. THOMAS EWING is an associate dean for Graduate Studies, Research, and Diversity in the College of Liberal Arts and Human Sciences and a professor in the Department of History at Virginia Tech. Dr. Ewing teaches courses in the history of data in social context, as well as courses in Russian, European, Middle Eastern, and world history; gender/women’s history; and historical methods. His publications include Separate Schools: Gender, Policy, and Practice in the Postwar Soviet Union (2010) and The Teachers of Stalinism: Policy, Practice, and Power in Soviet Schools in the 1930s (2002), and his articles on Stalinist education have been published in Gender & History, American Educational Research Journal, Women’s History Review, History of Education Quarterly, Russian Review, and Journal of Women’s History. He has received six grants from the National Endowment for the Humanities at the intersection of digital humanities, data analytics, and medical history projects. Dr. Ewing’s education includes a B.A. from Williams College and a Ph.D. in history from the University of Michigan.

LOUIS J. GROSS is an Alvin and Sally Beaman Distinguished Professor of Ecology and Evolutionary Biology and Mathematics and director of the Institute for Environmental Modeling at the University of Tennessee,

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

Knoxville (UTK). Dr. Gross is also director of the National Institute for Mathematical and Biological Synthesis, a National Science Foundation-funded center to foster research and education at the interface between math and biology. His research focuses on applications of mathematics and computational methods in many areas of ecology, including disease ecology, landscape ecology, spatial control for natural resource management, photosynthetic dynamics, and the development of quantitative curricula for life science undergraduates. Dr. Gross led the effort at UTK to develop an across-trophic-level modeling framework to assess the biotic impacts of alternative water planning for the Everglades of Florida. He has co-directed several courses and workshops in mathematical ecology at the International Centre for Theoretical Physics in Trieste, Italy, and he has served as program chair of the Ecological Society of America, president of the Society for Mathematical Biology, president of the UTK Faculty Senate, treasurer for the American Institute of Biological Sciences, and chair of the National Research Council Committee on Education in Biocomplexity Research. Dr. Gross is the 2006 Distinguished Scientist awardee of the American Institute of Biological Sciences and is a fellow of the American Association for the Advancement of Science and of the Society for Mathematical Biology. He has served on the National Research Council Board on Life Sciences and was liaison to the National Research Council Standing Committee on Emerging Science for Environmental Health Decisions. Dr. Gross completed a B.S. in mathematics at Drexel University and a Ph.D. in applied mathematics at Cornell University, and has been a faculty member at UTK since 1979.

NICHOLAS J. HORTON is Beitzel Professor of Technology and Society and professor of statistics at Amherst College. Dr. Horton is an applied biostatistician whose work is based squarely within the mathematical and computational sciences but spans other fields in order to ensure that biomedical research is conducted on a sound footing. He has published more than 170 papers in the statistics and biomedical literature and 4 books on statistical computing and data science. He has taught a variety of courses in statistics and related fields, including introductory statistics, data science, probability, theoretical statistics, regression, and design of experiments. He is passionate about improving quantitative and computational literacy for students with a variety of backgrounds as well as engagement and mastery of higher level concepts and capacities to think with data. Dr. Horton received the American Statistical Association (ASA) Waller Award for Distinguished Teaching, the Mathematical Association of America Hogg Award for Excellence in Teaching, the Mu Sigma Rho Statistics Education Award, and the ASA Founders Award. He was a co-principal investigator of the National Science Foundation-funded Project MOSAIC,

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

serves as the chair of the Committee of Presidents of Statistical Societies, is a fellow of the ASA and the American Association for the Advancement of Science, and was a research fellow at the Bureau of Labor Statistics. Dr. Horton earned an A.B. from Harvard College and an Sc.D. in biostatistics from the Harvard T.H. Chan School of Public Health.

JULIA LANE is a professor at the Center for Urban Science and Progress (CUSP) and at the New York University (NYU) Wagner Graduate School of Public Service. Dr. Lane also serves as a provostial fellow for innovation analytics and senior fellow at NYU’s GovLab. Dr. Lane is an economist who is the co-founder of the Longitudinal Employer–Household Dynamics (LEHD) partnership with the Census Bureau, which is now a major national statistical program. Dr. Lane has authored almost 80 refereed articles and edited or authored 10 books. Dr. Lane’s work to quantify the results of federal stimulus spending has been published in Science and Nature. She co-founded the new Institute for Research on Innovation and Science at the University of Michigan, which uses empirical evidence to describe the structure of the research workforce, the nature and evolution of research collaborations, and the diffusion of sponsored research results. Dr. Lane has had leadership positions in a number of policy and data science initiatives at her other previous appointments, which include senior fellow and senior managing economist at the American Institutes for Research; senior vice president and director, Economics Department at NORC/University of Chicago; various consultancy roles at the World Bank; and assistant, associate, and full professor at American University. Dr. Lane received a Ph.D. in economics and a master’s in statistics from the University of Missouri.

ANDREW McCALLUM is a professor and director of the Center for Data Science, as well as the Information Extraction and Synthesis Laboratory, in the College of Information and Computer Science at the University of Massachusetts Amherst. Dr. McCallum has published over 250 papers in many areas of artificial intelligence, including natural language processing, machine learning, and reinforcement learning; his work has received over 45,000 citations. In the early 2000s he was vice president of research and development at WhizBang Labs, a 170-person start-up company that used machine learning for information extraction from the web. Dr. McCallum is an Association for the Advancement of Artificial Intelligence fellow and the recipient of the UMass Chancellor’s Award for Research and Creative Activity, the UMass NSM Distinguished Research Award, the UMass Lilly Teaching Fellowship, as well as research awards from Google, IBM, Microsoft, and Yahoo. He was the general chair for the International Conference on Machine Learning 2012 and is the current

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

president of the International Machine Learning Society, as well as member of the editorial board of the Journal of Machine Learning Research. For the past 10 years, Dr. McCallum has been active in research on statistical machine learning applied to text, especially information extraction, entity resolution, social network analysis, structured prediction, semisupervised learning, and deep neural networks for knowledge representation. Dr. McCallum obtained a Ph.D. from the University of Rochester in 1995 with Dana Ballard and a postdoctoral fellowship from Carnegie Mellon University with Tom Mitchell and Sebastian Thrun.

RICHARD McCULLOUGH has been the vice provost for research (VPR) at Harvard University since 2012, working with the president and provost to encourage, cultivate, and coordinate high-impact academic research across all of Harvard’s schools and affiliated institutions. The office of the VPR has broad responsibility and oversight for the development, review, and implementation of strategies, planning, and policies related to the organization and execution of academic research across the entire university. Dr. McCullough leads a new office of foundation and corporate development. He also assists in oversight of many of the interdisciplinary institutes, centers, and initiatives across Harvard. Under Dr. McCullough’s leadership, the office of the VPR is particularly focused on removing barriers to collaboration, whether in university policies or in financial or administrative systems. Additionally, the VPR works with the president and provost to foster and encourage entrepreneurship among undergraduates, graduate students, and faculty members, and helps to lead the development of the new innovation campus. Dr. McCullough is also a professor of materials science and engineering at Harvard and is a member of numerous professional societies and boards. Prior to being named VPR at Harvard, Dr. McCullough was the vice president for research at Carnegie Mellon University in Pittsburgh, where he previously served as the dean of the Mellon College of Science and professor and head of the Department of Chemistry. Dr. McCullough has founded two companies: Plextronics, Inc., and Liquid X Printed Metals. Dr. McCullough has a B.S. in chemistry from the University of Texas, Dallas, and earned an M.A. and a Ph.D. in chemistry at Johns Hopkins University. He did his postdoctoral fellowship at Columbia University.

REBECCA NUGENT is the associate department head, the director of undergraduate studies, and a teaching professor in the Department of Statistics & Data Science at Carnegie Mellon University (CMU) and has been teaching at CMU since 2006. Dr. Nugent recently was awarded top teaching honors with the American Statistical Association Waller Education Award; the William H. and Frances S. Ryan Award for Mer-

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

itorious Teaching; and Statistician of the Year by the ASA Pittsburgh Chapter. Dr. Nugent’s research interests lie in clustering, record linkage, educational data mining/psychometrics, public health, tech/innovation/entrepreneurship, and semantic organization. Dr. Nugent received a B.A with majors in mathematics, statistics, and Spanish at Rice University and an M.S. in statistics at Stanford University. She completed a Ph.D. in statistics at the University of Washington in 2006.

LEE RAINIE is the director of Internet, science, and technology research at Pew Research Center. Under Mr. Rainie’s leadership, the center has issued more than 500 reports based on its surveys that examine people’s online activities and the role of the Internet in their lives. Mr. Rainie also directs the center’s new initiative on the intersection of science and society. The American Sociological Association gave Mr. Rainie its award for Excellence in Reporting on Social Issues in 2014 and described his work as the “most authoritative source of reliable data on the use and impact of the internet and mobile connectivity.” Rainie is a co-author of Networked: The New Social Operating System (MIT Press, 2012) and five books about the future of the Internet that are drawn from the center’s research. Mr. Rainie gives several dozen speeches a year to government officials, media leaders, scholars and students, technology executives, librarians, and nonprofit groups about the changing media ecosystem. He is also regularly interviewed by major news organizations about technology trends. Prior to launching Pew Research Center’s technology research, Mr. Rainie was managing editor of U.S. News & World Report. He is a graduate of Harvard University and has a master’s degree in political science from Long Island University.

ROB RUTENBAR joined the faculty at Carnegie Mellon University (CMU) in 1985. Dr. Rutenbar spent 25 years in electrical and computer engineering at CMU, ultimately holding the Stephen J. Jatras (E’47) Chair. He was the founding director of the Center for Circuit and System Solutions, a large consortium of U.S. schools (e.g., CMU, Massachusetts Institute of Technology, Stanford, Berkeley, Caltech, Cornell, Columbia, Georgia Tech, University of California, Los Angeles) supported by the Defense Advanced Research Projects Agency and the U.S. semiconductor industry, focused on design problems at the end of Moore’s Law scaling. In 2010, Dr. Rutenbar moved to the University of Illinois, Urbana-Champaign, where he was Abel Bliss Professor and head of the Department of Computer Science. At the University of Illinois, he pioneered the novel CS + X program, which combines a core computer science curriculum with a disciplinary “X” curriculum, leading to a bachelor’s degree in “X.” Student pipelines for CS + anthropology, astronomy, chemistry, and linguistics

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

are now under way, with several more CS + X degrees under design. Dr. Rutenbar now serves as senior vice chancellor for research at the University of Pittsburgh. His research has focused on three primary areas: tools for integrated circuit design, statistics of nanoscale chip designs, and custom architectures for machine learning and perception. In 1998 he founded Neolinear, Inc., to commercialize the first practical synthesis tools for nondigital ICs, and served as Neolinear’s chief scientist until its acquisition by Cadence in 2004. In 2006, he founded Voci Technologies, Inc., to commercialize enterprise-scale voice analytics. Dr. Rutenbar has won numerous awards, including the Institute of Electrical and Electronics Engineers Circuits and Systems Society Industrial Pioneer Award and the Semiconductor Research Corporation Aristotle Award. His work has been featured in venues ranging from Slashdot to the Economist. Dr. Rutenbar received a Ph.D. from the University of Michigan in 1984.

KRISTIN M. TOLLE is the director of the Data Science Initiative in Microsoft Research Outreach, Redmond, Washington. Dr. Tolle joined Microsoft in 2000 and has acquired numerous patents and worked for several product teams including the Natural Language Group, Visual Studio, and the Microsoft Office Excel Team. Since joining the Microsoft Research Outreach program in 2006, she has run several major initiatives from biomedical computing and environmental science to more traditional computer and information science programs around natural user interactions and data curation. She also directed the development of the Microsoft Translator Hub and the Environmental Science Services Toolkit. Dr. Tolle is an editor, along with Tony Hey and Stewart Tansley, of one of the earliest books on data science, The Fourth Paradigm: Data Intensive Scientific Discovery (Microsoft Research, 2009). Her current focus is developing an outreach program to engage with academics on data science in general and more specifically around using data to create meaningful and useful user experiences across device platforms. Dr. Tolle’s present research interests include global public health as related to climate change, mobile computing to enable field scientists and inform the public, sensors used to gather ecological and environmental data, and integration and interoperability of large heterogeneous environmental data sources. She collaborates with several major research groups in Microsoft Research including eScience, computational science laboratory, computational ecology and environmental science, and the sensing and energy research group. Prior to joining Microsoft, Dr. Tolle was an Oak Ridge Science and Engineering Research fellow for the National Library of Medicine and a research associate at the University of Arizona Artificial Intelligence Lab managing the group on medical information retrieval and natural language processing.

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

Dr. Tolle earned a Ph.D. in management of information systems with a minor in computational linguistics from the University of Arizona.

TALITHIA WILLIAMS takes sophisticated numerical concepts and makes them understandable and relatable to everyone. As illustrated in her popular TED Talk “Own Your Body’s Data,” Dr. Williams demystifies the mathematical process in amusing and insightful ways, using statistics as a way of seeing the world in a new light and transforming our future through the bold new possibilities inherent in the science, technology, engineering, and mathematics (STEM) fields. As an associate professor of mathematics at Harvey Mudd College, Dr. Williams has made it her life’s work to get people—students, parents, educators, and community members—more excited about the possibilities inherent in a STEM education. In her present capacity as a faculty member, she exemplifies the role of teacher and scholar through outstanding research, with a passion for integrating and motivating the educational process with real-world statistical applications. Her professional experiences include research appointments at the Jet Propulsion Laboratory, the National Security Agency, and NASA. Dr. Williams develops statistical models that emphasize the spatial and temporal structure of data and has partnered with the World Health Organization in developing a cataract model used to predict the cataract surgical rate for countries in Africa. Through her research and work in the community at large, she is helping change the collective mind-set regarding STEM in general and math in particular—rebranding the field of mathematics as anything but dry, technical, or male dominated but instead a logical, productive career path that is crucial to the future of the country. Dr. Williams’s educational background includes a bachelor’s degree in mathematics from Spelman College, master’s degrees both in mathematics from Howard University and in statistics from Rice University, and a Ph.D. in statistics from Rice University.

ANDREW ZIEFFLER is a senior lecturer and researcher in the Quantitative Methods in Education program within the Department of Educational Psychology at the University of Minnesota. Dr. Zieffler teaches undergraduate- and graduate-level courses in statistics and trains and supervises graduate students in statistics education. His scholarship primarily focuses on statistics education, and he has authored or co-authored several papers and book chapters related to statistics education. Additionally, he has been a co-principal investigator on many National Science Foundation-funded statistics education research projects. Dr. Zieffler has co-authored two textbooks that serve as an introduction to modern statistical and computational methods for students in the educational and behavioral sciences. He currently serves as co-editor of the jour-

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×

nal Technology Innovations in Statistics Education and as a member of the Research Advisory Board for the Consortium for the Advancement of Undergraduate Statistics Education. Dr. Zieffler received his Ph.D. in quantitative methods in education from the University of Minnesota in 2006.

Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 95
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 96
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 97
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 98
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 99
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 100
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 101
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 102
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 103
Suggested Citation:"Appendix A: Biographies of the Committee." National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. doi: 10.17226/25104.
×
Page 104
Next: Appendix B: Meetings and Presentations »
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Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent.

Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

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