Natalia Summerville
Director of Applied Data Science
Natalia Summerville is the Director of Applied Data Science in the Strategy and Innovation Division at Memorial Sloan Kettering Cancer Center. Her team develops data analytics products to support hospital strategy and innovations in care delivery, as well as cutting-edge cancer research. Previously, she led a team of Operations Research and Machine Learning experts at SAS, building analytical engines for customers across industries such as Health Care, Life Sciences, Retail, and Manufacturing. Natalia has been teaching undergrad and grad-level classes in Operations Research, Data Analytics, and Machine Learning since 2005, and she is currently an Adjunct Professor at Duke University. She is deeply passionate about the Data4Good movement and has been collaborating with many non-profit and mission-driven organizations to implement data analytics for social good. She is a board member within the “Pro-Bono Analytics” committee and is part of the “Franz Edelman Award” committee at INFORMS.
By This Author
Operations Research for Social Good: A Practitioner’s Introduction Using SAS® and Python
By Natalia Summerville and Rob Pratt
Advance your knowledge of operations research and social good!
Recent technological developments allow data analytics practitioners to solve large problems better and faster with state-of-the-art artificial intelligence (AI) tools. At the same time, humanity faces overarching challenges such as the climate crisis, child malnutrition, systemic racism, and global pandemics, among others. Operations Research for Social Good: A Practitioner’s Introduction Using SAS® and Python showcases operations research (OR) methodologies typically required in engineering curricula to applications targeted to make this world a better place.
Designed for data scientists, analytics and operations research practitioners, and graduate-level students interested in learning optimization modeling with applied use cases, this book provides the skills to model and solve OR problems with both SAS and Python as well as practical tools and tips to bridge the gap between academic learning and real-world implementations based on Data4Good initiatives.
Featured Authors
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.