NVTC Data Science Speaker Series
In 2021, the Virginia Tech Academy of Data Science partnered with the Northern Virginia Technology Council (NVTC) to launch the NVTC Data Science Speaker Series.
The series of virtual events was created to showcase the impact of data science in the modern era and how it is changing the way business and science are being conducted, serves as the basis of government policy, and shapes our world.
To view past events in the series, visit the Northern Virginia Technology Council website or click on the the links below.
It has become a necessity for organizations to be data-driven; the COVID-19 pandemic catapulted digital transformation projects into the must-have category. Data science, artificial intelligence and machine learning are key ingredients in the transformation toward more agile, resilient, faster, relevant and more contextual decisions.
Keynote presenter Oliver Schabenberger discusses the hype and reality of digitally transforming, data-driven organizations and provide his insights into a future state for data science. A panel discussion featuring Phil Vincenzes, chief analytics officer, IntelliDyne LLC; Alan Lattimer, chief data scientist, Socially Determined; and moderator Jennifer Van Mullekom, assistant professor of practice in statistics and director of the Statistical Applications and Innovations Group (SAIG) at Virginia Tech, follows.
Technology is advancing every day; we believe oversight should, too. During this event, hear from keynote speaker Taka Ariga, chief data scientist and director of the Innovation Lab at the U.S. Government Accountability Office. Learn how the U.S. Government's Innovation Lab is empowering the U.S. Government Accountability Office with new capabilities and enhanced capacity to tackle evolving accountability challenges.
Nirup Menon, associate dean at the George Mason University School of Business, and Vishal Ranjan, vice president of consulting services at CGI Federal, join moderator Stu Kippelman, the CIO at Parsons, for a post-keynote panel discussion.
Location Intelligence can help to solve some of our society's biggest challenges. We know that understanding human movement patterns, and how they change over time is key to better stewardship and enables local governments to make policy decisions based on data, not opinion.
In this presentation, keynote speaker Jeff White, CEO of Gravy Analytics and a Virginia Tech alumnus, shares specific examples of how location intelligence is helping us recover from disaster in today's uncertain environment. A panel discussion featuring Julie Kae, vice president of sustainability and diversity, equity and inclusion at Qlik; Patrick O'Neil, chief data scientist at BlackSky; and moderator Barbara Hoopes, the academic director for MBA programs and associate professor in business information technology at Virginia Tech, follows the keynote presentation.
The 2011 film Moneyball depicts Oakland A's general manager Billy Beane's struggles during the 2002 season to get his coaches and scouts to adopt a data-first strategy instead of relying on eye-based scouting. Almost 11 years later, utilizing predictive analytics and other techniques in the Data Science toolkit in sports is no longer a novel idea. While almost every front office has an analytics team, actual implementation of these powerful tools varies greatly. So how exactly does science impact sports performance?
During this event, keynote speaker Paul Sabin, a sports data scientist for ESPN, discusses how data science is being used to improve team and player performance and outcomes. He also shares what future frontiers in data science are being explored in the growing field of sports analytics. A panel discussion featuring Christian Matthews, vice president for strategy and sponsorship with the Washington Commanders; Ken Pomeroy, college basketball analyst and creator of KenPom.com; Zac Robertson, director of basketball analytics and research for the Miami Heat; and moderator Tanya Coutray, analytics strategy leader at Amazon Web Services, will follow Sabin’s keynote presentation.
Data science is one of the top 20 fastest-growing occupations in the U.S., and the U.S. Bureau of Labor Statistics projects a 22% growth between 2020 and 2030. Yet women make up only 27% of data science jobs in the U.S. (Harnham report).
Research has proven that diverse teams yield better results and reduce risks. In addition, organizations that demonstrate inclusivity and create cultures of belonging are more likely to attract diverse candidates. In a data-driven world, individuals who code and build algorithms have a direct impact on their accuracy and outcomes. With more diverse teams, unconscious bias can be mitigated.
Keynote speaker Judy Logan, co-director of Women in Data Science (WiDS) Stanford University, shares how the organization’s work has helped attract women to the data science field. A panel of female data science experts — Poornima Ramaswamy, chief transformation officer at Qlik; Radha Sambasivan, vice president of software development at Mastercard; and moderator Angie Patterson, professor of practice in statistics and co-director of the Computational Modeling & Data Analysis (CMDA) Capstone course at Virginia Tech — discuss progress they have seen, keys for success, and remaining challenges.