Annual Women in Data Science Blacksburg event returns for its sixth year
The two-day event is free for all participants.
Over the past decade, the demand for data scientists in the workforce has grown exponentially. According to the U.S. Census Bureau, that demand is expected to increase another 35 percent by 2032.
Yet as the demand in the field continues to increase, women remain underrepresented, making up less than a quarter of professionals working in data science.
As part of the mission to increase participation of women in data science and feature outstanding women in the field, the annual Women in Data Science (WiDS) Blacksburg event will return to Virginia Tech on Feb. 12-13. This free event welcomes anyone with an interest in data science — whether on campus or in the community — to attend.
About the event
Now in its sixth year, Women in Data Science Blacksburg is an independent event organized by Virginia Tech as part of the Women in Data Science Worldwide movement, which seeks to elevate women in the field of data science by inspiring, educating, and supporting women data scientists. After starting as a single conference at Stanford University in 2015, it has expanded to a global organization with participation across six continents and a suite of programs that feature, connect, and highlight outstanding women doing outstanding work.
Despite the name, all genders are invited and encouraged to attend conference events.
“It’s important for us to have events like this at Virginia Tech – events that bring together those who are interested in the data science community,” said Angie Patterson, professor of practice in the Department of Statistics and co-organizer of Women in Data Science Blacksburg. “Because we have a wide range of students and faculty at Virginia Tech who are working either specifically in data sciences or in other scientific areas that highly leverage data, this event provides an opportunity for everyone in this broader data science community to come together and talk about some of the exciting things that are going on in the field.”
Women in Data Science Blacksburg 2024 will kick off on Monday, Feb. 12, with a networking mixer from 5:30-7 p.m. The mixer will take place in the atrium of the Data and Decision Sciences Building, which opened in fall 2023 to encourage transdisciplinary teaching and learning and facilitate cross-college collaborations in the field of data science.
Co-organizer Monica Ahrens, a research scientist at the Center for Biostatistics and Health Data Science, said: “We’re excited to offer the networking mixer this year, providing a fun and friendly environment for students, faculty, and professionals alike to expand their networks. It’s interview season for many students, which is prime time for them to practice the art of conversation and networking.”
The main program of this year’s event is scheduled from 5-8:45 p.m. in the 220 New Classroom Building. The short conference format will feature:
- Opening keynote: Alison Motsinger-Reif
- Motsinger-Reif is the branch chief and a senior investigator in the biostatistics and computational biology branch at the National Institute of Environmental Health Sciences. Her primary research is the development of computational methods to detect genetic risk factors of complex traits in human populations.
- Student poster session
- Panel discussion: “Getting Recognition for Excellence in Data Science”
- Moderated by Ph.D. students Alicia Arneson of the Department of Biology and Adeline Guthrie of the Department of Statistics
- Panelists include:
- McKenna Magoffin, data scientist at Socially Determined
- Rebecca Medlin, research staff member at the Institute for Defense Analyses
- Gina Maria Pomann, associate professor of biostatistics and bioinformatics at Duke University
- Sarah Ratcliffe, professor and director of the Division of Biostatistics in the Department of Public Health Sciences at the University of Virginia
- Closing keynote address: Rebecca Nugent
- Nugent is the department head in the Department of Statistics at Carnegie Mellon University. Her current research focus is the development and deployment of low-barrier data analysis platforms that allow for adaptive instruction and the study of data science as a science.
For up-to-date details on Women in Data Science Blacksburg, including registration information and the full agenda, visit the event website.