WiDS Charlottesville 2023

Women in Data Science (WiDS) Charlottesville is an independent event that is organized by the University of Virginia School of Data Science as part of the annual WiDS Worldwide Conference. First hosted by Stanford University in 2015, the conference has now grown to nearly 200 events worldwide in more than 50 countries. WiDS features women doing outstanding work in the field of data science, and all genders are invited to attend conference events.

WiDS Charlottesville 2023 will be held in person at the University of Virginia with live stream options. Closed captioning will be included with the live stream, as well as during the event. Listening headsets will also be available for those who need them. If you require any other accommodations please reach out to the event organizers. All genders are invited to attend the conference.

Access the Livestream

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Program Agenda

9:00-10:00 a.m.

Check-In | Lobby

10:00-10:15 a.m.

Welcome and Introductions | Auditorium

10:15-11:15 a.m.

Fireside Chat with Kelli Palmer | Auditorium
Kelli Palmer, Chief Diversity Officer, WillowTree
Siri Russell, Associate Dean of DEI, UVA School of Data Science

11:15-11:30 a.m.

Break

11:30 a.m.-12:30 p.m.

Careers in Data Science Panel | Auditorium
May Casterline, Principal Solutions Architect, NVIDIA
Kerry Guerrero, Distinguished Machine Learning Engineer, Capital One
Jerrie Kumalah, Analytics Engineer, SeatGeek
Amanda Mercier, Principal Data Scientist Manager, Microsoft 
Hannah Pede, Assistant Director of Career and Professional Development, School of Data Science (moderator)

Sponsored by Microsoft

12:30-12:45 p.m.

Complimentary Bag Lunch | Lounge

12:45-1:15 p.m.

Mentor Roundtable Session I | Auditorium

Admissions Drop-In Session | Rooms CD

Resume Review | Room B

1:15-1:45 p.m.

Mentor Roundtable Session II | Auditorium

Admissions Drop-In Session | Rooms CD

Resume Review | Room B

1:45-2:00 p.m.

Break

2:00-3:00 p.m.

Student Feature Presentations | Auditorium

• Text-based Data Poisoning
  Izzy Shehan, Data Science Minor 2022
  Adversarial data poisoning can introduce negative social biases (e.g. against gender and race), weaken overall performance, and introduce insecurities and backdoors to machine learning models. NLP models, whose training data is often unaudited and scraped from open sources, are prime targets for this form of adversarial attack.
• Automating Diagnoses of Cerebral Palsy in NICU Settings Using Computer Vision 
  Navya Annapareddy, Ph.D. in Data Science Candidate, M.S. in Data Science 2022
  Infants that are born preterm or are in the NICU are at significantly higher risk for developmental movement disorders like Cerebral Palsy. While early intervention for these disorders is crucial, traditional diagnoses require around the clock manual supervision.  
• Data Science and the Law
  Meesun Yang, Ph.D. in Data Science Candidate, JD in Law
  What are some ways that data science is used in the legal industry?  We will explore how machine learning and AI are currently leveraged in litigation and government investigations.

3:00-4:00 p.m.

Closing Keynote: Mona Chalabi | Auditorium

4:00-5:00 p.m.

Closing Reception | Lounge

View Speaker Bios

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Keynote Speaker: Mona Chalabi

Chalabi is on a mission to, as she puts it, "take the numb out of numbers." In her illustrations, animations, and articles for The Guardian and publications like Fivethirtyeight and The New York Times, she explores data sets from the timely (affirmative action, voting trends, disability rights) to the offbeat (popular dog names in New York City) to the eye-opening (how many Americans eat pizza for breakfast). She's on a mission to make sure as many people as possible can find and question the data they need to make informed decisions about their lives. 

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