Fireside Chat with Kelli Palmer
Kelli Palmer, Chief Diversity Officer, WillowTree
Siri Russell, Associate Dean of DEI, UVA School of Data Science
Careers in Data Science Panel
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)
Student Feature Presentations
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.
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
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.
