WiDS Livermore is an independent event organized by LLNL ambassadors to coincide with the annual global Women in Data Science (WiDS) Conference held at Stanford University and an estimated 200+ locations worldwide. All genders are invited to attend WiDS regional events, which features outstanding women doing outstanding work.
The global WiDS Conference aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. This one-day technical conference provides an opportunity to hear about the latest data science related research and applications in a number of domains, and connect with others in the field. The program features thought leaders covering a wide range of domains from data ethics and privacy, healthcare, data visualization, and more. Learn more via the WiDS podcast and WiDS worldwide news.
Save the date: WiDS Livermore returns on Wednesday, March 8, 2023. This will be a hybrid event.
Our 5th regional event took place on Monday, March 7. The program for this one-day virtual conference included a livestream of the Stanford conference as well as workshops, mentoring sessions, and networking opportunities. This year’s Livermore event also featured a fireside chat between Kim Budil, LLNL’s first woman director, and Jessie Gaylord, leader of LLNL’s Global Security Computing Applications Division.
Recordings of WiDS Livermore sessions are posted to the Livermore Lab Events YouTube channel:
Coinciding with International Women’s Day on March 8, LLNL's fourth WiDS regional event brought women together to discuss successes, opportunities and challenges of being female in a mostly male field. The Lab’s first-ever virtual WiDS gathering attracted dozens of LLNL data scientists as well as some from outside the Lab, and featured speakers, a career panel and breakout sessions where women could network and discuss mentoring and career advancement. WiDS Ambassador Marisa Torres told attendees, “We’re here to celebrate a lot of accomplishments.”
Read more about the 2021 virtual event via LLNL News. A WebEx recording of the career panel session will be available soon. Speakers' slides are downloadable as PDFs:
- Ana Kupresanin, deputy director of the Center for Applied Scientific Computing: A Statistician’s Journey to LLNL
- Nisha Mulakken, co-director of the Data Science Summer Institute: Data Science in Action: Research, Internships, and Mentoring
LLNL hosted its third regional event on March 2. The day’s agenda featured local speakers, a career panel, mentoring sessions, and a networking reception interspersed with highlights from the Stanford livestream. Co-organizer Masha Aseeva stated, “Often, a woman with a technology career is the only woman in a room full of men, which can feel isolating. This event opens up the LLNL community to a broad network of women in data science so that we can support each other.”
- Welcome & agenda
- Marisol Gamboa: Data Science on a Mission
- Alyson Fox: Collaborative Autonomy Work in Unreliable Computing Environments
- Kathleen Schmidt: Sensitivity Analysis: Quantifying What Matters
- Kelli Humbird: Machine Learning-Guided Discovery and Design for Inertial Confinement Fusion
- Giuliana Pallotta: Multi-Frequency Analysis of Modeled-Versus-Observed Variability in Tropospheric Temperature
2019 marked the second consecutive WiDS Livermore event. "The goal is to increase interactions and make connections," said WiDS Livermore Ambassador Marisa Torres. "We want to get ideas of how we can foster this kind of community building throughout the year beyond this one event…I really want people to be able to talk about each other’s research and get ideas on how to collaborate and expand their network of who’s doing data science." Read more about the 2019 conference via LLNL News.
At the 2018 WiDS Livermore event, nearly 70 attendees, mostly women Livermore and Sandia national laboratory employees, heard featured talks by female LLNL scientists on machine learning and data analytics, and viewed a live broadcast of the daylong world conference from Stanford. Data scientist Ana Paula Sales began the day by presenting a talk on applying machine learning to the Cancer Moonshot and& Cancer Registry of Norway patient medical records, followed by machine learning group leader Brenda Ng, who discussed applying deep feature learning techniques in video analytics. Read more about the 2018 event via LLNL News.
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