
WiDS Livermore is independently organized by Lawrence Livermore National Laboratory to be part of the mission to increase participation of women in data science and to feature outstanding women doing outstanding work.
The global WiDS Conference aims to inspire and educate data scientists worldwide 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. Whether you're at LLNL, a university, a commercial company, or any other affiliation: Everyone is welcome.
Everyone—inside or outside the Lab, any career level, any data science experience level—is invited to attend our upcoming WiDS Livermore event and its related datathon. Both events are hybrid, though they will be held on different days just outside the main LLNL campus. Participants are asked to avoid sensitive information in all communications and interactions during these events.
LLNL Datathon
Wednesday, February 19 | 8:30am – 5:00pm PDT (GMT -7)
The global WiDS conference hosts a competitive datathon in which participants can learn more about data science and hone their skills. This one-day event at LLNL provides an opportunity to collaborate, innovate, and investigate a challenging data science problem.
The datathon is designed for data science enthusiasts who are discovering or building their data skills (beginner and intermediate levels). An LLNL data scientist will guide participants through the dataset and notebook.
Visiting LLNL | Directions to UCLCC | Agenda | Data Set | Jupyter Notebook
WiDS Livermore
Wednesday, March 12 | 8:30am – 5:00pm PDT (GMT -7)
This one-day hybrid conference provides an opportunity to hear about the latest data science related research and connect with others in the field. The event will include keynote speakers, technical talks, career-focused panel discussions, and a poster session.
We will be recording the speakers, photographing the event, and taking screen shots. Participants are asked to avoid sensitive information in all communications and interactions during this event.
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Past Events

WiDS Livermore took place on Wednesday, March 13 as a hybrid event. Attendees met online and in-person for the forum, highlighting women in computing and the data sciences, to network, engage in a speed mentoring session, and participate in a session. LLNL Center for Applied Scientific Computing (CASC) researcher Sarah Osborn presenting on her contributions to different research projects, including a scalable approach for forwarding propagation of uncertainties for large-scale subsurface flow problems. Keynote speaker and LLNL Distinguished Member of Technical Staff Carol Woodward spoke about her unconventional career path. Read a recap from LLNL News: WiDS Livermore conference attendees network, share research and absorb wisdom. The datathon took place on a separate day, with data science enthusiasts gathering on February 28. Additional resources:
- Conference agenda
- Mentoring questions/prompts
- Datathon agenda
- Datasets (.zip)
- Dataset description
- Jupyter Notebook (.zip)
Videos (view the full WiDS Livermore playlist):
- Welcome Address
- Keynote Address
- Panel Discussion: Leadership Roles
- Panel Discussion: Early Career Paths
- Panel Discussion: Being an early career woman in a technical field
- Technical Talk 1
- Technical Talk 2
- Dataset Introduction
- Integrating Cyber Security and Machine Learning for App in Transportation Sys.

WiDS Livermore took place on Wednesday, March 8 as a hybrid event. Attendees met online and in-person for the forum, highlighting women in computing and the data sciences, to network, listen to technical talks by Lab scientists and others, engage in a fireside chat with former LLNL Computation Associate Director Dona Crawford, and watch as LLNL Bioinformatics Group Leader Marisa Torres spoke about her work applying machine-learning tools to drug discovery live from the WiDS worldwide conference at Stanford University. Read a recap from LLNL News: First-ever hybrid Women in Data Science Livermore event celebrates achievements, supports women in the field. Additional resources:
- Agenda (PDF 504KB)
- Slide deck (PDF 2.6MB)
- Mentoring questions (PDF 193KB)
- Datathon information and results on Kaggle
- Datathon Jupyter Notebook tutorial (PDF 377KB)
Videos (view the full WiDS Livermore playlist):

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.
Read a recap of our 2022 event and download the agenda (PDF).
Recordings of WiDS Livermore sessions are posted to the Livermore Lab Events YouTube channel:
- Welcome Address (28:02)
- Fireside Chat (1:02:20)
- Beginner Workshop Track (1:12:12)
- Applied Workshop Track (50:26)

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.”
Recaps of the whole day and the technical talks are available on this website. Speakers' slides are downloadable as PDFs:
- 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.