Women in Data Science (WiDS) Berkeley Conference 2023 Recap
On March 7, 2023, the Women in Data Science (WiDS) Berkeley Conference was held in the Banatao Auditorium in Sutardja Dai Hall on campus. The Global Women in Data Science (WiDS) Conference is annually held at Stanford University, bringing together data professionals from across the world to discuss the latest data science research and applications. On the other hand, WiDS Berkeley is an independent event organized by the UC Berkeley School of Information alongside other UC Berkeley associates in correlation to the annual WiDS global conference, the WiDS Datathon, in addition to 200 WiDS regional events. Everyone is welcome to attend all WiDS affiliated conferences and events featuring incredible women in the data science field.
WiDS strives to support aspiring women in the field, as well as educate and encourage data scientists of all genders globally. Distinguished speakers in academia and industry, in addition to ongoing student projects from the Bay Area, were featured throughout the day. Topics such as breaking into industry, current data science skills & trends, and career progression in the field were some of the exciting topics.
As the first speaker, Ysis Wilson-Tarter started the speaker series with a commendable keynote in the morning. With a MS in applied biomedical engineering from Johns Hopkins as well as a BS in computer science from Stanford, Ysis is now a staff data engineer at Absci, leading data platform and pipeline development for biological data. She also aids in the development of other scientific tools for data analysis. Some of her published peer-reviewed articles cover areas of synthetic biological design and scalable neuroscience. At the moment, she is also currently the co-tech lead of the Black Girls Code Bay Area chapter.
Another outstanding speaker was Emily Barnes Franklin, a UC Berkeley PhD graduate with a focus on environmental engineering. Her talk primarily centered around how data science can improve chemical characterization of the organic compounds in our atmosphere. Introduced collaborations between data scientists and chemists can pose a chance to further our understanding towards atmospheric chemistry to effectively tackle air pollution and climate change.
Having earned a BS in Environmental Engineering from Yale and both her MS & PhD in Environmental Engineering from UC Berkeley, Emily has gone onto research human effects on aerosol creation and composition. She has investigated these impacts in both remote and urban locations utilizing machine-learning models to better characterize complex organic mixtures, Currently, she is a NSF-MPS Ascend Postdoctoral Fellow in Dr.Delphine Farmer’s group at Colorado State. She also continues to focus on minimizing aerosol exposure in schools, teaching math and environmental science at San Quentin Prison and preventing harassment during field studies.
Following the Keynote address by Ysis as well as a coffee break in the morning, tech talks from numerous speakers, including Emily, were presented. Deb Donig, an assistant professor of English at Cal Poly and lecturer at UC Berkeley’s School of Information, spoke about judgements and decisions related to counting towards overall numbers. Explorations were discussed further on how these numbers may further affect beliefs, assumptions, and biases of populations in the long run. Deb also holds experiences as the co-founder of the Cal Poly Ethical Technology Initiative, the host of “Technically Human” podcast, a consultant in the tech and film industries, and as a previous policy expert for the Biden/Harris Education Policy Strategy Team. Afterwards, other incredible speakers for the WiDS included Stacia Wyman, Tanya Roosta, and Jennifer King.
Stacia Wyman is a Computational Genomics Investigator at UC Berkeley's Innovative Genomics Institute. Much of her postdoctoral work covers algorithm development for miRNAs identification as cancer biomarkers and entire genome sequence analysis of tumors at the Fred Hutchinson Cancer Research Center. On the other hand, Tanya Roosta is currently a senior research scientist and manager at Amazon’s Alexa AI team. As a UC Berkeley alumnae from the engineering and computer science department, she also teaches the Statistics for Data Science course at the UC Berkeley School of Information. Lastly, Dr. Jennifer King is a privacy and data policy fellow at the Stanford University Institute for Human-Centered Artifical Intelligence. As a past UC Berkeley School of Information PhD graduate in information management and systems, her research primarily investigates the general public’s understanding of online privacy as well as the policy indiactions growing technologies hold. Dr.King’s tech talk focused on AI products such as GPT-3 and DALL-E, examining the data sources’ credibility and entire data lifecycle these platforms utilize.
Once these incredible tech talks concluded, lunch commenced, along with a poster session showcasing completed and in-progress data science projects led by UC Berkeley students. Afterwards, a panel discussion with briliant panelists 1. Joyce Shen (a venture capital/private equity investor), 2. Kira Wetzel (Lead at Meta’s Analytics Engineering Team), 3. Manjula Mishra (Senior Data Scientist at Radian Inc.), and 4. Sarah Luger (Principal in Orange Silicon Valley’s Tech Group) was moderated by Jennifer Chayes (Associate of Computing, Data Science, and Society + UC Berkeley Professor + Dran of the School of Information).
The latter half of the Women in Data Science Conference at UC Berkeley was concluded with poster awards for UC Berkeley data science students and a networking event for all attendees.
This event was co-sponsored by the CITRIS and the Banatao Institute; Computing, Data Science, and Society; Berkeley Research, Teaching and Learning (RTL); and the UC Berkeley School of Information. Organizing committee members from RTL included Liza Schlosser-Olroyd, Rani Hanstad, and Wan Nurul Naszeerah, who is a domain consultant for Research IT and opened the conference.
“Online conferences can not replace nor replicate these experiences. Community is an avenue for those to meet and hopefully create long-lasting experiences and long-term relationships to lean on for professional growth.” - Wan Nurul Naszeerah