Come learn about data science opportunities at Berkeley. Through a mix of presentations, panel discussions, and plenty of opportunities for networking, this event is being designed to help underrepresented undergraduates who are curious about data science, but might not yet know much about it, to learn more about what working in data science is like and opportunities that exist. By meeting data science practitioners and other students interested in data science, students may start to explore what path is right for them. Sessions will be tailored undergraduate students considering opportunities in data science.
REGISTER - Registration is FREE. Dinner is PROVIDED. Pre-registration is REQUIRED due to limited space.
-- 3:30-4:30 PM - Keynote: What is Data Science? Data Science for Your Community.
Speaker: Dani Ushizima, Lawrence Berkeley National Laboratory
Opportunities in data science to positively impact communities and social welfare.
-- 4:30-5:00 PM - Networking Break (refreshments provided)
-- 5:00-6:30 PM - Discussion Panel: Getting involved with data science
-- 6:30-8:00 PM - Dinner and Mixer.
Opportunities for questions and networking for students and invited guests. Topics for discussion will be introduced based on guests and participants attending.
Full details about upcoming events in this series will be posted as soon as they become available:
-- Data-intensive research / Tuesday, March 5, 2019 / 3:30-8:00 PM / 190 Doe Library
-- Beyond academic data science / Monday, April 8, 2019 / 3:30-8:00 PM / 190 Doe Library
Contact: For further information, visit https://bids.berkeley.edu/working-groups/diversity-and-inclusion-working-group.
The BIDS Diversity & Inclusion Working Group presents Fostering diverse and inclusive data science at Berkeley, a series of three workshop/dinner events featuring keynote talks, panel discussions, roundtable q&a sessions, and networking opportunities to encourage undergraduate students of diverse and underrepresented backgrounds to explore a potential future in data science and data-intensive research. Support for this workshop was provided by BIDS, the Berkeley Division of Data Science, the Student Technology Fund, the Chancellor’s Advisory Committee on Student Services and Fees, and the Berkeley Wellness Fund.
BIDS Faculty Affiliate Dani Ushizima is a Staff Scientist in the Machine Learning and Analytics Group in the Computational Research Division at Berkeley Lab, where she leads the Image Processing/Machine Vision team at CAMERA, and an Affiliate Faculty of the Bakar Computational Health Sciences Institute (BCHSI) at the University of California, San Francisco. She also leads the Center for Recognition and Inspection of Cells (CRIC), where her research focuses on imaging cancer cells for early-stage disease diagnosis. With 20 years of research and development experience in Computer Vision, Dani has focused primarily on quantitative microscopy and microstructure classification, from materials science to biomedical imaging.