News

Kellie Ottoboni Receives Award for Post-Election Auditing Notebook

Kellie Ottoboni receives EVN Innovation Award

Leveraging parallel computation to analyze landscape evolution

This new article by BIDS Data Science Fellow Richard Barnes introduces new ways of running hydrological models quickly by leveraging specialized processors called GPUs (graphics processing units).  Computers have been getting faster for years, but the way in which the new high-performance computers are getting faster has fundamentally changed. For instance, GPUs can be difficult to program and some types of problems do not work well on them. 

Worldwide audience for BIDS' first Spanish-language training workshop, "Introducción a R y Git (Introduction to R and Git)"

‘Acknowledging past injustices’: UC Berkeley Division of Data Sciences holds event focused on increasing, celebrating diversity

Katherine Finman  |  The Daily Californian In order to increase diversity and inclusion within the data science field, the UC Berkeley Division of Data Sciences partnered with the Diversity and Inclusion Working Group of the Berkeley Institute for Data Science, or BIDS, to host an informational data research event in Doe Library on Tuesday.

Introducing TraefikProxy — a scalable and highly available proxy for JupyterHub

Georgiana Dolocan  |  Jupyter Blog In the JupyterHub context, the proxy is the unit in charge of directing the user requests to their notebook servers. The proxy manages a list of [user : notebook] mappings (the proxy routing table) in order to decide which request is sent where. The routing table must be continuously updated as users start and stop their servers without disrupting the requests being processed. The following drawing illustrates the proxy functionality in a JupyterHub deployment.

Advancing machine vision tools for the early identification of cancerous cells

In this new article by BIDS Senior Fellow Dani Ushizima and her colleagues at CRIC, the team introduces new computational tools for analyzing cell samples, and screening cervical cells to help researchers in the early detection of cancer of the womb. Using digitized images and incorporating deep learning techniques, the new tools improve on existing techniques for cellular analyses by detecting microscopic abnormalities accurately.

BIDS/UC Berkeley team takes on fintech challenge at the Chengdu 80 hackathon

BIDS Data Science Fellows Sören Künzel and Chris Kennedy recently participated in the Chengdu 80 FinTech Design and Development Competition at the SWUFE & CDAR 2018 Symposium: Reform Through Fintech in Chengdu, China.

Shining a spotlight on medical imaging applications at PMWC 2019

As a computer vision expert and long-term UCSF collaborator, I was invited to be a speaker on the Precision Imaging for Prediction panel, one of the opening acts at last week’s Precision Medicine World Conference (PMWC) 2019, which took place at the Santa Clara Convention Center in Silicon Valley on January 20-23.

"Love Data Week" is February 11-15, 2019