News

BIDS congratulates our 2018-2019 "graduating" Data Science Fellows

Unlocking the secrets of stem cell renewal

Molecular Biologist Diya Das deciphers cellular signaling and activation patterns to understand how stem cells regenerate healthy tissue after injury.

BIDS undergraduate interns celebrate 2018-2019 milestones

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.