Project Archive

 

 

ATLAS-PHO-Event-2015-058-6 - Nachman - Image source: CERN

Anomaly Detection using Deep Learning for Fundamental Physics Discovery

BIDS Research Affiliate Ben Nachman offered this project through the 2021 NERSC Summer Internships program.  Applicants were students actively enrolled in undergraduate or graduate programs (and the project was to be adapted to the experience of the student).... more

AstroPy

The AstroPy Project is a community effort to develop a single core package for astronomy in Python and foster interoperability between Python astronomy packages. The core package has nearly 100 contributors to date and has become one of the most widely used pieces of software in astronomy. The... more

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Berkeley Carpentries Club

BIDS' Education & Training Working Group has launched the Berkeley Carpentries Club to connect instructors of research computing workshops in the Berkeley, California, area. The group is a community network of teachers and instructors with diverse interests and backgrounds,... more

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Berkeley Ecoinformatics Engine

Predicting biodiversity responses to global environmental change is a huge challenge that requires a holistic understanding of the complex interactions and feedbacks among organisms, climate, and their physical and biotic environments across space and time. Holos: Berkeley Ecoinformatics Engine... more

BIDS Machine Shop

BIDS Senior Research Data Scientist Stéfan van der Walt previously hosted these undergraduate projects through BIDS Undergraduate Internships Program. As more scientific fields move to intersect with computation, a need arises for software tools that can bridge the gap... more

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BIDS-BCHSI Research Xchange Forum

The BIDS-BCHSI Research Xchange Forum was launched in October 2020 as an open discussion platform for the interdisciplinary exchange of ideas and research projects at the intersection of healthcare and data science, enabling participants to support the development, and research of the group's... more

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COVID-19 Response: ​BIDS Data Science Services and Consulting

In April 2020, BIDS is convened researchers and resources to address COVID-19. As the demand for data science and data analysis expertise took on new urgency with the COVID-19 pandemic, BIDS started working with multiple units at UC Berkeley to determine how best to... more

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Cryptography of the unknown regions of genomes

BIDS Biodiversity and Environmental Sciences Lead Ciera Martinez originally launched as part of UC Berkeley's Undergraduate Research Apprentice Program (URAP).  As sequencing genomes becomes faster and cheaper, more sophisticated informatics tools are needed to... more

Data Science Discovery Program

The Data Science Discovery Program (formerly known as the BIDS Collaborative) provides undergraduates with opportunities to engage in hands-on, team-based research opportunities by connecting them with cutting-edge data science research projects, community impact groups,... more

Deciding Force

The Deciding Force (DF) project is classifying information from more than 8,000 news articles describing more than 35,000 events in which police and the Occupy movement interacted. These data are considered alongside variables describing the governing contexts in which protests occur (including... more

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Detecting change in global biodiversity through large scale network analysis

Global ecosystems that support life are undergoing dramatic pressure and rapid, unprecedented changes. Currently, there are a variety of separate scientific models, each with separate data sources, that can model the activities of diverse parts in an ecosystem, such as soil, bacteria-root... more

This is a gamma-ray burst GRB160530a as measured with the COSI telescope  during its 2016 balloon flight.

Enabling future gamma-ray space missions

The next generation of gamma-ray space telescopes aims to open a new window into gamma-ray astronomy with unprecedented angular resolution, energy resolution, and sensitivity. The goals of these new telescopes range from achieving a better understanding of the element formation in our Galaxy, to... more

Environment and Society: Data Sciences for the 21st Century (DS421)

Environment and Society: Data Science for the 21st Century (DS421) was an interdisciplinary graduate training program and National Science Foundation Research Traineeship at UC Berkeley at the interface of data, social, and natural sciences. The project was led by BIDS Senior Fellow... more

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Garbage In, Garbage Out? Do Machine Learning Research Papers Report Where Training Data Comes From?

Supervised machine learning is widely used across fields, but major issues are arising around biased, inaccurate, and incomplete training data. In this project, we investigate to what extent published machine learning application papers give specific details about the training data they used,... more

Hydrologic forecasting for the East River, CO

River flow forecasting is essential for planning reservoir operations, defense strategies against flooding, and fluvial ecosystems management plans. However, flow forecasting is a highly uncertain science. One of the biggest uncertainties lies in resolving the timescales over which water is stored... more

Hydrological forecasting and the water/energy nexus

Clean, available water is a critical and often-overlooked resource for human activity, food production, biological diversity and all aspects of life on our planet. Drawing on data streams from a national network of research collaborators and water sensor networks, the research team is creating and... more

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Julia

BIDS Senior Fellow David Anthoff led this project, which was offered through the UC Berkeley's Undergraduate Research Apprentice Program (URAP) for the Spring 2020 and Fall 2019 academic semesters.  Participants in this project worked on the core data science software stack... more

starry sky

Learning fundamental properties of physical systems with machine learning

Using data-driven methods and statistical modeling to uncover, unguided by existing theory, the fundamental properties of observed physical systems, this team is using software and data to provide a new pathway to develop a theoretical understanding of the physical world. The data for this project... more

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NIMBLE: Numerical Inference for Hierarchical Models Using Bayesian and Likelihood Estimation

NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally intensive methods. NIMBLE is built in R but compiles your models and algorithms using C++ for speed.  It includes three components: A system for... more

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Online Hate Index

BIDS co-invests in this project with the D-Lab, UC Berkeley’s home for data science training in the humanities and social sciences, to support the development of natural language processing (NLP) and machine learning (ML) tools for the scalable detection of online hate speech.  Proactive... more

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