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Michael Mahoney Tapped to Lead the Machine Learning and Analytics Group
Berkeley Lab’s Scientific Data Division recently appointed Michael Mahoney to lead its Machine Learning and Analytics Group.
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Berkeley Lab Computing Resources Enable Deeper Understanding of Supernovae Explosions
An international research team recently made history by recording the earliest post-explosion detection of a Type Ia supernova, using cosmological models developed at Berkeley Lab and supercomputing resources at NERSC. Read More »
HYPPO: Leveraging Prediction Uncertainty to Optimize Deep Learning Models for Science
With a growing need for optimization tools that can enhance deep learning models and their training to improve predictive capabilities and accelerate time-consuming computer simulations, a Berkeley Lab team developed HYPPO, an open-source software tool for hyperparameter optimization of deep neural networks. Read More »
Open Sourced Control Hardware for Quantum Computers
To make engineering quantum hardware more accessible, the Advance Quantum Testbed has open-sourced a new electronics control and measurement system for superconducting quantum processors. Read More »
Cutting Through the Noise
Berkeley Lab’s AMCR and Physics divisions joined forces to create a new approach to quantum error mitigation - "noise estimation circuits" - that could help make quantum computing’s theoretical potential a reality. Read More »
AMCRD’s Sherry Li Part of Team Honored by SIAM for Best Paper
AMCRD's Sherry Li is co-author on a paper being honored with the 2022 SIAM Activity Group on Supercomputing Best Paper Prize. Read More »
SIMCoV Models Cell-by-Cell Spread of Respiratory Infections
Berkeley Lab computational research scientist Steve Hofmeyr is part of a team that developed SimCoV, which can provide a 3D simulation of a portion of the lung and model the ways in which COVID-19 and other viral infections spread in the lungs. Read More »
Berkeley Lab’s FasTensor Provides Pain-Free Big Data Analysis
With FasTensor, researchers in Berkeley Lab’s Scientific Data Management Group developed an open source tool to help its users efficiently process and analyze their massive datasets. Read More »
Crucial Leap in Error Mitigation for Quantum Computers
Researchers at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed (AQT) demonstrated that an experimental method known as randomized compiling (RC) can dramatically reduce error rates in quantum algorithms and lead to more accurate and stable quantum computations. Read More »
David Brown to Step Down as AMCR Division Director in Early 2022
David Brown, who has served as the research division director in Berkeley Lab’s Computing Sciences Area (CSA) for more than a decade, will step down in early 2022. Read More »
How a Novel Radio Frequency Control System Enhances Quantum Computers
A team of physicists and engineers at Lawrence Berkeley National Laboratory (Berkeley Lab) successfully demonstrated the feasibility of low-cost and high-performance radio frequency modules for qubit controls at room temperature. Read More »
Berkeley Lab Researchers Honored with Best Paper Award at QCE21
Two researchers from the Applied Mathematics & Computational Research Division are co-authors on a paper selected as Best Paper in the Quantum Computing and Systems Track at the 2021 IEEE International Conference on Quantum Computing and Engineering. Read More »
Student Research Opens New Doors in Quantum Image Processing
When Mercy Amankwah joined the Computing Sciences Area’s Summer Program in June 2021, she’d never worked in quantum computing before and found the subject intriguing, but intimidating. By the end of the summer, she had helped advance the field. Read More »
Summer Students Use AMReX to Study Cancer Cell Migration
As part of Berkeley Lab's 2021 Computing Sciences Summer Program, a team of undergrads led by senior scientist Ann Almgren got a little closer to understanding how groups of cancer cells may respond to different kinds of forces. Read More »
Deep Learning Tactics Speed Quantum Simulations
Berkeley Lab and UC Berkeley researchers are using an AI technique called reinforcement learning to optimize quantum simulations and speed the time it takes to create and test different quantum architecture designs. Read More »
New Alvarez Fellow Eyes New Applications for Math and ML
Osman Malik, the newest Berkeley Lab Alvarez Fellow, joined the the Applied Math and Computational Research Division's Scalable Solvers Group on September 1. Read More »
Berkeley Lab Hosts Record 11 CSGF Fellows in 2021
In 2021, Berkeley Lab will welcome a record 11 Department of Energy Computational Science Graduate Fellows (CSGF). Drawing from diverse scientific and engineering disciplines, the fellows share a common interest in using computing in their research. Read More »
Didem Unat Named SIGHPC Emerging Woman Leader in Technical Computing
Didem Unat, Berkeley Lab’s 2012 Luis Alvarez Fellow in Computing Sciences, is the 2021 ACM SIGHPC Emerging Woman Leader in Technical Computing award winner. Read More »
How I Spent My Summer: Making Jupyter Tools – and Groundbreaking Science – Even Better
Each summer, Berkeley Lab hosts dozens of college students through the Computing Sciences Summer Program, and this year Josh Geden had the opportunity to work with NERSC and CRD on a variety of projects related to Jupyter. Read More »
CAMERA Mathematicians Build an Algorithm to ‘Do the Twist’
CAMERA mathematicians have developed an algorithm to decipher the rotational dynamics of twisting particles in large complex systems from the X-ray scattering patterns observed in X-ray photon correlation spectroscopy experiments. Read More »
Talita Perciano Recognized as Outstanding Mentor
Talita Perciano, a research scientist in CRD’s Machine Learning and Analytics Group, is being recognized for providing exceptional mentorship to students participating in various internships provided by Berkeley Lab. Read More »
Berkeley Lab CS Reorganization Brings Data Science to the Forefront
To position Berkeley Lab among the premier institutions for data science research, the Computational Research Division (CRD) will be reorganized to form two new divisions, effective October 1, 2021. Read More »
Latest IPCC Report Points to Urgent Need to Cut Emissions
Four Berkeley Lab scientists, Charles Koven, Michael Wehner, William Collins, and Chaincy Kuo, were key contributors to the Intergovernmental Panel on Climate Change (IPCC) 6th assessment report, Working Group I. Released today, the report points to an urgent need to cut greenhouse gas emissions. Read More »
CRIC Database Brings Machine Learning to Women's Health
CRD’s Dani Ushizima is part of a team developing a searchable image database that uses machine learning to enhance the accuracy of Pap smear tests. Read More »
CAMERA Leads International Effort on Autonomous Scientific Discoveries
To make full use of modern instruments and facilities, researchers need new ways to decrease the amount of data required for scientific discovery and address data acquisition rates humans can no longer keep pace with. Read More »
