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Ben Brown is a statistical scientist in the Environmental Genomics and Systems Biology division within Berkeley Labâs Biosciences Area. He specializes in the development of novel machine algorithms, usually for the biological and environmental sciences at Berkeley Lab. His group develops âthird-waveâ learning algorithms that combine the interpretability and reliability of classical statistics with the predictive performance of deep learning. They specialize in designing learning paradigms for complex, high-dimensional systems that enable accurate uncertainty quantification, model discovery, feature selection, and inference. Dr. Brown's expertise include statistics, machine learning, deep learning, and artificial intelligence.
COVID-19-related research: "Using Machine Learning to Estimate COVID-19's Seasonal Cycle". Other principal investigators include: Eoin Brodie, Nicola Falco, Dan Feldman, Zhao Hao, Chaincy Kuo, Joshua Ladau, and Haruko Wainwright.
Heather Gray is an experimental particle physicist working on the ATLAS experiment at the Large Hadron Collider (LHC) just outside Geneva in Switzerland. She has broad interests in particle physics, but the primary focus of her research is the Higgs boson -- the most recently discovered elementary particle, the only known elementary scalar of nature and the final piece of the remarkably successful Standard Model. She studies the properties of the Higgs boson and, in particular, how it interacts with different types of quarks, including top, bottom and charm quarks. Other research interests include the development of track reconstruction algorithms, silicon detectors and algorithms for quantum computers. A theme throughout her research is applications of machine learning.
Areas of expertise: physics/astrophysics, quantum computing, AI/machine learning, accelerators, dark energy/dark matter, particle physics, Higgs boson