Senior Machine Learning Scientist

Grad Student, bioinformatics (2018-2022). Daniel studied Computer Science and Biochemistry at UC Berkeley, and was in a PhD program within the Integrative Program in Quantitative Biology. He is interested in developing machine learning methodologies in improving human health, particularly in the fields of neurodegeneration and pharmacology. Daniel was co-mentored in the Butte Lab.

Lab papers

  1. Trans-channel fluorescence learning improves high-content screening for Alzheimer's disease therapeutics.

    Wong DR, Conrad J, Johnson N, Ayers JI, Laeremans A, Lee JC, Lee J, Prusiner SB, Bandyopadhyay S, Butte AJ, Paras NA, Keiser MJ. Nat Mach Intell. 2022 May 30.

  2. Deep learning from multiple experts improves identification of amyloid neuropathologies.

    Wong DR, Tang Z, Mew NC, Das S, Athey J, McAleese KE, Kofler JK, Flanagan ME, Borys E, White CL 3rd, Butte AJ, Dugger BN, Keiser MJ. Acta Neuropathol Commun. 2022 Apr 28.