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. Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels.

    Wong DR, Magaki SD, Vinters HV, Yong WH, Monuki ES, Williams CK, Martini AC, DeCarli C, Khacherian C, Graff JP, Dugger BN, Keiser MJ. Commun Biol. 2023 Jun 24.

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

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

  3. 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.