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Fang Han

Fang Han

· Professor

University of Washington · Economics

Active 2011–2025

h-index23
Citations5.4k
Papers12443 last 5y
Funding$650k1 active

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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Research topics

  • Computer Science
  • Artificial Intelligence
  • Biology
  • Applied mathematics
  • Neuroscience
  • Psychology
  • Statistics
  • Mathematics
  • Developmental psychology
  • Combinatorics

Selected publications

  • Shell microelectrode arrays (MEAs) for brain organoids

    Science Advances · 2022 · 179 citations

    Brain organoids are important models for mimicking some three-dimensional (3D) cytoarchitectural and functional aspects of the brain. Multielectrode arrays (MEAs) that enable recording and stimulation of activity from electrogenic cells offer notable potential for interrogating brain organoids. However, conventional MEAs, initially designed for monolayer cultures, offer limited recording contact area restricted to the bottom of the 3D organoids. Inspired by the shape of electroencephalography ca…

  • Distribution-Free Consistent Independence Tests via Center-Outward Ranks and Signs

    Journal of the American Statistical Association · 2020 · 69 citations

    Senior authorCorresponding

    This article investigates the problem of testing independence of two random vectors of general dimensions. For this, we give for the first time a distribution-free consistent test. Our approach combines distance covariance with the center-outward ranks and signs developed by Marc Hallin and collaborators. In technical terms, the proposed test is consistent and distribution-free in the family of multivariate distributions with nonvanishing (Lebesgue) probability densities. Exploiting the (degener…

  • IDEAS: individual level differential expression analysis for single-cell RNA-seq data

    Genome biology · 2022 · 54 citations

    We consider an increasingly popular study design where single-cell RNA-seq data are collected from multiple individuals and the question of interest is to find genes that are differentially expressed between two groups of individuals. Towards this end, we propose a statistical method named IDEAS (individual level differential expression analysis for scRNA-seq). For each gene, IDEAS summarizes its expression in each individual by a distribution and then assesses whether these individual-specific…

  • First Organoid Intelligence (OI) workshop to form an OI community

    Frontiers in Artificial Intelligence · 2023 · 52 citations

    The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the develop…

  • On universally consistent and fully distribution-free rank tests of vector independence

    The Annals of Statistics · 2022-08-01 · 35 citations

    articleOpen accessSenior author

    Rank correlations have found many innovative applications in the last decade. In particular, suitable rank correlations have been used for consistent tests of independence between pairs of random variables. Using ranks is especially appealing for continuous data as tests become distribution-free. However, the traditional concept of ranks relies on ordering data and is, thus, tied to univariate observations. As a result, it has long remained unclear how one may construct distribution-free yet con…

Recent grants

Frequent coauthors

  • Han Liu

    53 shared
  • Wei Sun

    49 shared
  • John Lafferty

    Yale University

    40 shared
  • Ming Yuan

    Peking University Shenzhen Hospital

    40 shared
  • Larry Wasserman

    Carnegie Mellon University

    39 shared
  • Zhen Miao

    Microsoft (United States)

    15 shared
  • Mathias Drton

    15 shared
  • Hongjian Shi

    Technical University of Munich

    14 shared

Education

  • Ph.D., Economics

    University of Washington

    2008
  • M.A., Economics

    University of California, Los Angeles

    2003
  • B.A., Economics

    University of California, Los Angeles

    2001

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