Martin Jinye Zhang

jinyezhang at hsph.harvard.edu [Github] [Google Scholar] [Twitter]

Hello! I am Martin, a postdoc at Harvard School of Public Health working with Prof. Alkes Price on statistical genetics. Currently, I am interested in analyzing the UK biobank whole exome sequencing (WES) data, and potential methods for combining GWAS with single-cell RNA-seq. Before that, I did my PhD at Stanford with Prof. David Tse and Prof. James Zou on statistics, machine learning, and computational biology. Some topics I worked on during my PhD include empirical Bayes, multiple hypothesis testing, multi-armed bandits, and single-cell RNA-seq.

I publish under Martin Jinye Zhang. I also go under Jinye Zhang (张金野).

Last updated: 04/14/2021

News:
  • 4/2021 Our paper on identifying aging signatures using the Tabula Muris Senis data was accepted by eLife.

Position & Education

2019 - Present, T.H. Chan School of Public Health, Harvard University,

Postdoctoral Researcher

2014 - 2019, Department of Electrical Engineering, Stanford University,

Doctor of Philosophy (PhD)

2014 - 2017, Department of Electrical Engineering, Stanford University,

Master of Science (MS)

2010 - 2014, Department of Electronic Engineering, Tsinghua University,

Bachelor of Engineering (B.Eng.)

Papers

(*Equal contribution)

Manuscripts under review


Published papers

  • Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures. [pdf] [code]
    Martin Jinye Zhang, Angela Oliveira Pisco, Spyros Darmanis, James Zou.
    eLife (2021).

  • Bandit-PAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits. [code]
    Mo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, Ilan Shomorony.
    NeurIPS (2020).

  • Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California.
    M Reza Sailani, Ahmed A Metwally, Wenyu Zhou, Sophia Miryam Schüssler-Fiorenza Rose, Sara Ahadi, Kevin Contrepois, Tejaswini Mishra, Martin Jinye Zhang, Łukasz Kidziński, Theodore J Chu, Michael P Snyder.
    Nature Communications (2020).

  • A single-cell transcriptomic atlas characterizes ageing tissues in the mouse. [code]
    The Tabula Muris Consortium.
    Nature (2020). Contributed to differential expression analysis (Fig. 2f-h) and cluster diversity score (Fig. 4c-f).

  • Polymicrobial periodontal disease triggers a wide radius of effect and unique virome.
    Li Gao, Misun Kang, Martin Jinye Zhang, M. Reza Sailani, Ryutaro Kuraji, April Martinez, Changchang Ye, Pachiyappan Kamarajan, Charles Le, Ling Zhan, Hélène Rangé, Sunita P. Ho, Yvonne L. Kapila.
    npj Biofilms and Microbiomes (2020).

  • Determining sequencing depth in a single-cell RNA-seq experiment. [code]
    Martin J. Zhang*, Vasilis Ntranos*, David Tse.
    Nature Communications (2020). Selected as 2020 Top 50 Life and Biological Sciences Articles
    (Preliminary version: "One read per cell per gene is optimal for single-cell RNA-seq". [pdf])

  • Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits. [code]
    Martin J. Zhang, James Zou, David Tse.
    ICML (2019).

  • Fast and covariate-adaptive method amplifies detection power in large-scale multiple hypothesis testing. [software] [code to reproduce paper]
    Martin J. Zhang, Fei Xia, James Zou.
    Nature Communications (2019). Preliminary version accepted as the Cell Systems best paper in RECOMB 2019 and received the RECOMB Best Paper Award
    (Preliminary version: "AdaFDR: a Fast, Powerful and Covariate-Adaptive Approach to Multiple Hypothesis Testing". [pdf])

  • Longitudinal multi-omics of host–microbe dynamics in prediabetes.
    Wenyu Zhou*, M. Reza Sailani*, Kévin Contrepois*, Yanjiao Zhou*, Sara Ahadi*, Shana Leopold, Martin J. Zhang, ..., George M. Weinstock, Michael Snyder.
    Nature (2019). Contributed 3 panels in 2 figures.

  • Exploring Patterns Unique to a Dataset with Contrastive Principal Component Analysis. [code]
    Abubakar Abid*, Martin J. Zhang*, Vivek K. Bagaria, James Zou.
    Nature Communications (2018).

  • Medoids in Almost Linear Time via Multi-armed Bandits. [code]
    Vivek Bagaria*, Govinda Kamath*, Vasilis Ntranos*, Martin J. Zhang*, David Tse.
    AISTATS (2018).

  • NeuralFDR: learning decision threshold from hypothesis features. [code]
    Fei Xia*, Martin J. Zhang*, James Zou, David Tse.
    NeurIPS (2017).

  • Block-wise MAP Inference for the Determinantal Point Processes with Application to Change Point Detection.
    Martin J. Zhang, Zhijian Ou.
    SSP (2016).

  • On the Theoretical Analysis of Cross Validation in Compressive Sensing.
    Jinye Zhang, Laming Chen, Petros T. Boufounos, and Yuantao Gu.
    ICASSP (2014).


Technical reports

  • Minimax Optimality of Sign Test for Paired Heterogeneous Data. [pdf]
    Martin J. Zhang, Meisam Razaviyayn, and David Tse.
    arxiv (2018).

Softwares

  • scdrs: single-cell disease-relevance score (demo).

  • adafdr: covariate-adaptive multiple testing.

  • sceb: sequencing-depth aware estimators for single-cell RNA-seq analysis via empirical Bayes.

  • Meddit: an almost linear algorithm for computing the medoid for a set of n points via adaptive sampling.

  • contrastive: a python library for performing unsupervised machine learning on datasets with learning (e.g. PCA) in contrastive settings, where one is interested in patterns (e.g. clusters or clines) that exist one dataset, but not the other.

Professional services

  • Reviewer for journals Nature Communications, BMC Biology, Bioinformatics, Biometrics, Scientific Reports, Journal of Genetics and Genomics and conferences IJCAI 2021(senior area chair), ICML 2021, ICLR 2021, NeurIPS 2020, ICML 2020, NeurIPS 2019, NeurIPS 2016.
  • Organizer of the Information Systems Laboratory Colloquium, 2015-2019, EE, Stanford.

Honors and Awards

  • 2020 Nature Communications 2020 Top 50 Life and Biological Sciences Articles for the paper "Determining sequencing depth in a single-cell RNA-seq experiment".
  • 2019 RECOMB 2019 best paper award
  • 2019 RECOMB 2019 travel award
  • 2017 NeurIPS 2017 travel award
  • 2015 Stanford Graduate Fellowship (SGF, Inventec Fellow)
  • 2015 Numerical Technologies Award in Electrical Engineering (Numerical Technologies Founders Graduate Fellowship)
  • 2015 Ranked 2/79 in the EE PhD Qualifying Exam at Stanford University
  • 2014 Outstanding Undergraduate Thesis "Speech Diarization Based on the Determinantal Point Processes" at Tsinghua University
  • 2013 Comprehensive Excellence Scholarship in Electronic Engineering at Tsinghua University

Teaching Experiences

  • TA, EE 278: Introduction to Statistical Signal Processing (Spring 2017)