Hi I'm Han.
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Intro

Three things about Han. Click the icons for more details.

Science

My research interests lie in data science, machine learning and statistics, with the goal of understanding underlying patterns of complex data. For more information, please checkout my Google scholar profile.

Programming

I believe in open-source programs, efficient algorithms, and well-documented codes. Most importantly, I am on Github and Sourceforge, where you can find a lot of amazing people.

Discussion

If you are interested in machine learning and data science, come follow me on twitter. We have a huge community with open discussions about these topics.

Selected Publications

Scikit-ribo Enables Accurate Estimation and Robust Modeling of Translation Dynamics at Codon Resolution

Cell Systems

Indel variant analysis of short-read sequencing data with Scalpel

Nature Protocols

Accurate de novo and transmitted indel detection in exome-capture data using microassembly

Nature Methods

For more information, check out my CV

News

  • July 2017

    Data Scientist at Facebook

    Location: Menlo Park, CA

  • Among five awardees out of 449 graduates

  • November 2016

    Paper in Nature Protocols

    Title: Indel variant analysis of short-read sequencing data with Scalpel (View Paper).

  • August 2016

    Summer internship as Data Scientist at Facebook

    Location: Menlo Park, CA

  • Feburary 2016

    Talk presentation at AGBT Meeting

    Title: Scikit-ribo—Accurate A-site prediction and robust modeling of translation control (View Slides).

  • October 2015

    Talk presentation at Genome Informatics meeting

    Title: Scikit-ribo—Accurate A-site prediction and robust modeling of translation control (View Slides).

  • November 2014

    Talk presentation at CSHL Data Science Meeting

    Title: Reducing INDEL calling errors in whole genome and exome sequencing data (View Slides).

  • October 2014

    Paper in Genome Medicine

    Title: Reducing INDEL calling errors in whole genome and exome sequencing data (View Paper).

  • August 2014

    Paper in Nature Methods

    Title: Accurate de novo and transmitted indel detection in exome-capture data using microassembly(View Paper).

Han Fang

Han Fang is currently a Data Scientist at Facebook. He focuses on scaling Facebook's core infrastructure using machine learning and data science. Han holds a PhD in Applied Mathematics and Statistics from Stony Brook University (2017). In his PhD, he developed a set of graphical and machine learning algorithms for large-scale genomics data (cited > 210 times). He is a recipient of the President’s Award to Distinguished Doctoral Students, the Woo-Jong Kim Dissertation Award, and Excellence in Research Award.


Email: hanfang.cshl [at] gmail.com

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