Han Fang
Ph.D. in Applied Math and Statistics
Data Scientist
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Intro

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

Science

My research interests lie in the intersection of machine learning, statistics, and genomics, with the goal of understanding underlying patterns of complex data. Checkout my Google scholar profile.

Programming

I believe in open-sourced 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 computer science, complex data, genomics and data science, come follow me on twitter. We have a huge community with open discussions about these topics.

Selected Publications

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

Reducing INDEL calling errors in whole-genome and exome sequencing data

Genome Medicine

For more information, check out my CV

News

  • March 2017

    Won the President’s Award to Distinguished Doctoral Students

    Location: Stony Brook, NY

  • 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 finished his PhD in Applied Math and Statistics at Stony Brook University , in residence at Cold Spring Harbor Laboratory . He received his B.S. in Optical Informatics at Sun Yat-sen University. His research interests intersect at machine learning, statistics, and genomics, with the goal of understanding underlying patterns of complex data.


Email: hanfang.cshl [at] gmail.com

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