Fei Xia

feixia at stanford.edu [Github] [Google Scholar]

About me

I am a second year PhD student at Department of Electrical Engineering, Stanford University. I am supervised by Silvio Savarese in CVGL/SVL. I also collborate with Leo Guibas, James Zou and David Tse on various projects. My research interests lie in Computer Vision (3D Vision in particular) and Applied Machine Learning.
News:
  • 2017.11 New NIPS and Bioinformatics papers' pdf versions are available.

Education

Aug. 2016 - Present, Department of Electrical Engineering, Stanford University,

PhD Student.

Aug. 2012 - Jul. 2016, Department of Automation Tsinghua University,

Bachelor of Engineering.

Aug. 2014 - Dec. 2014, Department of Electrical and Computer Engineering, Georgia Institute of Technology,

Exchange Student.

July. 2015 - Sept. 2015, Department of Electrical Engineering, Stanford University,

Visiting Researcher.

Publications and Manuscripts

  • Fei Xia*, Martin Zhang*, James Zou, David Tse. NeuralFDR: learning decision threshold from hypothesis features. To appear on NIPS 2017. [pdf] [code]

  • Qiao Liu, Fei Xia, Qijin Yin, Rui Jiang. Chromatin accessibility prediction via a hybrid deep convolutional neural network Bioinformatics. [pdf] [code]

  • Govinda M Kamath*, Ilan Shomorony*, Fei Xia*, Thomas A Courtade, David Tse. HINGE: long-read assembly achieves optimal repeat resolution. [pdf] [code] Genome Research Vol 27 2017.

  • Ilan Shomorony, Govinda M Kamath, Fei Xia, Thomas A Courtade, David Tse. Partial DNA assembly: a rate-distortion perspective. [pdf] ISIT 2016.

(*Equally contributed to the project and alphabetically listed)

Honors and Awards

  • 2016 Stanford Graduate Fellowship (Michael J. Flynn Fellow), Stanford University
  • 2015 Chang Jiong Scholarship (Highest honor in Dept. of Automation, 1/560)
  • 2014 Fang Chongzhi Scholarship (Highest honor in Dept. of Automation, 1/560)
  • 2014 China Scholarship Council Excellent Undergraduate Fellowship

Press Coverage