I am currently a research scientist at Facebook Applied Machine Learning. I obtained my PhD at Rutgers University on Sep 2017, advised by Prof. Dimitris Metaxas. Before that, I obtained my M.S. Degree from Shanghai Jiao Tong University in 2012 and B.S. Degree from Hebei University of Technology in 2009.
[Google Scholar] [Linkedin]

Work Experience

  • software engineer intern at Facebook, CoreML team, Menlo Park, California, 2016/05 - 2016/08
    Mentored by Liang Xiong
  • research intern at Facebook AI Research, Menlo Park, California, 2015/02 - 2016/03
    Mentored by Piotr Dollar and Yuandong Tian

Research Interest

I am widely interested in deep learning and computer vision. Me and my mentor Yuandong Tian developed Darkforest Go bots at FAIR. Our bots are currently available for play on KGS. Our bot was covered by media including Wired and MIT Tech Review


  • Yan Zhu, Shaoting Zhang, Dimitris N. Metaxas
    Interactive Reinforcement Learning for Object Grounding via Self-Talking [PDF]
    NIPS 2017 VIGIL workshop

  • Yan Zhu, Yuandong Tian, Dimitris N. Metaxas, Piotr Dollar
    Semantic Amodal Segmentation [PDF] [dataset and code]
    CVPR 2017

  • Yuandong Tian, Yan Zhu
    Better Computer Go Player with Neural Network and Long-Term Prediction [PDF] [Wired] [MIT Tech Review]
    ICLR 2016

  • Jingjing Liu, Chao Chen, Yan Zhu, Wei Liu, Dimitris N. Metaxas,
    Video Classification via Weakly Supervised Sequence Modeling [PDF]
    CVIU, October 2015

  • Yan Zhu, Shaoting Zhang, Wei Liu, Dimitri Metaxas,
    Scalable Histopathological Image Analysis via Active Learning [PDF] [Supplemental]
    MICCAI 2014
    Early acceptance rate, ~10%. Student Travel Award

  • Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas and Christoph H. Lampert,
    Scalable Computing the M Most Probable Modes of a Graphical Model [PDF] [Supplemental]
    AISTATS 2013.
    Oral, acceptance rate ~11%

  • Yan Zhu, Xu Zhao, Yun Fu and Yuncai Liu,
    Sparse Coding on Local Spatial-Temporal Volumes for Human Action Recognition [PDF]
    ACCV 2010

TA work

  • CS 536, Machine Learning, Rutgers University
  • CS 112, Data Structures, Rutgers University
  • CS 336, Principles of Information and Data Management, Rutgers University
  • VE 112, Data Structures and Algorithms, SJTU-Umich Joint Institute