Han Zhang

Research Scientist at Google Brain

Email: zhanghan at google.com


I am currently a Research Scientist at Google Brain. I obtained my Ph.D. in Computer Science at Rutgers University in 2018, supervised by Dimitris Metaxas. In 2012, I received my Master's in Communication and Information Systems at Beijing University of Posts and Telecommunications. I did my B.S. at China Agricultural University, where I majored in Information Science.

My research interests are computer vision, deep learning, and medical image analysis. My current research is focused on generative modeling and vision-language interaction.

Work Experience

  • 01/2019~ Present, Research Scientist, Google Brain, CA, USA.
  • 01/2018 ~ 05/2018, Research Intern, Google Brain, CA, USA.
  • 05/2017 ~ 08/2017, Research Intern, OpenAI, CA, USA.
  • 05/2016 ~ 08/2016, Core Data Science Intern, Facebook, CA, USA.
  • 05/2015 ~ 08/2015, Software Engineering Intern, Philips Research North America, NY, USA.
  • 09/2011 ~ 02/2012, Research Intern at Lab of Media Search, NUS, Singapore.
  • 08/2010 ~ 09/2010, Software Engineering Intern, Samsung, Beijing, China.

Selected Publications

(* indicates equal contributions)

[CVPR'19] Co-occurrent Features in Semantic Segmentation

Hang Zhang, Han Zhang, Chenguang Wang, Junyuan Xie. CVPR, 2019.

[ICML'19] Self-Attention Generative Adversarial Networks. [pdf][code]

Han Zhang, Ian Goodfellow, Dimitris Metaxas, Augustus Odena. ICML, 2018

[ICLR'18] Improving GANs Using Optimal Transport. [pdf][code]

Tim Salimans*, Han Zhang*, Alec Radford, Dimitris Metaxas. ICLR, 2018.

[CVPR'18] AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks. [pdf][code]

Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He. CVPR, 2018.

[TPAMI'18] StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks. [pdf] [code]

Han Zhang*, Tao Xu*, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas. To appear in TPAMI, 2018.

[Neuroinformatics'18] SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation. [pdf][code]

Yuan Xue*, Tao Xu*, Han Zhang, L. Rodney Long and Xiaolei Huang. Neuroinformatics, 2018.

[ICCV'17] StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks. [arxiv] [iccv] [code]

Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas. ICCV, 2017. (Oral presentation 45/2143=~2.10%)

[CVPR'17] Link the head to the "peak'': Zero Shot Learning from Noisy Text descriptions at Part Precision. [pdf][code]

Mohamed Elhoseiny*, Yizhe Zhu*, Han Zhang, Ahmed Elgammal. CVPR 2017.

[CVPR'16] SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-grained Recognition. [pdf]

Han Zhang*, Tao Xu*, Mohamed Elhoseiny, Xiaolei Huang, Shaoting Zhang, Ahmed Elgammal, and Dimitris Metaxas. CVPR, 2016.

[MICCAI'16] Multimodal Deep Learning for Cervical Dysplasia Diagnosis. [pdf]

Tao Xu*, Han Zhang*, Xiaolei Huang, Shaoting Zhang, and Dimitris Metaxas. MICCAI, 2016 (Early acceptance rate, ~10%).

[PR'16] Multi-feature based Benchmark for Cervical Dysplasia Classification Evaluation. [pdf]

Tao Xu, Han Zhang, Cheng Xin, Edward Kim, L Rodney Long, Zhiyun Xue, Sameer Antani, and Xiaolei Huang. Pattern Recognition, 2016.

[ISBI'14] Robust shape prior modeling based on Gaussian-Bernoulli RestrictedBoltzmann Machine.[pdf]

Han Zhang, Shaoting Zhang, Kang Li and Dimitris Metaxas. IEEE International Symposium on Biomedical Imaging, 2014. Oral presentation