Zhang obtained his Ph.D. in Computer Science at
Rutgers, the State University of New Jersey.
He was working with Prof. Dimitris
Imaging and Modeling Center (CBIM).
research interests are deep learning, computer
vision, machine learning and medical image
This website is not maintained after graduation. Please come to this new personal website.
- [02/2019] This website will not be maintained, come to this personal website.
- [01/2019] Join Google Brain as a full-time Research Scientist.
- [09/2018] Successfully defended my Ph.D. thesis.
- [06/2018] Our StackGAN++ paper is accepted to T-PAMI.
- [03/2018] Our AttnGAN paper is accepted to CVPR18.
- [02/2018] Our
OT-GAN paper is accepted to ICLR18.
- [01/2018] I will join Google Brain as a research intern.
StackGAN paper is accepted as oral to ICCV2017.
2017, I have been invited to present
work on ICCV
Tutorials on GANs.
2017, I will join OpenAI as a research
intern on generative models.
Present, PhD in
Computer Science, Rutgers University, NJ, USA
in Communication and Information
Systems, BUPT, China
2009, B.S. in Information Science, China Agricultural
~ 05/2018, Research
Intern, Google Brain, CA, USA.
~ 08/2017, Research
Intern, OpenAI, CA, USA.
~ 08/2016, Core Data Science
Intern, Facebook, CA, USA.
08/2015, Software Engineering
Intern, Philips Research North America, NY, USA.
02/2012, Research Intern at Lab
of Media Search, NUS, Singapore.
09/2010, Software Engineering
Intern, Samsung, Beijing, China.
| Selected Publications
|(* indicates equal contributions)
[Preprint] Self-Attention Generative Adversarial Networks.
Han Zhang, Ian Goodfellow, Dimitris Metaxas, Augustus Odena.
arXiv:1805.08318, 2018 [PDF]
[ICLR'18] Improving GANs Using Optimal Transport
Tim Salimans*, Han Zhang*, Alec Radford, Dimitris Metaxas
ICLR, 2018. [PDF]
[CVPR'18]AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks.
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He
CVPR, 2018. [PDF]
[T-PAMI'18] StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks.
Han Zhang*, Tao Xu*, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas.
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2018. [PDF][Project]
[Neuroinformatics'18] SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation
Yuan Xue*, Tao Xu*, Han Zhang, Rodney Long, and Xiaolei Huang
Neuroinformatics, 2018. [PDF]
StackGAN: Text to Photo-realistic Image Synthesis with
Stacked Generative Adversarial Networks
Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaolei Huang,
Xiaogang Wang, and Dimitris Metaxas.
ICCV, 2017. Oral Presentation [arXiv][PDF]
[CVPR'17] Link the head to the "peak'': Zero Shot Learning
from Noisy Text descriptions at Part Precision
Elhoseiny*, Yizhe Zhu*, Han Zhang, Ahmed
CVPR 2017. [PDF]
SPDA-CNN: Unifying Semantic Part Detection and
Abstraction forFine-grained Recognition
Xu*, Mohamed Elhoseiny, Xiaolei Huang, Shaoting Zhang,
AhmedElgammal, and Dimitris Metaxas
CVPR 2016. [PDF]
Multimodal Deep Learning for Cervical Dysplasia
Tao Xu*, Han Zhang*, Xiaolei Huang, Shaoting Zhang, and
MICCAI 2016 (Early acceptance rate, 10%). [PDF]
Multi-feature based Benchmark for Cervical Dysplasia
Tao Xu, Han
Zhang, Cheng Xin, Edward Kim, L Rodney Long,
Zhiyun Xue, Sameer Antani, and Xiaolei Huang.
Pattern Recognition 2016. [PDF]
Robust shape prior modeling based on Gaussian-Bernoulli
Shaoting Zhang, Kang Li and Dimitris Metaxas.
International Symposium on Biomedical Imaging,
2014. [PDF ] Oral
| TA Work
CS580: Topics in Computers in Biomedicine
CS520: Introduction to
to Computer Science
to Imaging and Multimedia