Shuangfei Zhai's Homepage at Binghamton University

Shuangfei Zhai

Multimedia Research Lab
Department of Computer Science
Binghamton Univeristy, State University of New York
google scholar

Update: I have joined Apple as a deep learning research scientist, where our team has desgined and shipped FaceID. I now work on various deep learning problems in the computer vision domain.

I obtained my PhD in Multimedia Research Lab, Department of Computer Science, Binghamton Univeristy, SUNY, where I worked with Prof. Zhongfei (Mark) Zhang. Before coming to Binghamton University, I obtained my B.E. in Electronic Engineering and Information Science in University of Science and Technology of China, Hefei in 2010. I was a master student in Chinese Academy of Sciences during 2010-2012.

[Home] | [Research] | [Publications] | [Experiences] | [Professional Activities]

I am interested in the broad area of machine learning, with a focus on deep learning. In particular, I like thinking about learning representations for unsupervised, semi-supervised, weakly supervised and implicitly supervised problems. I am also interested in building efficient deep models.


  • Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogerio Feris. Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification, CVPR 2017 (accepted) [paper]

  • Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Zhongfei (Mark) Zhang, Rogerio Feris. S3Pool: Pooling with Stochastic Spatial Sampling, CVPR 2017 (accepted) [paper] [code]

  • Shuangfei Zhai, Yu Cheng, Rogerio Feris, Zhongfei (Mark) Zhang. Generative Adversarial Networks as Variational Training of Energy Based Models, preprint, [paper] [code]

  • Nana Li, Shuangfei Zhai, Zhongfei (Mark) Zhang, Boying Liu, Structural Correspondence Learning for Cross-lingual Sentiment Classification with One-to-many Mappings, AAAI 2017 (acceptance rate 25%)

  • Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei (Mark) Zhang. Doubly Convolutional Neural Networks, NIPS 2016 (acceptance rate 22.7%) [paper] [code]

  • Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, Zhongfei (Mark) Zhang, DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks, KDD 2016 (full paper, acceptance rate 8.9%) [paper]

  • Shuangfei Zhai*, Yu Cheng*, Weining Lu, Zhongfei (Mark) Zhang (* equal contribution). Deep Structured Energy Based Models for Anomaly Detection, ICML 2016 (acceptance rate 24.2%) [paper][a CNN-EBM implementation]

  • Peng Xia, Shuangfei Zhai, Benyuan Liu, Yizhou Sun, Cindy Chen, Design of Reciprocal Recommendation Systems For Online Dating, Journal of Social Network Analysis and Mining, 2016.

  • Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, Zhongfei (Mark) Zhang, Attention Based Recurrent Neural Networks for Online Advertising, WWW 2016 Poster [paper]

  • Shuangfei Zhai, Zhongfei (Mark) Zhang, Manifold Regularized Discriminative Neural Networks, preprint [paper]

  • Shuangfei Zhai, Zhongfei (Mark) Zhang, Semisupervised Autoencoder for Sentiment Analysis, AAAI 2016 (oral) [paper]

  • Shuangfei Zhai, Zhongfei (Mark) Zhang, Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs, SDM 2015 (oral, acceptance rate 14.7%) [paper] [talk]


  • Research Intern, IBM T.J. Watson Research Center, May 2016 - Feb 2017
  • Data Scientist Intern, Microsoft (Bing Ads), Summer 2015
  • Teaching Assistant/Research Assistant, Binghamton University, Fall 2012 - Spring 2016
  • Research Assistant, Chinese Acedamey of Sciences, 2010-2012
Professional Activities

  • Externel Reviewer, ICME2013, PAKDD2015/2016, KDD2015/2016, ECML/PKDD2015, CIKM2015, NIPS2016

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Last updated: 08/14/2016