Hao (Henry) Zhou

Hao Zhou 

1 Hacker Way
Menlo Park, CA 94025

E-mail: haozhoustat [AT] gmail [DOT] com

About Me

I am now a Research Scientist at Facebook. I received my Ph.D. degree in March 2019 from the University of Wisconsin - Madison. I worked with Prof. Grace Wahba and Prof. Vikas Singh on machine learning and statistics. The topics include deep neural networks (DNN), kernel machines, multi-source datasets modeling (DA/TL/MTL), large scale spatio-temporal modeling, graphical causal models, etc.


  1. Hao Henry Zhou, YunYang Xiong, Vikas Singh. "Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty", arXiv, 2018.

  2. Hao Henry Zhou, Vikas Singh, Sterling C. Johnson, Grace Wahba. "Statistical Tests and Identifiability Conditions for Pooling and Analyzing Multisite Datasets", Published in Proceedings of the National Academy of Sciences (PNAS), 2018. [pdf][supp][Github code][summary slides on multisite datasets analysis, domain adaptation and multi-task learning]

  3. Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh. "When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications", Published in Proceedings of International Conference on Machine Learning(ICML), 2017.[pdf][supp][Github code][slides]

  4. Hao Henry Zhou, Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh. "Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease", Published in Proceedings of Neural Information Processing Systems(NIPS), 2016.[pdf][supp][Github code][slides]

  5. Hao Henry Zhou, Garvesh Raskutti. "Non-parametric Sparse Additive Auto-regressive Network Models", Accepted by IEEE Transactions on Information Theory. [pdf]


Python, R, Matlab, C++, Java, Caffe2, Pytorch, SQL, Latex

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Collaborators (alphabetical order)

Garvesh Raskutti (UW-Madison), Sterling C. Johnson (UW-Madison)