About Me

I am a tenure-track assistant professor at Department of Computer Science, Stevens Institute of Technology. I may take one or two PhD students. Drop me a line if you would like to apply.

From 2016 to 2018, I was postdoc scholar at Department of Statistics, UC Berkeley. I worked with Michael Mahoney. In 2011 and 2016, I got both of my doctoral and bachelor's degree from Zhejiang University, China. My advisor was Zhihua Zhang. During my doctoral study, I have been supported by "the Microsoft Research Asia Fellowship" and "Baidu Scholarship", which were the highest fellowships/scholarships in China.

Research Interest

Machine learning

Computational methods such as numerical optimization, matrix computation, bootstrap, etc.

Statistical machine learning, ensemble methods, regression, clustering, dimensionality reduction, kernel methods, Bayesian methods.

Randomized numerical linear algebra

Matrix sketching, randomized matrix computation, kernel approximation, etc.

Distributed computing

The design, analysis, and implementation of distributed algorithms (for machine learning and optimization).

Major Experience

Department of Computer Science, Stevens Institute of Technology, from 08/2018

tenure-track assistant professor

Department of Statistics, UC Berkeley, 07/2016---06/2018

postdoc researcher, with Michael Mahoney

Zhejiang University, Doctor of Engineering, 09/2011---06/2016

College of Computer Science and Techonology

Zhejiang University, Bachelor of Engineering, 08/2007---07/2011

College of Computer Science and Techonology

Chu Kochen Honors College

Graduate with "the 100 Best Bachelor Theses Award"

Representative Papers [Full List] [Google Scholar]

  • Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds.
    Shusen Wang, Alex Gittens, and Michael W. Mahoney.
    Accepted by Journal of Machine Learning Research (JMLR), conditioned on minor revisions.
    arXiv:1706.02803.

  • Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging.
    Shusen Wang, Alex Gittens, and Michael W. Mahoney.
    Journal of Machine Learning Research (JMLR), 18(218):1-50, 2018.
    [pdf] [bib]

  • GIANT: Globally Improved Approximate Newton Method for Distributed Optimization.
    Shusen Wang, Farbod Roosta-Khorasani, Peng Xu, and Michael W. Mahoney.
    To appear in NIPS 2018; available at arXiv:1709.03528.
    [Spark Code] [Large-Scale Experiments]

  • Improving CUR Matrix Decomposition and the Nystrom Approximation via Adaptive Sampling.
    Shusen Wang and Zhihua Zhang.
    Journal of Machine Learning Research (JMLR), 14: 2729-2769, 2013.
    [pdf] [bib]

Major Honors and Awards

Baidu Scholarship, 2014

award to 8 Chinese students around the world, CNY 200,000

Microsoft Research Asia Fellow, 2013

award to 10 students in Asia Pacific, USD 10,000

Scholarship Award for Excellent Doctoral Student Granted by Ministry of Education, 2012

award to 25 PhD students from all majors in Zhejiang University, CNY 30,000

National Scholarship for Graduate Students, 3 times, 2012-2014

CNY 30,000 each time

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Last update: 2018-06-18