About Me

I am a Ph.D. candidate in Statistics at New York University advised by Professor Halina Frydman. I have worked closely with Professor Jeffrey S. Simonoff at Stern NYU, Professor Denis Larocque at HEC Montréal, Professor Soledad Villar at Johns Hopkins University, Professor David W. Hogg at New York University, Professor Joshua Loftus at London School of Economics, and Professor Yixin Wang at University of Michigan.

My research interests lie in developing machine learning methodology and algorithms to tackle problems in various fields.

I have worked in the healthcare related fields, where we developed forest methods for better estimation and prediction in survival analysis; in particular, methods that can model data with time-varying covariates in a dynamic fashion.

Recently I focus on designing equivariant deep learning models that respect approximate symmetries in physical laws, such as translation and rotation. We aim to develop and demonstrate the our method's capacity for application in prediction for dynamical systems.

I also work on designing deep neural networks for active learning and active optimization. Our goal is to improve accuracy and reliability of the powerful deep learning algorithms at a reduced cost of time and human resources for science projects.

Here is my CV.

Research

Preprints and workshop papers

  • W. Yao, K. Storey-Fisher, D. W. Hogg and S. Villar
    A simple equivariant machine learning method for dynamics based on scalars
    Proceedings of the Advances in Neural Information Processing Systems (NeurIPS) 2021 Workshop on Machine Learning and the Physical Sciences, 2021.  
    arXiv code

Publications

  • S. Villar, W. Yao, D. W. Hogg, B. Blum-Smith and B. Dumitrascu
    Dimensionless machine learning: Imposing exact units equivariance
    Journal of Machine Learning Research (to appear), 2022.  
    arXiv code
  • W. Yao, H. Frydman, D. Larocque and J. S. Simonoff
    Ensemble methods for survival function estimation with time-varying covariates
    Statistical Methods in Medical Research, 31(11):2217-2236, 2022.  
    pdf link code
  • S. Villar, D. W. Hogg, K. Storey-Fisher, W. Yao and B. Blum-Smith
    Scalars are universal: Equivariant machine learning, structured like classical physics.
    Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), 2021.
    arXiv code
  • H. Moradian, W. Yao, D. Larocque, J. S. Simonoff and H. Frydman
    Dynamic estimation with random forests for discrete-time survival data.
    The Canadian Journal of Statistics, 50(2):533-548, 2021.
    pdf link code
  • W. Yao, H. Frydman and J. S. Simonoff
    An ensemble method for interval-censored time-to-event data.
    Biostatistics, 22(1):198-213, 2021.
    pdf link code
  • W. Yao, A. S. Bandeira and S. Villar
    Experimental performance of graph neural networks on random instances of max-cut.
    Proceedings of the Society of Photographic Instrumentation Engineers, 2019.
    pdf link code
  • J. H. Lee, D. E. Carlson, H. S. Razaghi, W. Yao, G. A. Goetz, E. Hagen, E. Batty, E. J. Chichilnisky, G. T. Einevoll and L. Paninski.
    YASS: Yet Another Spike Sorter.
    Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), 2017.
    pdf link code
Experience

STAT-UB1.001 Statistics for Business Control at NYU Stern (Summer 2020)

I am/was a teaching fellow at New York University for

  • XBA1-GB.8314: Operations Analytics (Summer 2021, Fall 2020, Spring 2019)
  • STAT-GB.3205: Analytics & Machine Learning for Managers (Spring 2021)
  • STAT-GB.3321: Introduction to Stochastic Processes (Spring 2021)
  • STAT-UB.0103: Statistics for Business Control Regress & Forecasting Models (Fall 2020, Summer 2020)
  • COR1-GB.1305: Statistcs and Data Analysis (Fall 2018)

I was a rearch assistant with Professor Liam Paninski at Grossman Center for the Statistics of Mind, Columbia University (2016–2017). We worked on projects that develop statistical methodology for understanding how neurons encode information.

Education

B.A. in Finance & B.A. in Applied Mathematics 2011-2015

Economics and Management School & Mathematics and Statistics School, Wuhan University