Research Interests:

  • Bayesian nonparametrics:
        Dependent nonparametric models, MCMC methods and deterministic approximations for efficient inference in nonparametric models
  • Continuous time stochastic processes:
        MCMC methods for inference in Markov jump processes and continuous time Bayesian networks
  • Point processes:
        Nonstationary renewal processes and repulsive point processes
  • Markov chain Monte Carlo for doubly intractable problems
  • Machine learning

Selected publications:

  • Zhang, B. and Rao, V.A. (2018)
    Efficient parameter sampling for Markov jump processes

  • Rao, V.A., Adams,R.P. and Dunson, D.B. (2016)
    Bayesian inference for Matérn repulsive processes
    (accepted at JRSS-B)
    [arxiv:1308.1136] [supplementary] [bibtex]

  • Rao, V.A., Lin, L. and Dunson, D.B. (2016)
    Data augmentation for models based on rejection sampling
    [Biometrika] [bibtex]

  • Rao,V.A. and Teh, Y.W. (2013)
    Fast MCMC sampling for Markov jump processes and extensions
    Journal of Machine Learning Research 14:3295−3320, 2013
    [pdf] [JMLR] [bibtex]

  • Rao,V.A. and Teh, Y.W. (2009)
    Spatial normalized Gamma processes
    Advances in Neural Information Processing Systems 22 (NIPS 2009)
    [pdf] [bibtex]