We focus on challenges that arise in modern datasets and multi-view learning. Our methods development is motivated by applications in molecular microbiology, microbiome multi-omics, spatial multi-omics, and loss reserves in non-life insurance. Some areas that we use to develop methods include matrix factorization, mixture models, generative models, approximation theory, nonparametric statistics, computational statistics, spatial statistics, Bayesian modeling, and Bayesian sampling methods.

Current Team Members

Graduate Students

Name Role Research Note
Pengfei Cai Ph.D. student in statistics Prediction on multiple loss triangles: application to loss reserve in multiple business lines Co-supervision with Dr. Anas Abdallah, 2021-2024
Inwook Black Ph.D. student in statistics Replicated (multiple view) spatial point pattern: application to spatial omics expect to start in Fall 2022
Ishanka Fernando M.Sc. student in statistics Multiple (structured) count matrices: application to microbiome data expect to start in Fall 2022

Undergraduate students

Name Role Research Note
Shiheng Huang Undergraduate thesis student Replicated (multivariate marked) spatial point pattern: application to the analysis of the brain tumor samples expect to start in Fall 2022

Alumni

Undergraduate students

Name Role Research Note
Hainan Xu Undergraduate research student Spatial point pattern summaries of multiple views: application to the analysis of the primary visual cortex James Stewart Student Research Award, May - July 2022
Mariana Mariles Torres Undergraduate Research Assistant Monte Carlo experiments for generative models with goodness-of-fit measures: application to microbiome data Fall 2021 - Winter 2022
Ka Yat Liu Undergraduate research student Prior sensitivity analysis and multiplicative noise effects in Bayesian sampling methods: application to microbiome data, https://github.com/kaidenliu0806/summer_research James Stewart Student Research Award, May - August 2021
Gheeda Mourtada Undergraduate research student Spatial point pattern summaries for spatial count matrix: application to spatial proteomics data NSERC USRA, May - August 2021

Prospective students

We welcome

  • undergraduate research students in
    • Spring/Summer with NSERC USRA/Stewart Award,
    • Fall for undergraduate research assistants,
    • Fall - Winter for undergraduate thesis.
  • graduate (masters and PhD) students (Statistics, Computational Science and Engineering) in
    • Fall
  • postdocs throughout the year.

Please look at Join Us for more details.