Scientific Interests

Brief Background:

Cancer cells undergo Darwinian evolution, whereby cell-intrinsic and extrinsic factors modify a cell’s fitness that in turn propogates continual selection. Intrinsically, genetic and epigenetic factors modify cellular phenotypes. Extrinsically the tumour microenvironment (TME) composed of many “normal” human cells ranging from fibroblasts to immune cells impose conditions that select for the fittest cancer cell (with varying definitions). Together, these factors lead to highly heterogeneous populations within the same patient, and within the same tumour. This diversity contributes to metastasis and drug-resistance; therefore, understanding the driving factors behind this diversity and identifying possible evolutionary trajectories is an important area of research. Improved understanding of tumour evolution can lead to the development of targeted therapies and hopefully improved patient outcomes.

Research Interests:

Broadly, my research interests intersect to solve biological problems, including the one introduced above. Naturally, I am interested in topics from biology, computer science, and statistics.

  • On the biology side, I am interested in topics related to immunology, selection, the tumour microenvironment, and cancer evolution.
  • On the quantitative side, I am interested in statistical machine learning, bayesian modelling, and statistical inference.
    • I am interested in applying existing methods to uncover interpretable and experimentally-verifiable latent variables.
    • I am interested in developing novel methods to address specific biology-related questions that existing methods are insufficient for.

Others:

  • I am interested in studying software principles to write well-designed and extendable software.
  • I am interested in developing a greater understanding of fundamental statistical and mathematical principles. This is an area of further self-study.

<!– Acknowledgements

I have been blessed to have had so many mentors through my careeer. In academic circles, I would like to thank Drs. Christian Steidl, Ryan Morin, Ben Greenbaum, Ed Reznik, Laura Hilton, Katsuyoshi Takata, and Aixiang Jiang. I have missed many. –>