I am currently a Data Scientist at GRAIL, Inc where I am working on developing computational methods to analyze diagnostic tests for detecting cancer in its early stages.

My research interests are in developing machine learning techniques to address problems in computational biology. Currently, there is an explosion of genome, transcriptome and proteome data available for biological systems. However, understanding the genetic basis of disease and the regulatory relationships between molecular entities creates significant challenges in machine learning. I am interested in advancing machine learning so that we can reliably predict this information in such settings.

I was previously a post doctoral researcher at Carnegie Mellon University in the Computational Biology Department with Seyoung Kim. Before that, I did my Ph.D. in the Machine Learning Department at Carnegie Mellon University.

I previously interned with Jennifer Listgarten and the eScience group at Microsoft Research where I worked on developing efficient statistical methods for testing gene-gene interactions using low-rank matrix tricks.

Before that, I was a Master’s student in Biomedical Engineering at the University of British Columbia in Vancouver, Canada. I was supervised by Robert Rohling and Purang Abolmaesumi in the Robotics and Control Laboratory. I worked on algorithms for CT to ultrasound registration for minimally invasive surgery. And because of that, I have one engineering degree! I did my Bachelor of Computing specializing in Biomedical Computing at Queen’s University in Kingston, Canada.