to see a representative publication
Early years
My initial research interest was dimension reduction.
In the early years of my faculty career, I devoted much attention to efficient kernel machines for rare target detection and ensemble methods for variable selection.
I also worked on
algorithms for making personalized recommendations,
and applications of machine learning to healthcare informatics.
Recent years
While ensemble learning continued to captivate my curiosity, in more recent years I explored a hodgepodge of different topics—such as
evaluation metrics,
protein structures,
transactional networks,
and genetic epistasis.
I also wrote an op-ed for a major newspaper and a textbook for data science students.
At present, I am studying various problems about
dependence modeling,
large covariance matrices,
and generative neural networks.