I am an Associate Professor jointly appointed by the Centre for Quantitative Medicine and the Program in Health Services and Systems Research, Duke-NUS Medical School, and the Department of Statistics and Data Science at the National University of Singapore. I also hold an Adjunct Associate Professor position with the Department of Biostatistics and Bioinformatics at Duke University. At Duke-NUS, I had previously served as the Director of the Centre for Quantitative Medicine (2014-2018), and as the founding Co-director of the PhD program in Quantitative Biology and Medicine, first of its kind in Singapore.
Prior to joining Duke-NUS in 2013, I was an Assistant Professor at the Department of Biostatistics, Columbia University during 2009-2013. Previously, I had completed my Master of Statistics degree from the Indian Statistical Institute, Kolkata, India, and then my PhD in Statistics from the University of Michigan, Ann Arbor, under the supervision of Prof. Susan A. Murphy. Here is a copy of my dissertation.
I am a recipient of the Young Statistical Scientist Award in 2017 from the International Indian Statistical Association (IISA) and an Elected Member of the International Statistical Institute (ISI) in 2022.
My primary research interest lies in developing statistical methods to facilitate data-driven personalized medicine in a time-varying setting, specifically in the area of dynamic treatment regimes (DTRs) or adaptive interventions. DTRs are decision rules about recommended treatments based on past treatment and time-varying patient characteristics. Once developed, these treatment regimes can be employed as decision support systems for clinicians, and are deemed as a key element of the chronic care model of health care. Jointly with Dr. Erica E.M. Moodie, I wrote the first textbook on this cutting-edge topic, published by Springer Inc., New York, in August 2013.
I have strong interest and expertise in modern clinical trial designs, including sequential multiple-assignment randomized trials (SMARTs) for DTRs, various types of adaptive designs, and multiphase optimization strategy (MOST) for developing multicomponent interventions using full and fractional factorial designs.
More recently, I got deeply interested in mobile/digital health interventions (e.g., just-in-time adaptive interventions, or JITAIs) and associated micro-randomized trials (MRTs), as well as analysis of big electronic health records data using (interpretable) machine learning tools. I organized a thematic workshop on Statistical Methods for Developing Personalized Mobile Health Interventions hosted by the NUS Institute of Mathematical Sciences in February 2019.
Here is the link to my Google Scholar citation page.
And here is a newspaper article on personalized smoking reduction strategies, co-authored by my PhD student Yan Xiaoxi and myself.