I’m a T32 Postdoctoral Research Fellow on Substance Use Disorders at the Center for Population Health Sciences and Systems Neuroscience and Pain Lab at Stanford University. I received my doctorate from Harvard TH Chan School of Public Health in Quantitative Methods from the Department of Social and Behavioral Sciences, and I was a 2016 fellow at University of Chicago’s Data Science for Social Good summer fellowship.
My dissertation work involved studying how we can use multimodal data (i.e., individual-level high-density mobile phone data, microlevel death certificate data, or population level cell tower data) with spatial modeling, Bayesian methods, and data science to understand health disparities and social and behavioral determinants of health.
My current work is focused on applying these methods to the opioid epidemic, especially racial/ethnic disparities of fatal overdoses. Specifically, I’m working with Keith Humphreys, the Basu Lab, and the Shah Lab to leverage predictive modeling, machine learning, and causal inference to prevent opioid overdose and optimize treatment.
- Vable AM, Kiang MV, Glymour MM, Rigdon J, Drabo EF, & Basu S, Performance of matching methods to unmatched ordinary least squares regression under constant effects, American Journal of Epidemiology (April 2019), doi: 10.1093/aje/kwz093
- Kiang MV, Basu S, Chen JT, and Alexander MJ. Assessment of changes in the geographical distribution of opioid-related mortality across the United States by opioid type, 1999- 2016. JAMA Network Open (Februrary 2019). doi: 10.1001/jamanetworkopen.2019.0040 [Open Access] [PDF] [Code] [Shiny App] [Press Release] [CNN] [NBC]
- Gemmill A, Kiang MV, and Alexander MJ. Trends in pregnancy-associated mortality involving opioids in the United States, 2007-2016. American Journal of Obstetrics and Gynecology (January 2019). doi: 10.1016/j.ajog.2018.09.028 [Code] [Press Release]
- Kiang MV & Alexander MJ, Decomposition of the US Black/White inequality in life expectancy: Quantifying the impact of deaths of despair. Society for Epidemiologic Research Annual Meeting 2019: Minneapolis, MN (June 2019) [Slides coming soon]
- Course developer (x2), Using Python for Research via HarvardX V1 (Nov 2016) and V2 (Jan 2018), HSPH, Professor Jukka-Pekka Onnela
- Instructor, Intro to Causal Inference for Data Science Workshop (March 2017), Instituto Tecnológico Autónomo de México
- Teaching assistant (x2), Dynamics of Infectious Disease (Spring 2017 and Spring 2018), HSPH, Professor Caroline Buckee
- Teaching assistant, Society and Health (Fall 2013), HSPH, Professor Ichiro Kawachi
- Teaching assistant, Biostatistics II (Spring 2010), NYU, Professor Ying Lu
- Teaching assistant, Statistics I (Fall 2009), NYU, Professor Robert Norman
Current Working Papers
- Kiang MV, Krieger N, Buckee CO, Onnela JP, & Chen JT. Decomposing the geographic distribution of black-white inequalities in premature mortality in the United States, 2010–2015. [Under Review]
- Kiang MV, Chen JT, Buckee CO, Krieger N, & Onnela JP. The human factors of digital phenotyping: Evaluating the feasibility of mobile phones in health inequalities research.
- Kiang MV, Onnela JP, Krieger N, Chen JT, & Buckee CO. Predicting dengue in Thailand: Comparing administrative and empirical areal units. [Under Review]
- Kiang MV, Tsai AC, Alexander MJ, Rehkopf DH, Basu S. The rapid acceleration of opioid-related deaths among non-Hispanic Black Americans, 1999–2017. [Under Review]
- Kiang MV, Humphreys KN, Cullen MR, Basu S. Opioid prescribing patterns among US providers, 2003–2017. [Under Review]
†Authors contributed equally.
‡Best student poster award.