Hi there! I’ve you’re on this page, you’re likely trying to learn a little more about who I am, what I do, and why I’m here. I’m a Data Scientist supporting the All of Us Research Program (AOU) at the National Institutes of Health (NIH). AOU was established to accelerate health research and medical breakthroughs to enable an era of precision medicine for all. The program seeks to achieve this mission through building relationships with one million or more participant partners, delivering the largest, richest biomedical dataset ever, and catalyzing a robust ecosystem of researchers eager to use the dataset to advance human health. As Data Scientist, my role is to build sophisticated data pipelines and products to wrangle and analyze data, drive analytics innovation and experimentation to enable data-driven insights for complex business and scientific problems, thereby playing a key role to enable application of advanced analytics techniques across the organization.
My background is in Industrial and Systems Engineering with a specialization in healthcare systems and processes. During my team in Graduate School at North Carolina State University, I was involved in efforts that use operations research (OR) and analytics to inform public policies on a population level as part of RA funded work. The primary project related to these efforts was the use of a detailed simulation model of individuals’ choice and response to public health type interventions for colorectal cancer screening. Furthermore, my dissertation aimed to improve hospital operational efficiency using dynamic programming and queueing theory to optimize different decisions within the health care process, such as patient flow and resource utilization. My prior experience also includes Social Network Analysis (SNA) and resource allocation under uncertainty. My research using SNA involved studying the user-engagement patterns in an online smoking cessation forum to develop a framework for prescriptive applied research. My interests in resource allocation under uncertainty led to my work on the sequential stochastic assignment problem (SSAP) which studies the allocation of available distinct workers with deterministic values to sequentially arriving tasks with stochastic parameters to maximize the expected total reward obtained from the assignments. All the projects I undertook during my time in graduate school had the underlying theme of incorporating the ‘human’ element in OR/Analytics models to influence policy on a large scale.
During my time as a Post-Doc at MedStar Health Research Institute, I continued participating in research efforts that use OR and analytics to inform public policies and to help improve access to healthcare. Some examples of projects that I was involved in include 1) building and evaluating a cardiovascular disease risk calculator that estimates a patient’s future risk of having a heart attack or stroke, 2) developing dfecision support tools to enable physicians to identify if an incoming patient requesting prenatal care could be at a high risk of developing adverse maternal health outcomes, and 3) leading a project aimed at evaluating the efficacy of a biometric wearable device (containing Machine Learning algorithms) to identify the presence of COVID-19 infection, and 4) leading a project aimed at evaluating the state of Opioid Use Disorder screening and treatment among pregnant and parenting individuals within the District of Columbia.
Please feel free to reach out to me if you’d like to discuss any of my work. I love talking shop, be it over a virtual or an actual cup of coffee :)