I teach databases and data science in the Computer Science Department at Rice University. I received an S.B. degree in Computer Science and Engineering from the Massachusetts Institute of Technology, a professional M.S. degree in Computer Science from Stanford University, and a research M.S. degree and Ph.D. in Computer Science from Rice University.
Since the day I first graduated from college I have been interested in applying technology to improve healthcare. My first position was developing software for a medical device manufacturer. This job kindled my interest in the healthcare field. As part of my master’s degree in computer science, I enrolled in courses in biomedical informatics, a nascent field, at the time. This coursework included both didactic learning and a research project where I collaborated with a family practice physician. These early partnerships with medical professionals shaped both my philosophy and my path forward. After completing my master’s degree in computer science, I started working in a research group at Baylor College of Medicine. There, I had the chance to design, build, and support a prototype distributed electronic health record, for the citywide Teen Health Clinics1.
In 2008, while working at the University of Texas MD Anderson Cancer Center building a data warehouse to enable longitudinal research of surgical data, I realized that I wanted to use the data warehouse, not just build it. That epiphany led me to first complete a certificate in Health Informatics from the University of Texas School of Biomedical Informatics, and later to return to school (Rice University) for a PhD in Computer Science, with a focus on machine learning and data science. These areas built upon my strong computer science background and data centric work history. I brought a collaboration with researchers at MD Anderson to my PhD program and forged new partnerships with researchers at Baylor College of Medicine. In addition, I was awarded an NIH National Library of Medicine training fellowship for three years of my PhD. The fellowship provided additional training and mentorship and honed my informatics knowledge and skills.
After completing my PhD, I worked as a Data Scientist at Houston Methodist, a hospital system in Houston, Texas. There, I had the opportunity to work on clinically driven, data centric projects as well as helping to establish baseline processes for preserving patient monitoring data. In August 2017, I returned to academia, teaching a graduate course in Databases in the evenings at Rice University. That experiment led to a full-time teaching appointment in the Computer Science Department at Rice.
At Rice I have had the opportunity to explore and innovate in Data Science pedagogy. Shortly after returning to Rice, I joined a research group, the Children’s Environmental Health Initiative (CEHI). Joining this team has enabled me to stay involved in research and to continue to work on interesting and novel problems that also have the potential to motivate classroom learning. I continue to be fascinated with data – how do we collect, clean, manage, and use data to solve problems? How can we improve all of these steps?
I enjoy working in this intersection of healthcare data and computer science where I have the opportunity to build new relationships, understand the challenges faced by practitioners in both fields, help people answer questions that matter, and train the next generation of researchers and practitioners.
I am interested in exploring and innovating in data science pedagogy. I do this both through the development of interactive learning materials and by bringing lessons learned from research into the classroom in the form of examples, assignments, and exercises. Together with Lydia Kavraki and Chris Jermaine we have packaged a graduate level course on Data Science Tools & Models with an emphasis on healthcare data. The lecture slides are available here
and the teaching materials are available to instructors by request.
My research with the CEHI team is focused on data management in healthcare. There I explore approaches to making healthcare data more accessible and available.