Dr. Daza is the principal investigator of the Causes and Associations in Single-Individual Analysis (CASIA) Project. He leads a Stanford Center for Clinical and Translational Research and Education (Spectrum) pilot study to improve personalized discovery of health-related causes and effects using machine learning---in particular, utilizing data from wearable or implanted devices, sensors, or mobile apps.
Eric J. joined the Stanford Prevention Research Center in 2015 as a postdoctoral research fellow under the mentorship of Mike Baiocchi. He earned his DrPH (Doctor of Public Health) in Biostatistics at the Gillings School of Global Public Health at the University of North Carolina at Chapel Hill, under advisors Michael Hudgens and Amy Herring. He had earlier completed his MPS in 2002 and BA in 2000 at Cornell University. He has worked in both the pharmaceutical industry and academia (i.e., research projects involving clinical trials, survey sampling, global nutrition and maternal/child health, and health promotion + disease prevention).
His main interests include causal inference, longitudinal missing data methods, mobile health, self-experimentation, n-of-1 (i.e., single-subject) studies, public health data science, minority health (focusing on Asian Americans, in particular Filipinos), microbiome research, and research on gun violence and use-of-force training.
Honors & Awards
Young Investigator Award: 2018 Sage Assembly: Algorithms and the Role of the Individual, Sage Bionetworks (19 – 21 April 2018)
Pilot Award: Improving Personalized Medicine through N-of-1 Causal Inference and Predictive Modeling, Stanford Center for Clinical and Translational Research and Education (Spectrum) (May 2017 – June 2018)
DrPH, The University of North Carolina at Chapel Hill, Biostatistics (2015)
MPS, Cornell University, Applied Statistics (2002)
BA, Cornell University, Neurobiology & Behavior and Cognitive Studies (2000)