Robert A. McDougal, PhD, is an assistant professor in the YSPH Health Informatics Division of the Department of Biostatistics. McDougal is affiliated with the computational biology and bioinformatics graduate program, the Yale Center for Medical Informatics, and the Center for Biomedical Data Science. His research focuses on developing methods for aggregating, computationally representing, analyzing, and modeling experimental data, with an emphasis on understanding brain function and dysfunction.
McDougal is a principal investigator on two National Institutes of Health grants seeking to build efficient methods for simulating the interaction of intracellular and network dynamics in the brain. Recent collaborations include a project to detect trends in the use of animal models and interventions in the Alzheimer's literature, and a project to use computational modeling to interpret magnetoencephalography (MEG) data. As a member of the NeuroML Scientific Committee, he supports the development of future standards for sharing computational neuroscience models.
Course name: BIS 544E (Computational Methods for Informatics)
What drives you in your work in health informatics? What are you passionate about?
I love problem solving. Informatics, broadly speaking, is the science of how we can store, analyze, compute with, and communicate information. Our ability to aggregate and preserve information is better than ever, giving us the ability to ask new questions. As we try to answer these questions, we may find that there is an obvious way forward except that it would take years to get an answer, or it would take too many computer resources, or it would not preserve privacy. Coming up with novel solutions to these problems is fun and allows us to answer even harder questions in the future.
Why did you choose a career in public health?
I want to make a positive difference in the world. My PhD was in mathematics, which gets an unfair reputation for being overly abstract. But within public health, I can use my quantitative skills to address public health problems. One day I might be studying ischemic stroke, and on another I’m reviewing electronic health record usage patterns. I also love teaching. Knowing how to communicate about public health and scientific knowledge is critical to being effective in public health. It’s exciting to go to work every day and to learn how my colleagues and students are applying their skills to advance public health.
What is the most significant challenge facing your field of study today, and where is the opportunity related to that challenge?
One of the most exciting, and one of the most challenging developments of the last few years is the rapid advancement in artificial intelligence technologies. This is great in that it democratizes informatics; you don’t need to be a programming expert to do well in my course, BIS 544E (Computational Methods for Informatics), because there are new tools that can help you. Our challenge is to ensure that these tools are used in scientifically valid ways, and that they help us to learn and communicate without built-in biases. It is one thing to say that something is predictive of heart disease, but another to be able to say why it is predictive. Building out these technologies to make mechanistic explanations and to communicate better about public health is the key scientific opportunity these technologies present.