Foundations of Data Science
Michael Burke is currently a Director’s Postdoctoral Fellow at Argonne National Laboratory; he will be joining the faculty at Columbia University in July 2014 as an assistant professor in Mechanical Engineering and affiliated member of the Institute for Data Sciences and Engineering (IDSE). He received his Ph.D. in Mechanical and Aerospace Engineering at Princeton University, where he studied the flame properties and chemical kinetics of high-pressure hydrogen combustion. Afterwards, he joined the Chemical Sciences and Engineering Division at Argonne to create interdisciplinary modeling approaches for complex systems frequently encountered in energy devices. He applies these approaches to combustion systems relevant to high-efficiency, low-emissions engines and is also involved in collaborations to apply similar techniques for materials applications (http://www.anl.gov/articles/michael-p-burke).
His primary research interests lie at the intersection of diverse areas—multi-scale modeling, data sciences, and automation—applied in mixed-experimental-and-computational investigations of complex reaction networks and reacting flows encountered in advanced combustion and energy applications. He is interested in combining high-throughput automated experiments and data sciences techniques, for example, to predict the emissions from potential biofuels, identify the ideal additive for longer lasting batteries, or quantify the lifetimes of greenhouse gases in the atmosphere.