Mike Hughes, PhD, Assistant Professor, Computer Science at Tufts University
About: Michael C. Hughes (“Mike”) is an Assistant Professor of Computer Science at Tufts University, where he does research in statistical machine learning and its applications to healthcare. His goal is to develop predictive and explanatory models that find useful structure in large, messy datasets and help people make decisions in the face of uncertainty. His research interests include Bayesian hierarchical models for sequences and images; optimization algorithms for approximate inference; and learning from limited labeled data. Active projects include helping clinicians automatically diagnose cardiovascular disease from ultrasound images of the heart, assessing risk of stroke and dementia from neuroimages, and predicting risk of mortality from time-varying vital signs and laboratory results available in electronic health records.
Visit his website for links to recent papers, open-access datasets, and open-source code.
Previously, from 2016-2018 he was a postdoctoral fellow in computer science at Harvard’s School of Engineering and Applied Sciences (SEAS), advised by Prof. Finale Doshi-Velez. He completed a Ph.D. in the Department of Computer Science at Brown University in 2016, advised by Prof. Erik Sudderth.
- LinkedIn: https://www.linkedin.com/in/michaelchughesli
- Google Scholar: https://scholar.google.com/citations?hl=en&user=ugSmcnoAAAAJ