A mathematician and a pulmonologist walk into a bar…
As tales of unlikely convergences go, this one is about the improbable intersection of big data and clinical efforts to combat bacterial drug resistance. Except in this case, the paths of mathematician Michael Baym and pulmonologist Maha Farhat crossed here in the Department of Biomedical Informatics at Harvard Medical School.
Farhat and Baym are the newest faculty members of a young but rapidly growing department aspiring to improve diagnoses and catalyze treatments by translating information into practical clinical knowledge.
Farhat and Baym are on a quest to do just that.
“We met very recently and, as it turns out, we have a lot of common threads in our work,” Farhat said.
For one, they share a passion for unraveling the evolutionary mysteries of microbial drug resistance and curbing its spread. They also each harbor a belief that the most promising pathway to solving drug resistance lies in using large-scale genomic data and computation.
“We ended up basically identifying the same problem taking a very similar angle on a solution, despite coming from completely different backgrounds and skill sets,” Baym said.