Scientist, writer, policy advocate, YouTuber – before Jordan Harrod established her many successful career identities, her first role was as a student athlete. While she enjoyed competing in everything from figure skating to fencing, she also sustained injuries that left her with chronic pain. These experiences as a patient laid the groundwork for an interest in biomedical research and engineering. “I knew I wanted to make tools that would help people with health issues similar to myself,” she says.
Harrod went on to pursue her BS in biomedical engineering at Cornell University. Before graduating, she spent a summer at Stanford University doing machine-learning research for MRI reconstruction. “I didn’t know anything about machine learning before that, so I did a lot of learning on the fly,” she says. “I realized that I enjoyed playing with data in different ways. Machine learning was also becoming the new big thing at the time, so it felt like an exciting path to follow.”
Harrod looked for PhD programs that would combine her interests in helping patients, biomedical engineering, and machine learning. She came across the Harvard-MIT Program in Health Sciences and Technology (HST) and realized it would be the perfect fit. The interdisciplinary program requires students to perform clinical rotations and take introductory courses alongside medical students. “I’ve found that the clinical perspective was often underrated on the research side, so I wanted to make sure I’d have that. My goal was that my research would be translatable to the real world,” Harrod says.
Mapping the brain to understand consciousness
Today, Harrod collaborates with professors Emery Brown, an anesthesiologist, and Ed Boyden, a neuroscientist, to study how different parts of the brain relate to consciousness and arousal. They seek to understand how the brain operates under different states of consciousness and the way this affects the processing of signals associated with pain. By studying arousal in mice and applying statistical tools to analyze large datasets of activated brain regions, for example, Brown’s team hopes to improve the current understanding of anesthesia.
“This is another step toward creating better anesthesia regimens for individual patients,” says Harrod.
Since beginning her neuroscience research, Harrod has been amazed to learn how much about the brain still needs to be uncovered. In addition to…
Continue reading: https://news.mit.edu/2021/jordan-harrod-brain-ai-0829