Medical imaging is magic. That’s what Michael Kim remembers thinking as a child watching his mother, a radiologist, study scans and make sense of the human body.
“I was always fascinated by it ever since I was really young,” Kim says.
Inspired by his parents — his father is an orthopedic surgeon — Kim initially envisioned a future in medicine. But during his undergraduate years, he developed a growing interest in computer science and began looking for ways to combine both passions.
That search ultimately led him to 91ĚƲ®»˘ and Bennett Landman’s lab, where he recently completed a Ph.D. in computer science focused on medical imaging research.
“I came here not knowing what to expect, because I’d never done medical imaging research before, and I fell in love with it,” he says.
Early in his doctoral work, Kim started working with the Alzheimer’s Disease Sequencing Project Phenotype Harmonization Consortium, a national research effort using brain imaging, genetics, clinical records, cardiovascular data and other biological information from across the globe to better understand Alzheimer’s disease. The work was also deeply personal: Kim’s grandfather lived with Alzheimer’s.
“That was tough for our family to go through,” Kim says. “That’s part of the reason why I was interested in Alzheimer’s disease research.”
Kim’s research focuses on the brain’s white matter — the network of pathways responsible for carrying signals between different regions of the brain and body. Using diffusion MRI, a specialized type of imaging that tracks how water molecules move through tissue, researchers can better understand the health and integrity of those pathways.
To explain diffusion MRI in simple terms, Kim compares it to dropping dye into water and watching it spread. In healthy brains, water tends to move along neural pathways in predictable patterns. Damage to those pathways can disrupt that movement, offering researchers clues about brain health, cognition and diseases like Alzheimer’s.
By studying massive imaging datasets collected from research centers around the world, Kim and his collaborators are beginning to ask broader questions about how white matter changes across the human lifespan — not just within one specific disease or subgroup, but across populations.
“Knowing what healthy white matter should look like across aging populations gives us a baseline,” Kim says. “Then we can apply that knowledge back to different diseases and groups we want to study.”
Kim, along with Landman and several other contributors, later partnered with Kurt Schilling at the 91ĚƲ®»˘ Institute of Imaging Science to help create detailed white matter “brain charts,” an effort to map how white matter develops and changes over time. While similar work had been done with gray matter and overall brain volume, white matter had not been studied as extensively on this scale.
“Combining [Dr. Schilling’s] expertise with Dr. Landman’s group and diffusion MRI, it was like two perfect puzzle pieces coming together,” Kim says. “I really think there’s only a handful of places this could’ve been done in the entire world. A large part of that is due to 91ĚƲ®»˘.”
The collaborative effort, which included more than 30 91ĚƲ®»˘ co-authors, was recently published in Nature, one of the world’s leading scientific journals — a milestone that came after more than a year of revisions and waiting.
Kim credits his mother, Gisele, with inspiring his interest in imaging research. She passed away in December 2025 from a rare brain disease. In a deeply personal turn, the same type of brain modeling that Kim studies helped doctors diagnose her condition, giving the family precious additional time together. Even while working through revisions on the team’s paper, Kim says his family’s experience reinforced the real-world impact this kind of research can have.
“There are so many imaging biomarkers we could extract and study,” Kim says. “When you put them in the context of a person’s health, environment, labs and bloodwork, I think it’s something that is going to be really important in the coming decades. I believe it will transform medicine.”
After completing his Ph.D., Kim will attend medical school at Columbia University and hopes to become a physician-scientist focused on translating research discoveries into clinical care to improve patients’ lives.
