Ph.D. candidate Md Abdur Rahaman’s dissertation studies brain data to understand how changes in brain activity shape behavior.
Computational tools Rahaman developed for his dissertation look for informative patterns between the brain and behavior. Successful tests of his algorithms show promise to help doctors diagnose mental health disorders and design individualized treatment plans for patients.
Unsurprisingly, Rahaman successfully defended his dissertation and is on his way to graduate in a few weeks.
“I've always been fascinated by the human brain and how it defines who we are,” Rahaman said.
“The fact that so many people silently suffer from neuropsychiatric disorders, while our understanding of the brain remains limited, inspired me to develop tools that bring greater clarity to this complexity and offer hope through more compassionate, data-driven care.”
Rahaman’s dissertation introduces a whole framework focusing on granular factoring. This computing technique stratifies brain data into smaller, localized subgroups. This makes it easier for computers and researchers to study data and find meaningful patterns.
Granular factoring overcomes the challenge of size and heterogeneity in neurological data science. Brain data is sourced from different modes, like neuroimaging, genomics, and behavioral datasets. Each of these sources are very large to study on their own, let alone analyzed at the same time to find hidden inferences.
Rahaman’s research allows researchers and physicians to move past one-size-fits-all approaches. Instead of manually reviewing tests and scans, algorithms look for patterns and biomarkers in the subgroups that otherwise go undetected, especially ones that indicate neuropsychiatric disorders.
“My dissertation advances the frontiers of computational neuroscience by introducing scalable and interpretable models that navigate brain heterogeneity to reveal how neural dynamics shape behavior,” Rahaman said.
“By uncovering subgroup-specific patterns, this work opens new directions for understanding brain function and enables more precise, personalized approaches to mental health care.”
Rahaman defended his dissertation on April 14, the final test in completing his Ph.D. in computational science and engineering. He will graduate on May 1 at Georgia Tech’s Ph.D. Commencement.
After walking across the stage at McCamish Pavillion, Rahaman’s next step in his career is to Amazon where he will work in the generative artificial intelligence (AI) field.
Graduating from Georgia Tech is the peak of an educational summit spanning over a decade. Rahaman hails from Bangladesh where he graduated from Chittong University of Engineering and Technology in 2013. He attained his master’s from the University of New Mexico in 2019 before starting at Georgia Tech.
“Munna is an amazingly creative researcher,” said Vince Calhoun, Rahman’s advisor and Distinguished University Professor. Calhoun is the founding director of the Translational Research in Neuroimaging and Data Science Center (TReNDS).
TReNDS is a tri-institutional center spanning Georgia Tech, Georgia State University, and Emory University that develops analytic approaches and neuroinformatic tools. The center aims to translate the approaches into biomarkers that address areas of brain health and disease.
“His work is moving the needle in our ability to leverage multiple sources of complex biological data to improve understanding of neuropsychiatric disorders that have a huge impact on an individual’s livelihood.”
Bryant Wine
Communications Officer II
College of Computing