Mika Mustafayev ’27: Bulsai Health
Since middle school, I’ve been intrigued by the idea of using computers to test how artificial intelligence can improve existing technologies. Working with Bulsai, a startup company, I had the opportunity to analyze large datasets and build information classifiers with the ultimate goal of helping diabetics.
Bulsai analyzes subcutaneous tissue to detect lipohypertrophy—a buildup of fatty tissue in areas injected with insulin over and over. This build-up of tissue heavily restricts insulin intake. Therefore, even though a diabetic could be taking all their insulin properly, they may face dangerous complications if they do it in the same area too many times.
Every week, my supervisor, Jim Ervin, would send me a fresh batch of data from their trials. I trained machine learning algorithms on sensor data to distinguish lipohypertrophy from healthy tissue. The algorithm can then instantly analyze new sensor data to flag potential problem areas completely noninvasively.
This internship taught me to turn raw sensor data into actionable predictions while emphasizing rigorous analysis in healthcare. My early models were promising, but true clinical validation requires larger datasets; this showed me the vital intersection of technology and medicine.
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