Michael B.

At Boston University, Michael received Dean’s List recognition and was inducted into Tau Beta Pi and IEEE-Eta Kappa Nu, both of which recognize students in the top 20 percent of their class. Michael began teaching as an undergraduate at Boston University, where he taught Electric Circuits to roughly 200 students per semester, organized teaching sessions, designed lab assignments, and tutored students one-on-one. He also served in a leadership capacity in his school's chapter of the Student National Medical Association.

Michael began his research career in college, at Harvard’s Rowland Institute, developing machine learning tools to quantify gait patterns in studies of cerebellar learning while also working as an EMT. He later conducted clinical research at Massachusetts General Hospital, designing models to optimize deep brain stimulation targeting for movement disorders and collaborating with clinical teams developing stem cell therapies for Parkinson's disease. Now a neuroscience doctoral candidate at Mount Sinai’s Friedman Brain Institute, he studies cognitive flexibility in mouse models of Alzheimer’s disease using miniscope imaging. He has presented his work at the Society for Neuroscience Annual Meeting and Massachusetts General Hospital Clinical Research Day.

At Mount Sinai, Michael later served as a teaching assistant and Course Representative for Brain and Behavior, creating supplemental materials and working with faculty to improve how medical students learned neuroanatomy and neurophysiology. He co-leads Mount Sinai's Wilderness Medicine Interest Group and also serves as a study monitor for the liver transplant team at Mount Sinai, tracking organ viability during machine perfusion cases.

Michael’s approach to tutoring reflects his own path to medicine. Coming to the MCAT as an engineer rather than a traditional pre-med, he learned much of the material by reasoning from first principles, which reinforced his belief that the exam rewards reasoning more than memorization. He believes that most students who feel stuck are closer to their goal than they believe.

Michael takes a diagnostic, efficiency-driven, and systems-oriented approach to MCAT tutoring, identifying where students lose points and prioritizing high-yield areas with the greatest potential for improvement. He has found that many plateaus are not content problems but pattern problems, whether a reasoning habit, a misread question stem, or a pacing issue that repeats across questions. From there, he works on two fronts at once: test-taking strategies that transfer broadly across sections, and targeted content review that emphasizes understanding the material rather than memorizing it.