Raj Vaza, who received his Master of Science in Biomedical Data Science degree at Mount Sinai’s Graduate School of Biomedical Sciences in 2023, says that Mount Sinai had much to offer him, but one top opportunity was working in the Huang Lab in Computational Omics. Under the direction of Kuan-Lin Huang, PhD, Assistant Professor, Genetics and Genomic Sciences, Mr. Vaza worked on a capstone project that studied common and rare genetic variants to predict the risk of Alzheimer’s disease.
In the following Q&A, Mr. Vaza discusses his recent achievements at Icahn Mount Sinai and his career aspirations.
What first attracted you to this area of study?
It combines my interests in human biology and computer science, and I believe having a master’s would make me a more prepared candidate for medical school. Health care will become more data-driven and personalized. For me to be an effective physician, I need to understand how massive amounts of data can improve health care. As for neurology, my grandparents had Parkinson’s disease and dementia and as a child—as early as the sixth grade—I was curious about what ailed my grandparents.
What did you find most satisfying about the work you did in Dr. Huang’s lab?
It’s very exciting to be at the forefront of Alzheimer’s research. We have all these genetic sequencing tools, and the goal of my capstone project was to see how we can take the information we already had on common genetic variants and combine it with the data we’re collecting about rare variants. We’re trying to understand the differences at the genetic level and in the future, the protein level, to enable us to predict individual risk.
Why Mount Sinai—what, specifically, are the strong points of this program?
I majored in human biology and minored in computer science, so the Biomedical Data Science program was the perfect niche for me. It enabled me to look at the intersection of computers and data science with biology and medicine. And Mount Sinai, as a massive research and health care environment, presented all kinds of resources and opportunities to explore this intersection. Mount Sinai has so many resources available for students. For example, we have our own high-performance supercomputer and a database of genetic data for 30,000 individuals.
And the classes are exceptional. The Machine Learning for Biomedical Data Science course I just finished was the most informative and tied together everything I’ve been learning throughout the years. I also thought the people I worked with during my time here were brilliant.
What particular activities interested you as a student?
I arrived on campus in 2021, and when the COVID-19 Omicron wave started a few months later, I joined the Student WorkForce [a team of medical and graduate students who took on vital non-medical roles in the Mount Sinai Health System to support physicians, staff members, researchers, and hospital operations]. I got involved in COVID-19 testing of staff. Just being part of that entire process and learning how a health system works was very insightful. It was great that Mount Sinai asked the student body to help out at a critical time, and the fact that students rose up and met those expectations was very inspiring.
I have also been involved in Story Time/Teen Talk in the Child and Adolescent Psychiatry Inpatient Unit at Mount Sinai Morningside. We played games with the children and had discussions with the teens to lift their spirits during their treatment. Being a part of that gave me the idea to introduce similar programs at other hospitals.
What’s next?
I’ll be attending medical school at the University of Central Florida College of Medicine. I’m keeping an open mind about my area of specialization. The field that intrigues me right now is neurology, but I don’t think I’ll actually know until I get to medical school. Whatever I decide, my goal is twofold—to help patients in the clinic and advance research.