“AI has infiltrated so many different aspects of everyone’s lives over the past few years, but seeing firsthand how it’s been able to make strides in virtually every field of science has been inspiring,” says Neeloy Bose.
Neeloy Bose, a first-year student in the Master of Biomedical Data Science and AI program at the Icahn School of Medicine at Mount Sinai, was already working in a laboratory and understood the importance of “Big Data.” But he concluded that in order to reach his goals, he had to learn more about how to process these large data sets himself, and how that can help researchers like him make discoveries that can improve health and help people.
In a Q&A, he describes how he decided to study at the Icahn School of Medicine and how that has helped him understand the value of studying data science.
Why did you decide to study at the Icahn School of Medicine at Mount Sinai?
The Icahn School of Medicine at Mount Sinai gives me the opportunity to access the resources of a world-renowned medical and academic institution while offering me the flexibility to continue my research externally. The program specifically offered me the flexibility to continue my master’s studies in a hybrid setting while I am also working at the New York Stem Cell Foundation, a non-profit research institute based in Manhattan. It’s an exciting time to work with these institutions while being able to see what I’m studying brought to life through real world applications in the field.
What attracted you to study Biomedical Data Science and AI? What inspires you?
Working at a high-throughput lab that harnesses the power of automated liquid handling robots, I’ve come to appreciate the process of casually creating terabytes of data. This has only made me more appreciative of the extractive and generative power of data science, especially using AI and machine learning tools. Being able to create “Big Data” as a biologist means that you need someone to be able to work with a humanly incomprehensible amount of information, and what could be better than learning how to do it yourself?
How do you think AI is going to impact Data Science moving forward?
AI has infiltrated so many different aspects of everyone’s lives over the past few years, but seeing firsthand how it’s been able to make strides in virtually every field of science has been inspiring. From high-content image analysis to looking for signatures of rare diseases to even creating tools to assist health care outcomes, the intersection of AI and science seems brighter than ever, and that can only increase the speed at which we make progress towards the greater good.
What are some of your achievements so far as a master’s student?
I’d say being a master’s student is an achievement enough at times, but being able to learn the cutting edge of new technologies and taking that knowledge to be able to apply it to real-world research is fascinating. It almost feels surreal at points to know that you’re always working to advance the future of the field.
What are your plans after you have completed your degree?
I hope to transition from more wet lab facing roles to better integrate computation into my research. With what I’ve learned and will continue to learn through the program, I hope to keep pushing forward what I’ve learned and thought to be the boundaries of what science is capable of. Being able to see my work improving the real-world prospects of patients and health care systems using this ever-evolving technology would be one of my greatest dreams that I think I’ll always be in pursuit of.