CMDA Student Experience - Aanish Pradhan '24

My name is Aanish Pradhan. I'm a senior majoring in computational modeling and data analytics. I'm going to be graduating in spring 2024, and I'm minoring in computer science, math and statistics. Originally, I was not a CMDA major. I wanted to -- I came to Virginia Tech for neuroscience and I wanted to go to med school. At the suggestion of my dad, I took a computer science class and surprisingly I liked it. It was a bit of a challenge, it was something different than what I had ever done before. At the same time, I was also taking a statistics class that was needed for my major. And I liked the two of them, and I said, you know, is it possible if I could combine these somehow. And lo and behold, I came across what data science was, and one thing led to the next. I discovered what CMDA was. I talked to the advisors, I looked into the program, looked at the opportunities, looked at past testimonials from students. And I switched in and it's the best decision, you know, I've ever made, if I had a chance to do college again from the start, I would have definitely been a CMDA major. The best way I could describe what CMDA has done for me is it's allowed me to become basically a Swiss Army knife. I can I can I can work in really any field that I want to. It's like, if I want to go off and work in biostatistics, I can go work in biostatistics. If I want to go work in some physics or engineering discipline, I can do that. If I want to go work on Wall Street as a quant, I can go do that. And it's really anything that I want to do. So for example, for about a year, I did research with the Department of Biochemistry. I was working on a computational biochemistry project where we were studying the protein -- we're studying the mechanics of a particular protein that's implicated in a variety of cancers. And so we researched this protein using artificial intelligence based protein folding software. This past summer for my summer internship, I was originally hired as a digital signal processing intern, studying basically communication methods for unmanned aerial vehicles that communicated via the cellular network. In addition to that, I was also -- I worked on a machine learning project to basically classify encrypted data transmissions. And then my third project in my internship was a high performance computing project, basically accelerate some old signal processing software. My capstone project was in environmental data science, where we're working on improving the locality of weather forecasts from the National Oceanic and Atmospheric Administration for the purpose of improved water quality forecasting. So I think really what it's done for me is just I've been allowed to jump from domain to domain. So as I gain an interest in something else, I can go work there. So, you know, several years down the line, if I've gained an interest in sports analytics, I can go jump into sports analytics. So it's really allowed me to be extremely versatile and an extremely agile data scientist, which is I think one of the most critical skills that any data scientist in today's world should have. They should be domain agnostic. I just want to say, you know, thank you to everyone who works for the CMDA program. The last couple of years have just been from an educational perspective, just absolutely amazing. There's so much to learn and CMDA has given me the footing to basically go and pursue each of these individual domains at a greater depth at my choosing. So I think they've made me a versatile addition to any team that I might work with in the future.