The Interview

 

Janice: What led you to your current major?

Justin: In high school I was involved in the computer programming club. That was a jump start to my experience with programming. Later on, my school participated in the Cornell Tech hackathon for high school students and we had a speaker talk about autonomous robots. The speaker mentioned that they were offering an  internship, so afterwards I reached out to that speaker! Following that, I was a part of the Future Automation Research Lab, where I created a simulation of Roosevelt Island for Cornell Tech in the summer of my junior year. 

 

What are some fun facts about yourself?

 A fun fact about me is that I’m actually a 4th gen missionary from my mom’s side of my family.

 

How did you come across this research opportunity with Professor Tripathi?

My brother was studying Biotechnology at the time, and he really pushed for me to get into research. I decided to reach out to Professor Tripathi as I often went to his office hours to ask questions, so I felt familiar with him. Over break I reached out to him and I told him that I was interested in machine learning and asked if he had any research I could be involved in. That’s how we ended up collaborating in the summer in research. Professor Tripathi focuses more on data science and I focus more on machine learning, so together it went hand in hand. 

 

What do you think was the most important thing you learned from this research experience?

Definitely the importance of networking. I was able to do research all because I went to office hours to ask questions. Faculty office hours are often overlooked when there are plenty of opportunities like that.  

 

What was the IBM mini-sprint like? What do you think was the most interesting part of it?

Before research, this was my first time at this kind of event. The most interesting part would definitely be seeing people of all backgrounds come together. There would be people that never took anything related to Computer Science in college but they were still trying their best. It was interesting being able to see people from all sides of the world, at different skill levels to work on a complex project. 

 

What was it like contributing to the expert collaborative articles on LinkedIn? What did your role look like?

So how it works is LinkedIn will give me a prompt and as a collaborator, I will respond and add contributions to the article. Members can then react and almost “grade” me on my responses. From that, I ranked the top 2% of contributions and that is how I became a Top Voice in Machine Learning. 

 

Are there any resources from CEAS/Stony Brook that you’ve found useful when it comes to your involvement and projects?

I actually sought a lot of guidance from Tripathi. But other than that, there’s actually a professor from Stanford on YouTube, Andrew Ng. He has a 10 part series of lectures on YouTube which I watched. It really helped me understand machine learning outside of my linear algebra foundation. 

Looking on CEAS website also really helped as a starting place for finding topics of interest when getting into research. 

 

How do you think your involvement in these opportunities has shaped your goals?

The plan right now is to stay in software engineering. But I also love machine learning so I’ve been jumping back and forth between the two in terms of involvement. My involvement in these opportunities has definitely shown me the scope of Computer Science as I learn something new about it every time. This has also led me to a lot of self-learning, about what I want and what it is I am looking for in a job. 

 

Do you have any advice for those who are also looking to get involved in these kinds of experiences?

My first piece of advice would definitely be enhancing your LinkedIn. So not only do you work on your profile but you should also be staying active to grow. Commenting and responding are parts of that as well. There are opportunities everywhere. For example, I found out about the IBM mini-sprint I did through my LinkedIn feed. There are really opportunities everywhere.

My second piece of advice would be to not overlook the small things such as research and faculty. Like I mentioned before, I was able to get involved in research because I went to office hours and reached out to Professor Tripathi. There are experiences like that everywhere. 

 

What do you think helped you make the most of your experiences?

I think the biggest part would be forthcoming, always trying to learn, and be curious. I think it is also the feeling of someone being able to be recognized for your work, as it gets you the experience and the network.