Global Graduate: Shrikanth NC

Shrikanth N C, Doctorate from the College of Engineering

About Shrikanth

Shrikanth spent most of his early life in the southern state of India, Tamil Nadu. He received his engineering degree in 2008 and worked in the software engineering space for 9.5 years. He joined the Ph.D. program at NC State in 2017. He is currently a Ph.D. candidate (advised by Dr. Tim Menzies). His research interest lies in software engineering and machine learning.

How was your experience at NC State University?

2017 Fall | New place, no friends, generation gap, can’t cook and what should I be working on?
2018 Spring | Well, I think I have some idea. New friends start appearing.
2018 Fall |Trying to publish my research work and found my favorite coffee place.
2019 Spring | Nope, paper rejected! No worries, let me correct and re-submit the paper again and start to like local food.
2019 Fall | Paper Accepted! (best paper nominee) and cooking skills get better.
2020 Spring | Good grades and more research.
2020 Fall | Paper Accepted (research Track) and even more research.
2021 Spring | Paper Accepted (Journal) and Research Internship at Microsoft.
2021 Fall | Learns to drive in the U.S., writing my dissertation and final defense.

What would you say is your biggest accomplishment during your time at NC State?

Persistence.

What are your plans post-graduation?

Shrikanth is actively looking for research opportunities in the industry.

Do you have any advice for current or incoming international students?

Ph.D./MS (thesis): In my humble opinion doing the heavy lifting (research) early is critical to fail fast. Ideas (Objectives) will brew as you get acquainted with the research space by reading more papers. Always read a paper with a set objective. The objective could change as you read more papers, that is okay. Caveat: It is very easy to wander away in research. Hence, it helps to have periodic meetings with the advisor(s) to gauge your goal. Lastly, always stand on the shoulders of giants (greek metaphor) that could include your peers. In other words, much of the data, computer code, insights, etc are already available.