Vishnu Komanduri - ECE PhD Student of the Month - March 2024
Vishnu Komanduri is a Ph.D. student in the Helen and John C. Hartman Department of Electrical & Computer Engineering at New Jersey Institute of Technology (NJIT) advised by Dr. Roberto Rojas-Cessa. His research focuses on network congestion control, and machine-learning-assisted network design.
What would you say that could be the next big thing in your area of research?
It looks like the next big thing in many areas, including mine is going to be artificial intelligence (AI), as I've noticed both academia and industry extensively focusing on this new hype. There are a wide variety of new machine learning methods that have been implemented to design faster and more efficient networks, and I think the number of technological applications will continue to increase for the foreseeable future.
You have taken a few non-ECE courses from the Computer Science department. What's your experience with those courses?
The Computer Science courses gave me a fresh perspective into the field of computing, and vastly expanded my technical skills. It was a truly rewarding experience when I came across problems in my research area that I was able to quickly resolve with this prior knowledge. Having the Lecture Slides and Class Notes as a reference was also a huge help in my day-to-day research.
In addition to the Ph.D. study, you also have experience from the industries. What do you think is a major difference between academic research and industrial R&D?
I believe a major difference between industrial R&D and academic research is the technological application. Industrial R&D is typically implementation-focused and works to enhance or design a specific product for commercial purposes. Academic research is a lot broader and more theoretical, which allows it to be applicable to a wider range of products or technologies over a longer term into the future. In academic research, we explore the unknown or untouched areas of technology, and this feeling of adventuring into an unknown world is what truly sets academic research apart from industrial R&D.