“You have to work every day at being the best you can be. It is a project that is never-ending.”
These are Raja Phanindra Chava’s own words — and his inspiration — as he pursues an M.S. in computer engineering.
“I believe that learning is a constant process throughout life to achieve excellence,” said Chava, “and it is my primary driving force.”
After graduating with a bachelor’s degree in electrical/electronic engineering from SASTRA University in India, Chava said he realized that undergraduate studies would not be enough for him.
“I wanted to do research where major innovations take place. Virginia Tech is one of the best graduate institutions for research in the field of deep learning and graphs and that is what brought me to the university and to DAC,” he said.
Deep learning — now being used successfully in many technological areas — has always been Chava’s area of interest and integrating deep learning with network comparison using neural networks is where he finds the potential to be particularly innovative. He credits his advisor, Srijan Sengupta, with helping to guide him through the right application and approach to his research.
“When given two or more graphs/networks, I am trying to find out the degree of similarity between them,” Chava said. “Social networking has become a major force in the contemporary world and networking is all about connections. If you look at connections between people in social networks from a research perspective, they are nothing but graphs with people as nodes and connection between them as edge. It would be great if we could compare connections between people from various social media networks.”
Chava’s goal is to work for a Fortune 500 company in a position that aligns to his research interests. His projected graduation is May 2019.