Ph.D. Student Recognized as eBay's 'Best of Class'-Silicon Valley Campus - Carnegie Mellon University

Ph.D. Student Recognized as eBay's 'Best of Class'

Internship experiences at prestigious Silicon Valley companies are an opportunity for Carnegie Mellon University students at the Silicon Valley campus to apply their classroom knowledge to real-world problems. This summer, Priya Sundararajan, a Ph.D. student in Electrical and Computer Engineering at Carnegie Mellon Silicon Valley came away from an internship at eBay with not only industry experience but bragging rights as well, winning a Best of Class award.

At InternPalooza, an intern showcase at which 70 Marketplace eBay interns showcased their summer projects and research, Data Visualization Analyst intern Sundararajan emerged as the cream of the crop with their project, “User Behavior Visualization.” Their project focuses on developing new visualization techniques for tracking user behavior on the eBay website and was developed as part of the Analytic Platform & Delivery (APFD) team.

“I was fortunate to intern at eBay and learn about the current tools and technologies used there and developed by my fellow interns,” said Sundararajan. “During this event, I’m thrilled that my project received much attention because I realized that people are in need of such visual and analytical techniques.”

At Carnegie Mellon University in Silicon Valley, Sundararajan’s research focuses on creating new visualization techniques for exploring large or complex data. Along with faculty advisors, Associate Research Professor Dr. Ole J. Menghshoel and Distinguished Service Professor Dr. Ted Selker, she has developed a multi-focus technique to help users zoom and study multiple regions of a large network simultaneously. They have applied this technique to fault diagnosis in an electrical power network.

“I’m very proud of Priya and the great work she did at eBay,” said Dr. Mengshoel. “Her Ph.D. research on combining visualization and analytics is very timely and important now that more and more organizations see the need for better software tools to help them tap into the potential of their Big Data.”