USC Electrical Engineering Ph.D. Graduate Receives Prestigious Award

Joshua An | September 19, 2018

Longbo Huang recently received the 2018 ACM SIGMETRICS Rising Star Research Award

Longbo Huang, a 2011 USC Electrical Engineering Ph.D. graduate and current assistant professor at Tsinghua University in Beijing, has received the prestigious 2018 ACM SIGMETRICS Rising Star Research Award.

The award is given annually and recognizes a junior researcher who demonstrates outstanding potential for research in the field of computer and communication performance.

Huang, who has also earned Tsinghua University’s Distinguished Teaching Award, received the Rising Star Award because of his work in the field of stochastic network optimization, in particular, on investigating the fundamental benefits of online learning and prediction in network control. An example of this includes websites like Amazon being able to predict and pre-ship products users may purchase.. Video streaming apps are also similar in that they often preload videos so that users won’t have to wait through a buffering period. Essentially, Huang wants to understand how data and learning can impact algorithm design and performance in networks.

Huang hopes to increase the intelligence of existing systems by creating smarter algorithms. Because these algorithms can be applied to many different situations, Huang’s research is broad and interdisciplinary in nature.

“For me, I keep track of things by interacting with people in industry and colleagues, trying to understand what the real and important issues are and what they believe is important,” Huang said. “Then, I can sit down and try to create algorithms that can be used to optimize networks in the specific areas where I feel they are needed.”

Huang credits a large part of his research capabilities and passion to his time at USC. Working with advisors and other faculty, Huang believes that he wouldn’t achieve nearly as much without his time here.

“I’d really like to express my gratefulness to USC and thank my advisors and faculty that I met there, in particular, Michael Neely, Leana Golubchik and Bhaskar Krishnamachari.” Huang said. “They taught me how to become a mature researcher and how to do research.”

Huang hopes that his results are consistent in solving problems and if they can inspire others to create their own algorithms.

Huang said. “If I can come up with an actual product from my research, that’s great. If not, the important thing is that I can contribute something novel and impactful to the field.

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