Huijuan Shao, DAC Ph.D. alumnus and research scientist at Hitachi America, Ltd.

Since graduating in 2016 with a Ph.D. in computer science, Huijuan Shao has transitioned from academia to industry. For nine months, she was a research associate at George Washington University where she developed regular expression models with Java to extract clinical variables from cancer pathology reports and tuned queries performance in PostgreSQL when searching from 8TB national electronic health records. In January 2018, her career took another path. She and her family moved west, to Santa Clara, California, where she joined Hitachi America, Ltd., as a research scientist, focusing on industrial AI.

Was moving from a university to a corporation a big change for you? 

It was actually more like going back to the familiar. After I earned my master’s degree from the University of Chinese Academy of Sciences in Beijing, I worked for six and a half years as an associate senior researcher in Hitachi’s research and development department in Beijing so I was not new to the business world.

What attracted you to Virginia Tech and DAC?

Data mining led me to Virginia Tech and DAC. My research interests are machine learning in time series, natural language processing and deep learning and its applications in the domain of sustainability and healthcare. Within those interests is a strong focus on supervised and unsupervised learning algorithms related to times series in urban computing.

How did you wind up in the Washington, D.C., area?

I began my Ph.D. program in Blacksburg in January 2011 but moved to McLean, Virginia, in 2014 when my advisor, DAC Director Naren Ramakrishnan, moved to the center’s Arlington location

What was the most exciting research you engaged in while at DAC?

My most exciting work while a Ph.D. student was to implement temporal mining algorithms to help save energy for sustainability, and discover social network sensor groups to predict the spread of epidemics in cities.

How are you using now what you learned at DAC?

Predictive analysis in industrial AI – which is what I do in my current position — proposes new data mining algorithms and applies existing machine learning algorithms to industrial datasets. This is strongly related to what I learned while at DAC.

Reflecting on your own experience, what advice would you give to current Ph.D. students?

Work hard and closely with your advisor. In my case, Naren had the most impact on me while I was a DAC student because he is an expert in this research area. In addition to guiding my research, he encouraged me when I met difficulties. I learned that both research direction and spiritual encouragement are very important.

I understand that you were also raising children while earning your Ph.D. That couldn’t have been easy. 

My three children were born while I was a student at DAC. Elaine is seven now and the twins, Franklin and George, are around two. I am very grateful for the continuous support from my parents and my parents-in-law.

Any other advice for current DAC students?

Industry internships can be very helpful if that is where you are headed. When I joined Hitachi, I found that several colleagues were recruited very quickly because they had previously interned here.

With a full-time job and three young children to care for, you probably don’t have much spare time.  But what do you like to do for fun?

Of course I am busy. Usually I get up very early in the morning, then read some books, or run or go hiking with friends. Every Sunday morning I hike with other VT alumni here and we talk about work, career, health, family, kids, and so on. I really enjoy these two to three hours of precious time.