Meet ML@GT: What Yao Xie Has Learned On Her Journey to Becoming a Successful Professor and Mother

At the Machine Learning Center at Georgia Tech (ML@GT), we’re lucky to have over 150 faculty members affiliated with our mission. With faculty from all six colleges on Georgia Tech’s campus plus several from Georgia Tech Research Institute (GTRI) and the Enterprise Innovation Institute (EI2), our professors bring a broad range of skills and areas of expertise.

Yao Xie is no exception. Xie is an associate professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) and an associate director of ML@GT. She is also an adjunct professor in the School of Electrical and Computer Engineering (ECE) and is the Harold R. and Mary Anne Nash Early Career Professor.

Some of Xie’s recent work partnered her with the Atlanta Police Department to help the department implement her zone redistricting design. This redesign allows police officers to respond to incidents more quickly and efficiently.

Xie is passionate about statistics and machine learning and makes balancing a successful career while raising a young family look effortless. Always ready to lend a helping hand, Xie shares her journey so far, what she has learned along the way, and more.

Tell us about yourself.

Besides teaching, I enjoy art in the form of painting and sculpture, music (especially Chopin), and going to concerts and museums. I also enjoy Zumba, yoga, and pilates, browsing T.J. Maxx for treasures, and practicing piano (baby-steps). Recently, I’ve started to read about history before bed-time. It’s fun to sometimes end the day with making a discovery!

I always feel so fortunate to work with my great mentors, all of whom are shining-star scholars with incredible intellectual power. After I obtained my undergraduate degree from the University of Science and Technology of China, I came to the United States to attend graduate school, like many international students.

I first worked on medical imaging and MIMO radar with Dr. Jian Li at the University of Florida. I later moved and received my Ph.D. from Stanford University in electrical engineering with a minor in mathematics under the guidance of Dr. David Siegmund and Dr. Andrea Goldsmith.

After that, I spent a year and a half at Duke University, working as a research scientist with Dr. Rebecca Willett and Dr. Robert Calderbank. They helped me to become who I am now.

Tell us about your research and why it interests you.

My research focuses on sequential statistical analysis with various applications, primarily in signal processing and sensor networks. In the past few years, I have been focusing on the problem of subsequent change-point detection and real-time anomaly detection. This naturally leads me to work on problems at the intersection of statistics and optimization, such as distributional robust testing and classification, adversarial learning, and network data analysis.

Those problems usually lie at the foundation of machine learning and I believe it is important to work on them, to gain statistical insights, and develop efficient new algorithms to harvest knowledge from the massive amount of data.

What drew you to your field of study and to be a professor?

I have had a vast interest in computer programming and coding since I was first introduced to it in 3rd grade. That was in the early 90’s and I still remember coding using the BASIC language on the early generation Apple’s mac computer with a green screen, implementing double FOR loops to draw a triangle using *.

I was good at it and I ended up participating in coding and algorithm competitions up to high-school when I was selected to participate in the National Olympia of Informatics in China. During that time, I was fascinated by the magic of algorithms: solving the shortest path problems, Hanoi, even playing the chess game. My curiosity has never faded in teaching computer “tricks” or algorithms, especially involving data.

I realized that to model data, we need statistics and probability, and to solve a problem, we often need optimization. Therefore, I have been passionately learning about these subjects. I guess this passionate thirst for knowledge naturally led me to become a professor because now I get to pursue research in statistics and machine learning for the rest of my life.


What has been the biggest challenge about being a professor?

For me, the biggest challenge of being a professor has been keeping a work-life balance. I did not realize that before having kids and a family, I had all the time in the world. Now my kids (Jolene, 5, and Jeremiah, 3) control all of my time. But I never regret it because not only do they teach me how to be efficient, but they actually keep me inspired and my life more balanced. I also have to give a shout out to my loving and forgiving husband who makes managing these challenges easier.

Why did you choose Georgia Tech?

I did not choose Georgia Tech, but Georgia Tech chose me. In retrospect, it was probably one of the best moves that I have ever made. It’s a fantastic environment with smart, energetic students and brilliant colleagues, which helps me to become a more mature researcher and teacher. The supportive environment at Georgia Tech has also nurtured my leadership. I have learned and grown a lot at Georgia Tech since arriving at Tech in 2013.

What do you enjoy about machine learning and being affiliated with ML@GT?

I love attending ML@GT seminars by leading researchers in both academia and industry. I have also really enjoyed the opportunity to work with Ph.D. ML students and other students who are interested in machine learning research.

ML@GT also forms a crucial bridge between my research and industry partners. For instance, one of my funded projects that was initiated by ML@GT has allowed me to collaborate with Macy’s Technology and develop anomaly detection for their shopping systems.

What is some advice you would give to someone looking to go into academia as a career?

My humble advice would be find your passion and follow your heart. Talk to many people who are currently in academia to get an idea about the profession and disillusion yourself. We all have different aspirations, but if you truly love research, it’s worth a try. Don’t forget your curiosity and that “fire” in you once you are further down the path.

What is your proudest accomplishment so far?

My proudest accomplishments so far, no doubt, are my two precious little children (both of them are born during my tenure-track years). And I am happy that meanwhile, I am able to maintain a highly rewarding career and receive my tenure.


Tell us something about you that would surprise us.

Not sure if this would be surprising, but I have been a disciplined dancer for ballet, Chinese dance, and Jazz, etc.. I continue practicing whenever I can.

What is something you wish you knew at the beginning of your career that you know now?

I wish I had known that “One should not lose your heart even in the downturn and rejection.” It’s a lesson I’ve learned over the years, but it would have been a big help years ago.

Why do you think embodying Georgia Tech’s motto of “progress and service” is important, especially in regards to artificial intelligence and machine learning?

AI and ML are becoming extremely important in society, and everyone is talking about it and asking questions about it. Whether I am teaching a class, attending a conference, meeting people in the industry, or just chatting with my Lyft driver, I believe that as a Georgia Tech ML researcher, it’s our service and our mission to society to disseminate knowledge in a way that everyone can comprehend it. We need to be fostering discussions that will lead to wisdom.

With this in mind, I have been teaching online courses, giving lectures and talks, and speaking outreach activities and trying to live out the phrase, “Being the salt and light in the world.”

Connect with Yao at

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