Gang Chen ('12) - Software Development Engineer, A9.com

Gang

Gang Chen is a 2012 PhD graduate currently working as a research orientated software development engineer for A9.com in Silicon Valley. A9 is an Amazon company located in Palo Alto, California that manages search and advertising technologies for Amazon and other clients. If you've done a search on Amazon, you've used A9's search engine. 

What is your favorite part about your current occupation/position? How did you get to where you are now?

I am excited that there are a lot challenge problems raising from the large volume of unstructured and noisy data in computational advertisement field, and there are also a lot of unique problems to be solved in Amazon.

I began my career at Zhejiang University, where I earned a Bachelor degree in Computer Science in 2005. I then earned my Master degree in Computer Science from Shanghai Jiao Tong University, in 2008.  After that I decided to learning more statistics knowledge, I earned my PhD in Statistics from the University of Illinois at Urbana Champaign in May 2012.  After graduation, as Neustar’s first data scientist, I work on marketing and user targeting problems using statistical analysis and data mining based on big data. I then worked for a mobile analytical company called Apsalar, built the company’s first Data Management platform for improving mobile advertisement performance. In 2015, I moved to Silicon Valley and join Samsung’s SmartTV advertisement platform team and help built and launched company’s first Smart TV advertisement platform. Currently, I work as a research oriented software development engineer in A9, working on various challenge computation advertising problems for Amazon. 

After graduation, I try to keep working in one area (online advertising) in order to learn more domain knowledge, and explore deeper on how can I apply my statistical skills in that area.

What aspects of your education as a statistics student have been most beneficial to your career?

I have gained solid fundamental knowledge of statistics from continues in-depth statistics courses, and attended various lab sessions to practice statistical analysis methods and programming skills. All the courses and research work help me build a solid foundation for continues learning new machine learning and deep learning algorithms that can be applied to solve complex problem form work.

What advice would you give to current statistics students about the professional realm?

I would say, find one or two industry areas that interested, look for the statistical applications/use cases on that area, then be more motivated to study statistical theory in order to solve real world problem in a statistical correctly and elegantly way. Meanwhile, always do more practicing on programing, not only know how to call statistical package but also able to implement statistical algorithms and build them in a good shape that can be used by other people.

What did you enjoy about being a Statistics student at the University of Illinois?

I feel lucky as Statistics student that our department has many knowledgeable professors can help mentoring in various research fields, as well as a lot of cross-disciplinary research collaboration with other departments.

'12 - PhD in Statistics

 

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