Ph.D. student gains real-world research experience

Linh Le

With an undergraduate engineer degree focusing on computer network and telecommunication and a Master of Science in information systems, Linh Le, Ph.D. student in the Analytics and Data Science Institute, came to Kennesaw State University looking for ways to design and build systems and apply big data and data mining science research. This led him to a working as a graduate research assistant for the Center for Statistics and Analytical Research (CSAR).

“My work for CSAR is mainly to do research for the center’s clients,” Le explained. “Some of the projects are determining statistical differences between people with and without incontinent (mostly among the elderly), building predictive models for future sales of a company, and clustering customers of a company based on their purchases. I was also helping tutor the students for a semester or so.”

Continuing his love for research, Le joined the research-funded Equifax Data Science Research Lab. Housed in the Center for Statistics and Analytical Research, the lab’s mission is to investigate business challenges and opportunities created by non-traditional sources and types of data, with the overarching objective to improve Equifax’s customer experience, using cutting-edge techniques and methodologies to achieve their goals.

Le is working to develop a facial recognition system. Although the information available on the lab’s research is confidential, he was able to explain a little about his research, “It is a facial recognition system using deep learning. In other words, it receives a facial image and tell you who is in the image.”

“I (want to) think that our work on a biometric verification system using deep learning attracted their [Equifax’s] interests, and they decided to extend the fund to longer term,” Le added.

Le is using his research from CSAR and the Equifax lab to aid him with achieving his goals for after graduation. “My degree requires research in analytical problems, for example, building a model to predict the outcomes based on some inputs or clustering objects into similar groups based on their information, and so on,” he explained. “All the researches provide me with more experiences and insights of working with analytical models, and of course, this is important for any data scientist. I believe, at the moment, I can look at a problem and come up with the solution within a reasonable amount of time.”

With this real-world experience, Le hopes to continue his involvement in higher education but as a professor rather than a student. “I have some experiences in doing research and enjoy doing so. So I’m hoping to become a professor in some university to continue my research works,” he said. “I think I can also contribute if working in industry, since I have acquired a good understanding of analytics, including both statistics, machine learning and deep learning.

For any graduate students wanting to follow in Le’s footsteps, he offers this: “My advice would be to try to grasp the basic as soon as possible and then spend time catching up with the latest technologies. Data science is probably among the fastest evolving fields, especially machine learning and deep learning. It is highly important for you to keep yourself the most up-to-date.”

To learn more about CSAR or the Equifax Research Lab, visit

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