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Yijun Zhao

Part-Time Lecturer

Contact

Office Location

440 Huntington Avenue
462 West Village H
Boston, MA 02115

Mailing Address

Northeastern University
ATTN: Yijun Zhao, 301 ME
360 Huntington Avenue
Boston, MA 02115

Education

  • PhD in Computer Science, Tufts University
  • MS in Computer Science, University of Kansas
  • BS in Computer Science, Tianjin University

Biography

Dr. Zhao’s research interests include machine learning, data mining and statistical pattern recognition. In collaboration with industrial leaders, she has applied Machine Learning methods to detect brain abnormalities occurring in neurological disorders such as Epilepsy, and predict disease course in Multiple Sclerosis patients. At Northeastern, Dr. Zhao has been teaching a popular course, CS6220 Data Mining Techniques, which offers a comprehensive set of methods data scientists strive to have in their toolkits. Dr. Zhao has also taught Computer Science courses at Fordham University in New York.

Prior to embarking on her academic career, Dr. Zhao worked in the financial industry for over 10 years in a wide variety of roles, starting as a consultant at Coopers & Lybrand (now PricewaterCoopers), a senior quantitative analyst at Wachovia Securities (now Wells Fargo Advisors), and ending as a quantitative trader at hedge funds Millennium Partners and Ronin Capital.

What are the specifics of your educational background?

Dr. Zhao received her PhD degree in Computer Science from Tufts University, her MS degree in Computer Science from the University of Kansas and her BS degree in Computer Science from Tianjin University.

What are your research interests?

Over the last decade, technical developments and the emergence of large amounts of data have created a fertile environment for machine learning. Various applications that integrate automated learning and reasoning are pervasive in our daily life. I am excited to have the opportunity to conduct research in the medical field where machine learning has been used to help diagnose and treat incurable diseases. Given its vast domain of applications, machine learning would continue to be the focus of my research.