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Chengguang Xu

PhD Student

Contact

Office Location

440 Huntington Avenue
310 West Village H
Boston, MA 02115

BIOGRAPHY

Chengguang Xu is a PhD student studying machine learning and computer vision at Northeastern University in the College of Social Sciences and Humanities, advised by Professor Ehsan Elhamifar. He earned his Bachelor of Engineering and Master of Science from Nankai University in China. His main fields of research are Machine Learning and Computer Vision, and he is interested in combining the two to create complex learning algorithms that can process and solve specific issues in the outside world, and in creating learning algorithms and models that are both highly accurate and theoretically explicable.

EDUCATION

  • MS, Nankai University – China
  • BEng, Nankai University – China

About Me

  • Hometown: China
  • Field of Study: Machine Learning and Computer Vision
  • PhD Advisors: Ehsan Elhamifar

What are the specifics of your graduate education (thus far)?

I am going to pursue my PhD degree in Computer Science under the guidance of Professor Ehsan Elhamifar.

What are your research interests?

I am very interested in computer vision and machine learning algorithms. In my view, computer vision methods provide the machines (such as computers) with effective ways of perceiving the outside world. At the same time, machine learning algorithms equip them with intelligence of solving specific issues. By combining the algorithms in the two fields, we can design some really cool systems, such as face recognition system, object recognition system or even a self-driving system. After some applied research during my master’s study, I would like to delve into theoretical truth of some state-of-art learning algorithms such as deep learning.

What’s one problem you’d like to solve with your research/work?

As we all know, highly complex learning algorithms such as deep learning can achieve outstanding accuracy. However, their great properties are usually theoretically inexplicable. Therefore, I am aiming for designing learning algorithms or models that are both accurate and theoretically explicable.

What aspect of what you do is most interesting?

In my opinion, the uncertainty of the scientific research is the most fascinating part. Briefly speaking, I am curious about the unknown things and would like to explore the truth no matter how challenging the process will be.

What are your research or career goals, going forward?

I would like to be a researcher who can do some contributions to his field, maybe a professor in the university or a scientist in the company. I believe it will be a happy thing that one can do something one really likes.