Opportunities

Graduate Students

We are interested in students who meet these criteria:

• Good attitute.

• Interested in imaging + learning:

  • The research I do is imaging + learning. This involves optics, sensors, and algorithms.

  • I expect incoming students have self-learned this course https://www.youtube.com/channel/UCf0WB91t8Ky6AuYcQV0CcLw

  • I encourage you to read Joseph Goodman's Introduction to Fourier Optics.

• Strong background in:

  • Linear algebra (MIT's 18.06, or Purdue's MA 511)

  • Probability and statistics (MIT's 18-05, or Purdue's ECE 302)

  • Convex optimization (Stanford EE 364a, or Purdue's ECE 647)

  • Machine learning theory (Caltech's Learning from Data, or Purdue's ECE 595)

• Adequate programming skills: PyTorch, TensorFlow.

• Independence: Can solve problems by yourself.

• Good English. Speaks well. Writes well.

If you are interested, please send Prof. Chan an email with the following items:

• Your resume / CV;

• Transcript;

• One representative paper. That could be a journal article, a conference paper or a project report.

• Tips: Read carefully about what we do in i2Lab, and convince us that you can contribute.
  

Undergraduate Research

• Good GPA: Our most recent undergraduates typically have GPA of 3.9 or above.

• Self-Motivated: Projects at i2Lab are open problems. We expect that you can learn things by yourself, and work independently.

If you are interested, please send Prof. Chan an email with the following items:

• Your resume / CV;

• Undergraduate transcript;