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.
  

Advice on Deep Learning: We are generally open to students with different background, e.g., physics major or mathematics major. However, we are NOT interested in applicants who only want to pursue deep learning applications. We like to recruit students who can analyze the network, develop theory, and have insights. Applicants who have demonstrated how to apply deep networks (e.g., LSTM, recurrent network, Mask-RCNN) to specific applications (e.g., recognizing pedestrians) are NOT our priority.

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;