Join the Lab

The Hawaii Digital Health Lab has several openings for PhD, masters, undergraduate, and high school students.

For current University of Hawaii PhD students: I am happy to serve as your PhD advisor if your research aligns with the Hawaii Digital Health Lab. RAships are available for select students. I currently like to work with students for about 1 year prior to making a decision about an RAship commitment. Usually, this is in the form of mentorship on your masters thesis for course credit (ICS 699 and/or ICS 700). Working together for only 1 semester or during the summer before making a commitment may be possible in exceptional circumstances. If you are a PhD student funded through other means (e.g., TAships, fellowships, GAships, etc) then that makes it much easier to accept you as a student. Send me an email with your resume/CV, a description of which of my previous papers interests you and why, and a few sentences about your "dream research project".

For prospective PhD students: The lab is not currently accepting new PhD students for the upcoming admissions cycle. Please check back in future cycles if you are interested.

For University of Hawaii masters students: Course credit is available in the form of ICS 499, ICS 699, or ICS 700. Note that masters students completing Plan A must complete 6 units of ICS 700 and masters students completing Plan B must complete 6 units of ICS 699. Send me an email with your resume/CV and which of the following skillsets you would like to contribute to the lab: web development, mobile development (iOS or Android), data analysis, and/or machine learning (TensorFlow/Keras or PyTorch).

For University of Hawaii undergraduate students: Course credit is available in the form of ICS 499 or for your honors thesis (HONS 496). In addition, I am actively accepting mentees for the Undergraduate Research Opportunities Program (UROP). If interested in receiving ICS 499 course credits and/or participating in the UROP program, send me an email with your resume/CV and which of the following skillsets you would like to contribute to the lab: web development, mobile development (iOS or Android), data analysis, data mining, and/or machine learning (TensorFlow/Keras or PyTorch).