Interested in joining the group? Please read through the FAQ below before emailing. It covers the questions I receive most often about admissions, funding, and collaboration.
Frequently Asked Questions
Are you recruiting new students?
I am always looking for outstanding Ph.D. students who are passionate about machine learning research. The number of new students I can advise each year depends on current group size and funding, but I typically recruit one or two new Ph.D. students. I rarely have funding for M.S. students, though I am happy to advise research projects or theses for students who have taken my courses and demonstrated strong performance.
What are my chances of admission?
If you are serious about working with me, submit an application to the Computer and Information Science graduate program and list my name as a potential advisor. I review every application that mentions me. Successful applicants typically demonstrate:
- Solid preparation in mathematics, probability, and machine learning
- Strong programming and experimental skills
- Clear, concise technical writing
- Prior research experience or publications
Admission decisions also depend on how well your interests match ongoing projects and the overall strength of the applicant pool.
Do you have funding for students?
Almost all Ph.D. students in the department are supported as teaching or research assistants, which includes tuition and a stipend. I try to fund my Ph.D. students as research assistants whenever possible so they can focus on research, though most students spend one or two years as TAs during their degree. Funding for M.S. students is limited and unpredictable.
I’m already at the University of Oregon. Can I work with you?
Probably! Send me an email and attend a research group meeting. You will meet current students, learn about open projects, and see how you might contribute. Many students get started by helping with data preparation, feature design, or experimental evaluation. If you want to design new algorithms and publish in top venues, plan to take one of my courses (for example CIS 472/572: Machine Learning), do well, and budget substantial time—original research is demanding and iterative.
How can I get a response to my email?
Send a personalized note that explains who you are, why you are interested in our work, and what you hope to accomplish. Copying text from my website or publications is not helpful. Mention the word “moose” in the subject line so I know you read this page. If you do not hear back within a few days, feel free to send a polite follow-up.