General information about admission and funding

The general information about our graduate program (including admission, funding, etc) is available here. The information about tuition/fee is available from the Registrar's Office here. For the thesis-based program (MSc or PhD), you will need to find a supervisor before you can be admitted. This is different from some other schools where you can be admitted without a supervisor. Here at UManitoba, excellent incoming students can expect to receive funding from various sources (fellowship, research assistantship, teaching assistantship), see here for information. The funding decision is separate from admission and is decided on an individual basis. Please note that the application deadlines for many funding opportunities are significantly earlier than the admission (this is particularly true for many fundings that international students are eligible for). I strongly encourage you to plan your application as early as possible, and apply for all eligible fundings.

For prospective students (PhD or thesis-based MSc) interested in working with me

I am looking for self-motivated students interested in computer vision and/or machine learning. Interest/enthusiasm in research and good technical background (math, programming, CS and engineering is general) are required. For PhD applicants, research experience (preferably with published work) in computer vision and/or machine learning is usually required as well. To help me know more about your background, please send me the following items via email (PDF or plain text, or URL to a website containing these items).
  • A copy of your CV.
  • Transcripts (unofficial ones are sufficient) from ALL post-secondary institutions attended.
  • Up to three representative publications written in English if you have.
  • TOEFL/IELTS score when applicable (our department does not require GRE), or mention that you will take the test in the near future.
  • A brief description of your research interests, and your background in computer vision, machine learning, or related areas in AI and data science. This can be courses, projects, online courses/certificates (e.g. Coursera, Udacity).
  • Other information that you think might be relevant. For example, if you have a scholarship from your home country that can fund your grad studies at UManitoba, you can mention it.
Please put "GradApp" somewhere in the subject of your email, e.g. Subject: graduate research position in Computer Vision? (GradApp). This tells me that you have read this page. If you have followed these instructions and your email contains all the information requested above, rest assured that I will read your email. However, due to the large number of requests, I cannot respond to all of them. If I am interested in your application, I will reply within a week and start the conversation (and request more information from you if necessary). If you do not hear from me for more than one week, it means that I do not have a position for you -- in this case, please do not send me repeated emails, unless your profile has significantly improved, e.g. you get a new publication in a good venue.

The application process can be summarized as follows:
  • First make sure you meet the minimum requirement in terms of GPA and English requirement. You can assess your transcripts using the conversion charts found here.
  • Find a faculty member in the department who is willing to supervise you. Please refer to the information above if you want to contact me. If I am interested in you, I will reply and encourage you to apply. But this does not automatically mean that you are guaranteed to be admitted. You still need to formally apply for admission. The admission decision is made by the graduate admission committee and often depends on the pool of applications we receive in a given year.
  • Apply for admission to the program.
  • After getting admitted, apply for all eligible funding opportunities. If you receive a major funding award (e.g. UMGF), the amount is usually enough to cover the tuition and living expense. I may also provide RAship if you receive an award less than the UMGF amount (e.g. CS entrance award) or do not receive any award. It depends on the number/quality of students and the funding I have. Although the department has TA positions available, these positions are not guaranteed, and the amount you can get from TAship is fairly small. You can use TAship to supplement your income, but you certainly will not be able to fund your graduate studies using TAship alone.
Note that many funding applications require that a student has been accepted for admission to the program by both the Department of Computer Scienece and the Faculty of Graduate Studies. To ensure sufficent time for both, I strongly suggest prospective students to plan their applications as early as possible. For example, if you are applying for admission starting Fall 2017 (as an international student), ideally you should contact me before November 2016 and submit your complete application to FGS before December 15, 2016.

In addition to computer vision/machine learning, I may also be able to co-supervise students on applying machine learning in other areas (e.g. bioinformatics with Prof. Pingzhao Hu). Contact me for details if you are interested in this option.

Research requires commitment and mental focus. As a result, I usually do not supervise students who plan to do thesis-based graduate studies on a part-time basis.

I currently do not have funding for postdocs or visiting researchers. If you have your own funding from other sources (e.g. CSC scholarship in China) and would like to visit my lab, feel free to get in touch.

For undergraduate students at UManitoba

If you are an undergraduate student at UManitoba and would like to get involved in research with me (e.g. during the summer) or do an honours project in my group, please contact me directly (please attach your CV and transcript). I am particularly interested in students who have good background in both programming and math/stats (e.g. CS major with joint degree or minor in math, stats, physics). I strongly encourage you to apply for NSERC USRA and other fundings available (see here and here). Note that most of these funding applications require a minimum GPA of 3.5/4.5, but realistically speaking, you need a GPA close to 4.0/4.5 in order to be competitive. It will also be helpful if you have taken one or more courses in related areas, e.g. computer vision, image processing, machine learning, artificial intelligence, etc.

For undergraduate students outside of Canada

If you are from certain countries, you might consider applying through the MITACS Globalink Internship program, which funds you for an internship at a Canadian university in the summer. Typically you should apply in September of your 3rd year. I usually have 1-2 projects under the MITACS Globalink program every year. You can search for these projects and apply directly from the MITACS Globalink website. MITACS has its own screening and matching process, you do not need to contact me before applying. Unfortunately I do not have time to respond to individual inquiries regarding the internship. If there is anything (e.g. prior research experience, personal projects, etc.) that you would like me to know about, please include those information in your application materials, e.g. by putting a URL to your personal website or Github page in your CV. Once you are accepted to the program and matched to my project, I will provide you the relevant information and resources to help you get started on the project.

Other than MITACS Globalink, we do not have internship positions for undergraduate students outside of Canada and will not reply to unsolicited emails regarding internships.