Yani Ioannou, PhD

PhD, University of Cambridge, Cambridge, United Kingdom
MSc, Queen's University, Kingston, ON
BSc (Honours), University of Toronto, Toronto, ON

Portrait Photo

Areas of Research

Sparse Neural Networks, Efficient Deep Learning, Deep Learning, Machine Learning, Artificial Intelligence
My research area of focus is on unstructured sparse training of deep neural networks, and efficient deep learning more generally, with a focus on problems in computer vision in particular.
Computer Vision, Artificial Intelligence
I have worked on many computer vision applications such as conditional imitation learning for self-driving vehicles, medical imaging (brain tumour segmentation), 3D computer vision (point cloud segmentation), assistive technology (fall detection), and even exoplanet classification.

Supervising degrees

Electrical and Computer Engineering - Doctoral: Accepting Inquiries
Electrical and Computer Engineering - Masters: Seeking Students

Working with this supervisor

Who should apply?

Minimum Requirements for Graduate Admission

Prospective applicants must meet the minimum requirements for graduate studies and the admission requirements for the Electrical and Software Engineering program. I'm unable to waive these requirements, so prospective students should confirm they meet the requirements before contacting me.

Prospective Undergraduate Research Students

  • I look for 1-2 undergraduate research students every year (for up to 3 months over the summer) to engage with graduate students and myself in research projects, it's a great way to gain some research experience in your undergraduate degree, and goes a long ways towards improving your resume for graduate applications!
  • Interested undergraduate students should consider applying for the PURE awards (typical deadline is beginning of February)
  • Applicants should contact me by mid-January at the latest in order to apply for the PURE award or similar funding.
  • Must be enrolled in a relevant undergraduate degree at the University of Calgary, and 2nd year or above at the time of the research (Engineering/Computer Science, Mathematics, Physical Sciences or a related field).
  • Should ideally have an interest in pursuing a research career (in industry or academia).
  • Demonstrated experience programming, especially with Python.
  • Those from under-represented groups in particular are greatly encouraged to apply.

Prospective MSc Students (2 year degree)

  • Must meet the minimum requirements for admission (see above).
  • A background in Engineering/Computer Science, Mathematics, Physical Sciences or a related field.
  • Demonstrated experience programming with Python.
  • Ideally experience training models using a deep learning framework such as PyTorch.
  • Experience with research as an undergraduate research assistant or otherwise is highly valued.
  • Those from under-represented groups in particular are greatly encouraged to apply.

Prospective PhD students (4 year degree)

  • Must meet the minimum requirements for admission (see above), have completed, or will soon complete, a MSc or equivalent thesis-based degree program.
  • Experience training models using a deep learning framework such as PyTorch, and implementing research ideas in such a framework.
  • Demonstrated research experience with at least one publication in the field of machine learning, computer vision or another related field or significant industry experience with deep neural networks, and a demonstrated industrial impact.
  • Those from under-represented groups in particular are greatly encouraged to apply.

Postdoctoral Fellows

  • Have recently completed (or will in the near future) a PhD within the past 3 years. There are a number of fellowship opportunities available for such positions that come on a rolling basis, and interested candidates should inquire directly with me on any current fellowships. 

Self-Funded Students & Scholarships

The availability displayed above is based on my currently available funding awarded for research projects I'm pursuing. Prospective students are encouraged to apply to the many available funding/scholarship opportunities available at the University of Calgary. Students with a fellowship or funding of their own may be accepted/considered regardless of the stated availability above, and should contact me at any time.

How to most effectively contact me about an available position

I receive many e-mails from prospective students, many more than I can effectively respond to in a workday. If you do not receive a response from me please do not be offended - I only respond to e-mails for applicants I'm interested in potentially accepting. Unfortunately most of the e-mails I receive are from people who do not satisfy the requirements listed above, or have not explained well why they are interested in pursuing a 2-5 year graduate degree with me, and I'm unlikely to respond to these.

You can best ensure I respond to your e-mail by sending me an e-mail to my university e-mail address (click the following links for an undergraduate applicant or graduate applicant respectively to e-mail me with the subject "undergraduate applicant" or "graduate applicant"), and with the following content:

  1. Specify which position you are interested in.
  2. Verify you meet the minimum requirements (see above).
  3. Show me that your background/experience matches/exceeds the experience I expect (as listed above) for the potential degree you are applying for, by referring to relevant experience demonstrated in open-source code (e.g. on GitHub) and publications.
  4. State your earliest possible start date, and the expected completion date of your current degree if applicable.
  5. Attach an up-to-date CV/Resume.
  6. For graduate positions, attach a brief statement (maximum one page + bibliography) about what interests you in the research area of machine learning/computer vision in general. If you are self-funded PhD student, state what research agenda you would ideally want to pursue.

This brief statement (for graduate applicants) is so that I can better understand your motivations for pursuing a graduate degree. There are no right or wrong answers, and you don’t have to be interested in what I am specifically. In fact regurgitating/rewording something I’ve written online, or just copying the title of one of my papers is a bad way to go, I’m much more interested in seeing your independence and self-motivation!