Portrait Photo

Yani Ioannou

Pronouns: He, Him


Assistant Professor

Schulich School of Engineering, Department of Electrical and Software Engineering

Contact information

Phone number

Office: 403.220.6144


Office: ICT248

For media enquiries, contact

Joe McFarland
Media Relations and Communications Specialist

Cell: +1.403.671.2710
Email: Joe.Mcfarland@ucalgary.ca

Preferred method of communication

How to Contact Me:

Undergraduate/Graduate Research Opportunities

Please see my supervisor profile for details on how to apply for these opportunities.

Research Collaborations

For research collaborations, please e-mail me directly.

I'm looking for...

Research partners

I have a wide-range of industry and academic research experience, and am always open to new collaborations, especially on projects which might help fund M.Sc. and PhD students (e.g. MITACs funding)


Educational Background

PhD Information Engineering, University of Cambridge, 2018

M.Sc. Computing, Queen's University (Kingston, Canada), 2010

B.Sc. Honours Computer Science, University of Toronto, 2006


I completed my PhD at the University of Cambridge in 2018, where I was supervised by Professor Roberto Cipolla and Dr. Antonio Criminisi. My PhD was supported by a Microsoft Research Ph.D. Scholarship and I collaborated with researchers at Microsoft Research Cambridge (UK) extensively. Following my PhD I was a Postdoctoral Research Fellow at the Vector Institute, working with Prof. Graham Taylor, and Prof. Mihai Nica, and before that a Visiting Researcher at Google Brain Toronto/AR Core.

Research Impact

In my PhD I made research contributions in structured sparsity for Convolutional Neural Networks (CNNs) that are now widely used in all modern deep learning architectures for computer vision. I also worked on pioneering work in understanding the difficulty of adversarial robustness, and some of the earliest work applying CNNs to brain tumour segmentation. More recently I worked with NASA/SETI on applying deep learning to exoplanet classification, the resulting method continues to be used in processing data from the Transiting Exoplanet Survey Satellite (TESS) space telescope.

Current Research Interests

My current research 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.

Industrial Research Experience

Outside of academia, I have a range of industrial research experience, including at Microsoft Research Cambridge (Intern/Business Guest), Google Brain Toronto (Visiting Resarcher), and a UK self-driving startup Wayve (Research Scientist). Outside of research, I've contributed to open source projects such as the Linux kernel and the Point Cloud Library (PCL).


Areas of Research

Sparse Neural Networks, Efficient Deep Learning, Machine Learning

My current research 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).

Participation in university strategic initiatives


Course number Course title Semester
SENG 401 Software Architecture Winter 2022, Winter 2023, Winter 2024
ENSF 444 Machine Learning Winter 2024


NASA Frontier Development Lab: Finding Exoplanets

In work featured at Google Cloud Next `19, published in Astrophysics Journal Letters and Astronomy & Astrophysics, I along with Dr. Michele Sasdelli mentored two planetary scientists, Dr. Megan Ansdell and Dr. Hugh Osborn in deep learning and computer vision towards improving methods to find exoplanets in data from the NASA Kepler and TESS missions


  • Outstanding Reviewer, Asian Conference on Computer Vision (ACCV). 2020
  • Student Travel Award, NeurIPS. 2016
  • Student Travel Award, International Conference on Learning Representations (ICLR). 2016
  • Student Travel Award, Microsoft Research. 2016
  • Microsoft Research PhD Scholarship, Microsoft Research. 2013
  • Amazon Research Award, Amazon. 2021
  • Early Career Research Excellence Award, Schulich School of Engineering - Electrical & Software awarded. 2023


More Information

For an up to date and full list of publications, see my Google Scholar Profile