Mohamed Harmanani
Graduate Researcher, Deep Learning/Medical Imaging
Vector Institute, Toronto, Canada
Med-i Lab, Queen's University


I am a MSc candidate at Queen's University as well as a Research Assistant in the Medical Informatics (Med-i) laboratory, advised by Dr. Parvin Mousavi. My main research interests are in computer vision, deep learning, and medical imaging. More specifically, my research focuses on using deep learning to detect prostate cancer in real-time during ultrasound-guided biopsy procedures. I am a recipient of the Robert Sutherland Fellowship at Queen's and the NSERC MediCREATE training award.


MSc. in Artificial Intelligence, Queen's University

Advisor: Parvin Mousavi

2022 - Present
HBSc. in Computer Science & Philosophy, University of Toronto
2016 - 2021


Machine Learning Student Researcher, Vector Institute

2023 - Present

Graduate Research Assistant, Queen's University (with Parvin Mousavi on AI/ML for healthcare)

2022 - Present

Data Scientist, Flinks, Montréal (PyTorch, BERT, NLP)

2021 - 2022

Research Intern, University of Toronto (with Lisa Zhang on ML and NLP)


Research Assistant, University of Toronto (with Katharina Braeutigam on bioinformatics)

2020 - 2021

Software Engineer, Venngage, Toronto (TypeScript & React.js development)

2019 - 2020

Publications & Preprints

LensePro: Label Noise-Tolerant Prototype-Based Network for Improving Cancer Detection in Prostate Ultrasound with Limited Annotations
MNN. To, F. Fooladgar*, PFR. Wilson*, M. Harmanani*, M. Gilany, S. Sojoudi, A. Jamzad, S. Chang, P. Black,
P. Mousavi, P Abolmaesumi
Int J of Computer Assisted Radiology and Surgery (IJCARS), 2024
Towards Confident Prostate Cancer Detection using Ultrasound: A Multi-Center Study
PFR. Wilson, M. Harmanani, MNN. To, M. Gilany, A. Jamzad, F. Fooladgar, B. Wodlinger, P. Abolmaesumi, P. Mousavi
Int J of Computer Assisted Radiology and Surgery (IJCARS), 2024 (to appear)
Benchmarking Image Transformers for Prostate Cancer Detection from Ultrasound Data
M. Harmanani, PFR. Wilson, F. Fooladgar, A. Jamzad, M. Gilany, MNN. To, B. Wodlinger, P. Abolmaesumi, P. Mousavi
SPIE Medical Imaging 2024
Modelling the Spread of COVID-19 in Indoor Spaces using Probabilistic Automated Planning
M. Harmanani
ICAPS 2023 Scheduling and Planning Applications woRKshop (SPARK 2023)
Using Deep Learning to Localize Errors in Student Code Submissions
S. Fujimori, M. Harmanani, O. Siddiqui, and L. Zhang
ACM Technical Symposium on Computer Science Education (SIGCSE 2022)


W2024 Head Teaching Assistant, Algorithms I (CISC 365) at Queen's
F2023 Teaching Assistant, Neural & Genetic Computing (CISC 452) at Queen's
W2023 Teaching Assistant, Intro to Data Analytics (CISC 151) at Queen's

Honors & Awards

Vector Institute Research Grant
Awarded to Vector researchers to support research in AI/ML
NSERC MediCREATE Central Line Challenge, 2nd Place
Developed a deep learning model for (1) surgical tool detection and (2) task identification in surgical videos
Robert Sutherland Fellowship
Awarded to distinguished students at Queen's belonging to a minority group
NSERC MediCREATE Training Award
Awarded to students in the NSERC CREATE training program in medical informatics
University of Toronto Undergraduate Research Grant
Awarded to students in good academic standing to present at a conference
University of Toronto Maths & Computer Science Honour Roll
Awarded to students with a grade of 90% or greater in 3+ Math & Computer Science courses at the University of Toronto in 2020-2021
Excellence 300 Award in Philosophy
Awarded to the student with the highest mark in a 300-level Philosophy class
University of Toronto Entrance Award
Awarded to distinguished students admitted into the Faculty of Arts & Science


Programming Python, SQL, Java, R, TypeScript, C, C++, Haskell, Make
Frameworks PyTorch, scikit-learn, Keras, NumPy, Pandas, SciPy, TensorFlow, Seaborn, React, Node.js
Toolbox BigQuery, Google Dataflow, GCP, AWS (S3, SageMaker), Linux, DVC, vim, git, zsh, Jupyter

Last updated on 2024-04-15