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Bio Summary:
Education:
Assist Prof Dr. Mahdi S. Hosseini has an extensive educational background with a focus on image processing, applied mathematics, and electrical and computer engineering. Here is a summary of his academic journey:
Ph.D., University of Toronto, Toronto, ON, Canada (2016)
- Field: Image Processing, Applied Mathematics, ECE Department
- Thesis: Finite Difference Methods in Imaging and Inverse Problems
- Advisor: Professor Konstantinos N. Plataniotis
M.Sc., University of Waterloo, Waterloo, ON, Canada (2010)
- Field: Compressed Sensing, Image Processing, ECE Department
- Advisors: Professor Ravi Mazumdar, Professor Oleg Michailovich
M.Sc., University of Tehran, Tehran, Iran (2007)
- Field: Machine Learning, Pattern Recognition, ECE Department
- Advisors: Professor Babak N. Araabi and Professor Hamid Soltanian-Zadeh
B.Sc., University of Tabriz, Tabriz, Iran (2004)
- Field: Control/Communications Engineering, ECE Department
- Honor: CUM LAUDE, WITH HONORS
- Advisor: Professor Sohrab Khan-Mohammadi
Professional Experience:
Assist Prof Dr. Mahdi S. Hosseini has accumulated valuable professional experience in academia and research. Here is a summary of his previous professional roles:
Assistant Professor, University of New Brunswick: Fredericton, NB, Canada (October 2020 – May 2022)
- Tenure-track position in the ECE Department
Multimedia Lab, University of Toronto: Toronto, ON, Canada (Jan 2016 – Sep 2020)
- Postdoctoral Researcher (Supervised by Professor Konstantinos N. Plataniotis)
- Research Topic: Theoretical Developments of Deep Learning and Computer Vision Algorithms
Huron Digital Pathology AI Research: Waterloo, ON, Canada (May 2015 – September 2020)
- Research Scientist (Industrial Advisor: Dr. Savvas Damaskinos, CTO)
- Research Topic: Digital Pathology and Computational Pathology
Singspiel Inc.: Toronto, ON, Canada (May 2013 – April 2015)
- AI Research Consultant
- Research Topic: Mono and polyphonic piano notes detection and recognition
These roles reflect Dr. Hosseini’s contributions to both academic institutions and industry, showcasing his expertise in areas such as deep learning, computer vision algorithms, digital pathology, and artificial intelligence research.
Honors and Awards:
Assist Prof Dr. Mahdi S. Hosseini has received numerous honors and awards throughout his academic and research career, recognizing his outstanding contributions and achievements. Here is a list of his notable honors and awards:
Gina Cody Research and Innovation Fellow: 2024-2025
NSERC-Discovery Grant (DG): Early Career Research (ECR) Award: April 2022 – March 2027
MITACS-Elevate Postdoctoral Fellowship: Ontario government research funding award, September 2019 – August 2021
NSERC Postdoctoral Fellowship: NSERC research funding award, June 2016 – May 2018
International Scanner Contest 2016: 13th European Digital Pathology Congress, Validated Versatility Award for designing image deblurring algorithms with Huron’s team, improving image quality for clinical and research applications
MITACS-Accelerate Research Internship: Research studentship award at Huron Digital Pathology, May 2015 – August 2015
Diploma of Teaching Higher Education (THE500): University of Toronto, 2014 – Completed a full semester graduate course
Ontario Center of Excellence (OCE) Internship: Research studentship award at Singspiel, January 2013 – August 2013
Graduate Research Scholarship Award: University of Toronto, 2010-2014
Graduate Research Scholarship Award: University of Waterloo, 2008-2010
Top 10% High-Scoring Reviewing Award: NeurIPS 2020 Conference on Neural Information Processing Systems
Top 5% Student Paper Award: European Signal Processing Conference (EUSIPCO) 2009, Glasgow, UK
Top 10 Student Paper Award: International Conference in Biometrics (ICB) 2007, Seoul, Korea
M.Sc. Full Scholarship Award: Awarded by the Iranian Ministry of Education to study at the University of Tehran
B.Sc. Student Graduation Award: 3rd rank in 120 undergraduate students in the 2004 convocation
B.Sc. Full Scholarship Award: Awarded by the Iranian Ministry of Education to study at the University of Tabriz
Research Interests:
Assist Prof Dr. Mahdi S. Hosseini has a diverse range of research interests spanning multiple domains. Here are his primary areas of focus:
Computer Vision:
- Self-supervised learning
- Deep metric learning
- Lightweight architecture design
- eXplainable deep training
Computational Pathology:
- Cancer diagnostics
- Foundational modeling
- Biomarker discovery
Numerical Methods:
- Numerical difference methods
- Signal/image processing
- Computational imaging
- Convolutional filters
These research interests demonstrate Dr. Hosseini’s involvement in cutting-edge technologies and methodologies, particularly in the fields of computer vision, computational pathology, and numerical methods. His work in these areas contributes to advancements in fields crucial to medical diagnostics, imaging, and artificial intelligence.
Publications Top Noted & Contributions:
Focuslitenn: High efficiency focus quality assessment for digital pathology
- Authors: Z Wang, MS Hosseini, A Miles, KN Plataniotis, Z Wang
- Conference: International Conference on Medical Image Computing and Computer-Assisted (MICCAI), 2020
- Citation Count: 14
On Transferability of Histological Tissue Labels in Computational Pathology
- Authors: MS Hosseini, L Chan, Y Wang, D Hasan, C Rowsell, S Damaskinos, et al.
- Conference: European Conference on Computer Vision (ECCV), 2020
- Citation Count: 12
HistoKT: Cross Knowledge Transfer in Computational Pathology
- Authors: R Zhang, J Zhu, S Yang, MS Hosseini, A Genovese, L Chen, C Rowsell, et al.
- Conference: IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP), 2022
- Citation Count: 11
Reconsidering CO2 Emissions from Computer Vision
- Authors: A Fu, MS Hosseini, KN Plataniotis
- Conference: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
- Citation Count: 8
CONet: Channel Optimization for Convolutional Neural Networks
- Authors: MS Hosseini, JS Zhang, Z Liu, A Fu, J Su, M Tuli, KN Plataniotis
- Conference: ICCV2021 NeurArch, 2021
- Citation Count: 7
