Department of Mathematics and Statistics
Memorial University of Newfoundland
St. John's, NL, Canada, A1C 5S7
Phone: (709) 864-8798
Email:
LinkedIn: Hamid Usefi
Short Bio
My recent research interests include machine learning, deep learning, computer vision, and medical imaging. I obtained my PhD from Western University and held postdoctoral positions at the University of British Columbia and the University of Toronto before joining Memorial University in 2011. Additionally, I contribute as an editor in the computational section of Nature: Scientific Reports. I am serving as a Guest Editor for an upcoming collection in Scientific Reports entitled Modeling and methods of population health and social change.
Selected Publications (complete list can be found here)
- E. Ghanem, A. Hatefi, H. Usefi, Unsupervised Liu-type Shrinkage Estimators for Mixture of Regression Models, Statistical Methods in Medical Research, 2024. arXiv:2209.04739
- A. Ameli, L. Pena-Castillo, H. Usefi, Assessing the reproducibility of machine-learning-based biomarker discovery in Parkinson's disease, Computers in Biology and Medicine, 2024. DOI
- A. Sardari, H. Usefi, Machine learning-based meta-analysis of colorectal cancer and inflammatory bowel disease, PLoS ONE, 2023. DOI
- M. Maheri, C. Bazan, S. Zendehboudi, H. Usefi, Machine learning to assess CO2 adsorption by biomass waste, Journal of CO2 Utilization, 2023. DOI
- H. Usefi, Clustering, multicollinearity, and singular vectors, Computational Statistics & Data Analysis, 2022. arXiv
- M. Afshar, H. Usefi, Optimizing feature selection methods by removing irrelevant features using sparse least squares, Expert Systems with Applications, 2022.
- M. Afshar, H. Usefi, Dimensionality reduction using singular vectors, Scientific Reports, 2021. PDF
- H. Marvi Khorasani, H. Usefi, L. Pena-Castillo, Detecting ulcerative colitis from colon samples using efficient feature selection and machine learning, Scientific Reports, 10 (2020). arXiv: 2008.01615
- M. Afshar and H. Usefi, High dimensional feature selection for genomic datasets, Knowledge-Based Systems, 206 (2020). arXiv: 2002.12104
Conferences and Sessions
I have been a co-organizer for sessions on the mathematics of machine learning at Canadian Mathematical Society (CMS) bi-annual meetings:
Supervised Students
- Sahil Mahey (BSc Honors Thesis in Computer Science, 2024)
- Hridita Tabassum (MSc in Computer Science, 2024)
- Adithya Sudhan (MSc in Computer Science, 2024)
- Daniel Fiadjoe (MSc in Computer Science, 2024)
- Mahmoud Maheri (MSc in Computer Science, 2024)
- Aria Sardari (MSc in Computer Science, 2024)
- Bahare Zare (MSc in Computer Science, 2024)
- Javad Aghadvoodi (MSc in Statistics, 2023)
- Elsayed Ghanem (MSc in Statistics, 2023)
- Ali Ameli (MSc in Computer Science, 2022)
- Sri Harsha Yerramsetty (MSc in Computer Science, 2021)
- Majid Afshar (PhD in Computer Science, 2021)
- Asma Javaid (MSc in Computer Science, 2021)
- Aida Ghayour (MSc in Computer Science, 2020)
- Hoda Rafieipour (MSc in Computer Science, 2019)
- Fatemeh Taghdisi (MSc in Computer Science, 2019)
- Javad Rahimipour (PhD in Computer Science, 2019)
- Hanieh Marvi (MSc in Computer Science, Sept 2019)
- Keyvan Derakhshan Nik (MSc in Computer Science, 2018)
- Sudharaka Palamakumbura (MSc in Mathematics, 2016)
- Iren Darijani (MSc in Mathematics, 2015)
- Chris Pardy (NSERC USRA, MUN, Summer 2014)
- Si Ryun Lee (NSERC USRA, UBC, Summer 2010)
- Hassan Azzawi (NSERC USRA, UBC, Summer 2009)
I have had the privilege of supervising and working with many talented students across various levels of study, contributing to their growth and development in the fields of mathematics, statistics, and computer science. Below is a list of students I have had the honor of mentoring, along with their graduation years. If you are passionate about machine learning, have a strong background in Math/Stats, and would like to work with me please do reach out.
Contact Information
If you are interested in collaborating or learning more about my work, feel free to reach out!
Email: usefi@mun.ca