Mehrdad Oveisi

Mehrdad Oveisi is a Lecturer in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. His teaching focuses on courses such as Software Construction (CPSC 210), Introduction to Artificial Intelligence (CPSC 322), and Applied Machine Learning (CPSC 330), demonstrating expertise in foundational and advanced topics in computer science and AI.

His research interests center on the application of machine learning and artificial intelligence in medical imaging and healthcare. Key areas include radiomics (analysis of high-dimensional imaging features), development of standardized evaluation frameworks for machine learning models, and federated learning with privacy-preserving techniques. His work frequently involves collaboration with medical institutions to address challenges in oncology, cardiology, and diagnostic imaging.

Notable projects include the development of tools like ViSERA for reproducible radiomics workflows and studies on harmonizing imaging features across different modalities and institutions to improve reproducibility. His contributions span both methodological advancements (e.g., AllMetrics library) and clinical applications (e.g., survival prediction in cancer patients using MRI radiomics).

While no specific grants or awards are listed, his extensive publication record reflects active engagement in interdisciplinary research at the intersection of computer science and healthcare. Office hours are held at ICCS 141, and professional links include LinkedIn.