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Rohollah (Raha) Moosavi

Sessional Assistant Professor (CLA)

Bio

Dr. Rohollah (Raha) Moosavi is an Assistant Professor in the Department of Electrical Engineering and Computer Science (Sessional Teaching Stream) at York University. He holds a Bachelor’s (B.Sc.) and Master’s (M.Sc.) degree in Computer Software Engineering, a Ph.D. in Computer Science with a specialization in Computer Vision, and has completed Postdoctoral Fellowships in Computer Science at McMaster University and the University of Waterloo.

Raha has been teaching Computer Science and Computer Engineering courses since 2005 at several universities, including 6 years as a Limited Term Teaching Faculty member at Ontario Tech University (Canada) and 13 years as an Associate Professor at Tehran Azad University (Iran).

Over the past two decades, his teaching has covered a broad range of subjects, including Design and Analysis of Algorithms, Database Design, Big Data Systems, Operating Systems, Scientific Data Analysis, Image Processing, and Computer Vision. He brings nearly 20 years of academic experience to the classroom, blending strong theoretical foundations with practical expertise gained through his professional work as a Software Engineer, Senior Software Engineer, and Team Lead in the tech industry.

His research interests include Large Language Models, Big Data, Machine Learning, Deep Learning, and Medical Image Processing, with a focus on developing AI-driven methods for data-intensive applications, particularly in the healthcare domain.

Outside of academia, he enjoys reading, jogging, and swimming.

Research Interests

  • Large Language Models
  • Big Data Analytics
  • Machine Learning & Deep Learning
  • Natural Language Processing
  • Medical Image Processing
  • Medical Data Analysis

Selected Publications

Selected Journal Articles

  • Moosavi Tayebi, R., Tizhoosh, H. R., & Campbell, C. (2022). Automated bone marrow cytology using deep learning to generate a histogram of cell types. Communications Medicine, Nature
  • Youqing, M., Tizhoosh, H. R., & Moosavi Tayebi, R. (2021). A BERT model generates diagnostically relevant semantic embeddings from pathology synopses with active learning. Communications Medicine, Nature

Book

  • Moosavi Tayebi, R. (2009–Present). Operating Systems Concepts (15th ed.). Pooran Pajouhesh, Iran. ISBN: 978-964-184-081-7

Patent

  • Moosavi Tayebi, S. R., Tizhoosh, H. R., & Vaughan, C. J. (2022). Systems and methods for automatically classifying cell types in medical images. U.S. Patent Application No. US 20220335736