Bashashati, Ali
PhD
Academic Rank(s): Associate Professor, SBME & Department of Pathology and Laboratory Medicine, Faculty of Medicine, UBC | Director of Artificial Intelligence (AI) Research in the OVCARE
Affiliation(s): BC Cancer
Research and Scholarly Interests: Cancer, artificial intelligence, machine learning, computational pathology, computational genomics, bioinformatics
Clinical Interests: Imaging & Computational Biology
Dr. Bashashati is currently the director of artificial intelligence (AI) research in the Ovarian Cancer Research Program (OVCARE) at BC Cancer as well as a faculty member in the Department of Pathology and Laboratory Medicine and the School of Biomedical Engineering at the University of British Columbia.
Dr. Bashashati’s research area lies at the interface between computational, engineering and biomedical sciences. He is interested in developing machine learning algorithms to combine various sources of ‘omics and imaging data (including digitized pathology slides) in the context of cancer. Dr. Bashashati runs BC’s Translational Digital Pathology AI program and works closely with clinicians and biologists across various health sites. Through AI, they intend to improve pathology efficiency, identify new biomarkers for treatment selection and derive biological insights that can be studied in various disease models in the lab.
Academic Background
- PhD in Electrical & Computer Engineering, University of British Columbia (UBC), BC, Canada. 2007
- MSc in Biomedical Engineering, Tehran Polytechnic (Amirkabir University of Technology), Tehran, Iran. 2002
- BSc in Electrical Engineering (Electronics), Sharif University of Technology, Tehran, Iran. 2000
Awards and Recognition
Publications
Research Interest
Dr. Bashashati’s research area lies at the interface between computational, engineering and biomedical sciences. He is interested in developing machine learning, statistical and signal processing algorithms and software infrastructure to combine various sources of omics and imaging data with major emphasis on discovering novel complex biological information related to different diseases. His research is specifically focused on ovarian and breast cancers as well as lymphoid malignancies and how these cancers evolve and respond to therapies. He has published extensively in cancer genomics, bioinformatics, computational biology and brain computer interface fields and his papers have appeared in top-tier journals such as Nature and Nature Genetics.