Hesam Farsaie, Ph.D.
About Hesam Farsaie, Ph.D.
Hesam Farsaie, Ph.D., is a Senior Data Scientist at Intactlab, where he has worked since 2018. He has over 8 years of experience in research and development, specializing in prediction theory and machine learning applications.
Work at Intact Financial Corporation
Hesam Farsaie serves as a Senior Data Scientist at Intactlab, a position he has held since 2018. In this role, he applies his expertise in machine learning and statistical modeling to develop innovative solutions. His work focuses on enhancing data-driven decision-making processes within the organization. Intactlab is known for its commitment to leveraging advanced analytics to improve customer experiences and operational efficiency.
Previous Employment Experience
Prior to his current role at Intactlab, Farsaie worked as a Data Scientist at Symcor from 2017 to 2018, contributing to data analytics projects in the Toronto area. He also briefly worked at Zighra in 2017 for two months as a Data Scientist in Ottawa. Earlier in his career, he held positions at MMS Laboratory as an Electrical Scientist and later as a Machine Learning Specialist from 2015 to 2016. Additionally, he worked as an Electrical Engineer specializing in signal processing at ERI-SUT in Iran from 2009 to 2011.
Education and Expertise
Hesam Farsaie holds a Doctor of Philosophy (Ph.D.) in Electrical Engineering from École de technologie supérieure, which he completed from 2011 to 2015. He also earned a Master of Science (M.Sc.) in Electrical, Electronics and Communications Engineering from Sharif University of Technology between 2008 and 2010. His undergraduate degree is a Bachelor of Science (B.S.) in Electrical and Electronics Engineering from Shahid Beheshti University, completed from 2003 to 2008. Farsaie has over eight years of research and development experience, particularly in prediction theory and machine learning applications.
Research and Development Experience
Farsaie's professional background includes extensive experience in research and development, particularly in machine learning, statistical learning, and modeling. He has a strong focus on natural language processing (NLP), computer vision, and speech processing. His expertise extends to leading multidisciplinary teams and projects, where he combines his knowledge of machine learning, pattern classification, and decision theory to drive innovation and improve analytical capabilities.