Hamidreza Shahidi
About Hamidreza Shahidi
Hamidreza Shahidi is a Research Engineer II at Borealis AI, with a background in computer science and electrical engineering. He has held various positions in academia and industry, including roles at the University of Waterloo and RSVP.ai.
Current Role at Borealis AI
Hamidreza Shahidi serves as a Research Engineer II at Borealis AI, a position he has held since 2021. His work focuses on advancing machine learning technologies within the organization. Borealis AI is known for its commitment to research and innovation in artificial intelligence, contributing to various projects that enhance the capabilities of AI systems.
Previous Experience at Borealis AI
Prior to his current role, Hamidreza Shahidi worked at Borealis AI as a Machine Learning Software Engineer II from 2020 to 2021. He also held the position of Machine Learning Software Engineer I from 2019 to 2020. His tenure at Borealis AI involved developing and implementing machine learning solutions, contributing to the company's research initiatives.
Academic Background
Hamidreza Shahidi completed his Master's of Mathematics (MMath) in Computer Science at the University of Waterloo from 2017 to 2019. He also holds a Bachelor of Science (BSc) in Electrical Engineering from the University of Tehran, where he studied from 2013 to 2017. His educational background provides a strong foundation in both theoretical and practical aspects of engineering and computer science.
Research Experience at University of Waterloo
During his time at the University of Waterloo, Hamidreza Shahidi worked as a Research Assistant from 2017 to 2019. In this role, he contributed to various research projects, enhancing his skills in research methodologies and data analysis. He also served as a Teaching Assistant during the same period, supporting undergraduate students in their coursework.
Internship Experience at RSVP.ai
Hamidreza Shahidi gained practical experience as a Machine Learning Research Intern at RSVP.ai from 2018 to 2019. This internship allowed him to apply his academic knowledge in a real-world setting, focusing on machine learning applications and research.