Azin Asgarian is currently an applied research scientist on Georgian’s R&D team, where she works with companies to help adopt applied research techniques to overcome business challenges. Azin holds a Master of Science in Computer Science from the University of Toronto and a Bachelor of Computer Science from the University of Tehran. Before joining Georgian, Azin was a research assistant at the University of Toronto and part of the Computer Vision Group, where she worked on the intersection of Machine Learning, Transfer Learning, and Computer Vision. In addition, due to her interest in HealthCare, she has worked on various healthcare projects as a research assistant at University Health Network.
Datacast Episode 56: Apprehending Quantum Computation with Alba Cervera-Lierta
Alba Cervera-Lierta is a postdoctoral researcher at the Alán Aspuru-Guzik group at the University of Toronto. She obtained her Ph.D. at the University of Barcelona in 2019. Her background is in particle physics and quantum information theory. She has focused on quantum computation algorithms in the last years, particularly those suited for noisy-intermediate scale quantum computation.
What I Learned From Attending Toronto Machine Learning Summit 2020
Last month, I had the opportunity to attend the Toronto Machine Learning Summit 2020, organized by the great people at the Toronto Machine Learning Society. I previously attended their MLOps event in the summer, which I also have written an in-depth recap here.
The summit aims to promote and encourage the adoption of successful machine learning initiatives within Canada and abroad. There was a variety of thought-provoking content tailored towards business leaders, practitioners, and researchers. In this long-form post, I would like to dissect content from the talks that I found most useful from attending the conference.