About

Mostafa Rahmani is a highly skilled machine learning scientist with a strong background in randomized linear algebra, probability theory, and optimization. He specializes in unsupervised learning, randomized data sketching, deep learning, and computer vision. Currently, he works as a Machine Learning Scientist at Amazon AI, where he is responsible for enhancing the quality of recommendations made in Prime Video using state-of-the-art techniques in deep learning and online convex optimization. Mostafa has an impressive track record of devising and implementing novel algorithms for various projects. He developed a novel algorithm for the Human in The Loop (HITL) feature of Amazon Lookout for Metric and also devised a novel anomaly detection algorithm for the same project that outperformed existing baselines with a remarkable margin. Prior to joining Amazon, Mostafa worked as a Research Scientist and Post-Doctoral Machine Learning Researcher at Baidu USA. He has a Doctor of Philosophy (PhD) degree in Electrical, Electronics, and Computer Science from the University of Central Florida, a Master of Science (MSc) degree in Electrical, Electronics, and Communications Engineering from Sharif University of Technology, and a Bachelor of Science (BSc) degree in Electrical, Electronics, and Communications Engineering, also from Sharif University of Technology. Mostafa has a strong tech stack that includes skills such as research scientist, ML, AI, deep learning, and computer vision. With almost five years of relevant experience, he is a valuable asset to any team he works with.