About

Taha Bahadori is a Senior Machine Learning Scientist at Amazon with over 9 years of relevant experience. He is a skilled researcher with a strong interest in developing innovative machine learning tools for analyzing sequential data, such as multivariate time series. His expertise includes deep networks, high-dimensional sparse learning, and low-rank tensor learning. Taha is passionate about solving practical problems in the healthcare domain, given the prevalence of sequential data in this field. He is committed to designing novel and scalable machine learning algorithms for time series forecasting, survival analysis, and ensemble learning. Prior to his current role at Amazon, Taha worked as a Machine Learning Scientist at the same company and as a Senior Academic Advisor at Terra.ai. At Terra.ai, he was responsible for designing novel and scalable machine learning algorithms for time series forecasting, survival analysis, and ensemble learning. Taha holds a PhD in Electrical Engineering from the University of Southern California and a Bachelor of Science in Electrical Engineering from Sharif University of Technology. He has a strong technical background and is proficient in ML and Research Scientist. In summary, Taha Bahadori is a highly skilled Senior Machine Learning Scientist with a strong research background and a passion for developing innovative machine learning tools for analyzing sequential data. He has extensive experience in the healthcare domain and is committed to solving practical problems in this field.