Mahmoud (Ramin) Essalat
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Mahmoud, who is known as Ramin, obtained his PhD in Electrical and Computer Engineering from UCLA and his Bachelor’s degree in electrical engineering from the Sharif University of Technology in Iran. He possesses extensive research experience in applying time-series data acquired from sensors, including IMUs, PPGs, EEGs, ECGs, BLEs, and radar, across various industries ranging from smart healthcare, specifically oral healthcare and wearable devices, to automotive applications. Ramin’s expertise lies in deep learning techniques, encompassing architecture design for CNNs, LSTMs, and Transformer models, as well as model interpretability and optimization through hyperparameter tuning. He is also skilled in signal processing methods, particularly adaptive filters and spectrum estimation, and has a strong background in statistical analysis, specifically mixed-effect GLMs. Ramin has gained practical experience through internships with the Tesla Autopilot sensing team in Palo Alto, CA, and the Institute for Infocomm Research, A*STAR in Singapore. During his leisure time, he enjoys listening to music, playing poker, and spending time with friends.