Causal Inference in Educational Systems

Manie Tadayon, a PhD graduate from the ECE department at University of California, Los Angeles, joins us today to talk about his work “Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach.”

Guest

Manie Tadayon: Manie obtained his M.S and Ph.D. in Electrical and Computer Engineering at the University of California, Los Angeles (UCLA). His research was at the intersection of machine learning, causal inference, and time series analysis with application to education. During his Ph.D., he borrowed tools from various domains such as computer science, statistics, econometric, and epidemiology to design more intelligent educational systems. From October 2019 to May 2020, he was a research intern at Jet Propulsion Laboratory (JPL), working on various projects related to time series forecasting and Bayesian and graphical modeling. During his M.S study, He has done internships at Qualcomm and JPL in various signal processing and communication projects.