Causal Inference in Educational System

Speaker: Manie Tadayon
Affiliation: Ph.D. Candidate

Via Zoom:



Experimental designs like randomized control trials are considered golden standards; however, they are impractical due to cost, ethical, and compliance issues. Our research targets the use of quasi-experimental and observational studies with emphasis on graphical and causal DAGs. We propose to model the educational system as time-varying treatment and confounder feedback and claim if a sufficient number of confounders are measured, the joint causal effect of interventions on the outcome can be estimated accurately.



Manie Tadayon is currently working toward his Ph.D. in the Electrical and Computer Engineering Department. His research consists of designing the intelligent educational system using methods borrowed from causal inference and graphical models. Manie was an intern in Qualcomm lab at San Jose during summer 2017, and he has been with the Robotic group at JPL during 2019 and 2020.


For more information, contact Prof. Gregory Pottie ()

Date(s) - Jun 08, 2021
11:00 am - 1:00 pm

Via Zoom Only
No location, Los Angeles
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