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About me
About me
I am an Operations Research PhD student at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at the Georgia Institute of Technology.
My research is applying modern machine learning and optimization methods to causal inference. In particular, I am interested in re-examining the estimation of the Conditional Average Treatment Effect and the Variable Treatment Intensity under the lens of modern optimization methods.
I am advised by Professor Turgay Ayer
Before this, I did my undergraduate in Cornell University, where I graduated in May 2017 with a double major in Computer Science and Operations Research.
My resume is available here
Publications
Publications
She, Z.*, Wang, Z.*, Ayer, T., Toumi, A., & Chhatwal, J. (2020). Estimating County-Level COVID-19 Exponential Growth Rates Using Generalized Random Forests. NeurIPS ML4H 2020
Wang, Z.*, She, Z.*, Ayer, T., & Chhatwal, J. (2021). Small Area Estimation of Case Growths for Timely COVID-19 Outbreak Detection (Operations Research, Under Review)
Wang, Z*, She, Z, Ayer, T (2021) Estimating Heterogeneous Treatment Effects With Modern Mixed Integer Programming (Working Paper)
(* indicates first/co-first authorship)
Professional Experience
Professional Experience
Google, Sunnyvale, CA, USA
08/2022 - 11/2022
Software Engineering Intern
05/2022 - 08/2022
Machine Learning Engineer Intern
Amazon Care, Seattle, WA, USA
05/2021 - 08/2021
Data Scientist Intern
Institute of High Performance Computing, Singapore
01/2018 - 08/2018
Computer Vision Engineer
06/2018 - 12/2018
Research Engineer
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