Dehua (Andy) Liang

714-***-**** # ad0lo2@r.postjobfree.com ï dehualiang § andylikescodes

Summary

Ph.D. in Data Science. Proficient in Python, R and SQL. Experienced in machine learning, statistics, A/B testing and causal inference, and their application for data-driven decisions in marketing, product development and operations.

Experience

Brain Institute, Chapman University Jan 2023 – Present

Postdoctoral Researcher

Orange, CA

• Led the design and implementation of data processing and machine learning pipelines for data science projects in lab

• Conducted research on longitudinal data and time-series neural signals, leading to two publications in preparation

• Collaborated with three external research institutes to explore and implement new research ideas

Brain Institute, Chapman University Jan 2019 – Dec 2022

Research Assistant

Orange, CA

• Led data curation for a yearlong survey study, resulting in a dataset for multiple high-profile publications

• Published 5 papers and gained 200+ total citations through collaboration with external and internal researchers

• Enabled processing and modeling for large-scale neuroimaging data on high-performance computing cluster and AWS

MingFeng Packaging USA Jul 2016 – Jan 2017

Sales & Marketing Representative

Baldwin Park, CA

• Boosted website traffic and sales conversions via SEO content creation and data analysis from Google Analytics

• Organized product trade show in Consumer Electronics Show (CES) and acquired new customers

• Collaborated with cross-functional global teams for seamless product production and on-schedule delivery

Projects

A/B Testing for Treatment Effect of Spanish Translation on Conversion Rate Git Sep 2023 – Oct 2023

• Conducted statistical testing for treatment effects on conversion rate

• Automated data analysis pipelines for data visualization and detection of confounding bias

Longitudinal Survey Study on Psychological States During Covid Publication link, Git Mar 2020 – Mar 2023

• Merged data from different sources, imputed missing values, and performed quality check in R

• Developed an interactive data visualization tool for exploratory analysis in Shiny-app

• Studied the impact of lockdown on depression through panel data analysis, machine learning and causal inference

Software Development of a Causal Inference Package in Julia Git May 2021 – Jan 2022

• Implemented inverse-probability weighting, standardization, and doubly-robust estimation in Julia

• Estimated causal effect confidence intervals through bootstrapping

Software Development of the Abra Eye-tracking Open-Source Package Git Jan 2020 – Jan 2021

• Led a software development team to develop a package for analyzing pupillometry data from eye-trackers

• Implemented object oriented design, unit testing and documentation with industry software development practices Skills

Programming: Python, SQL, R, Matlab, Julia

Modeling: Machine/Deep Learning, Causal Inference, Bayesian Stats, Panel/Signal Data, A/B Testing Software: Tableau, Shiny-app, Scikit-learn, Keras, Pandas, Numpy, Seaborn, Scipy, Jupyter Notebook Environments & Version Control: Git, Anaconda, Linux, Bash Scripting, VSCode, Docker, AWS, Slurm

Education

Chapman University, Orange, CA Jan 2017 – Dec 2022 Ph.D. in Computational and Data Science

California State University, Fullerton, CA Aug 2013 – May 2016 M.S. in Information System and Decision Science

Ball State University, Muncie, IN Aug 2008 – Dec 2012 B.S. in Business Administration/Economics (1+2+1 Sino-American Duel Degree Program)

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