Projects
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R Packages
MiscHelperfuns: Demo R Package
Python Packages
Other Open-Source Maintainership
UpDoc: An application for serving documentation in a cloud environment
Undergraduate Research Projects
Senior Thesis: A Primer on the Mathematics of Guaranteed Minimum Maturity Benefit (GMMB) Insurance Contracts
Advisor: Runhuan Feng
Project Duration: Academic Year 2017 - 2018 (December 2017 - May 2018)
Review on Capital Allocation Principles(SOA-Sponsored Center of Actuarial Excellence Project)
Advisor: Ying Wang
Project Duration: Academic Year 2016 - 2017 (August 2016 - May 2017)
Summarized literatures on optimal policy limits and capital allocation principles. Simulated numerical solutions using copula package in R.
Marketing Strategy Research Using Big Data
Advisor: Yi Yang
Project Duration: May 2016 - December 2016
Implemented network analysis in NEO4J on interaction data of 240 Facebook brand pages (~20GB) to test customer recommendation and social media management strategies. Intensive use of Python (data cleansing, feature engineering), databases (data management), and R (statistical analysis).
Undergraduate Class Projects
STAT 428 Course Final Project
Course Title: Statistical Computing
Course Term: Fall 2017
Instructor: Uma Virendra Ravat
Project Title: Applications of Computational Statistics Methods in Equity-Linked Insurance Pricing
MATH 484 Extra 4th-Hour Project
Course Title: Nonlinear Programming
Course Term: Spring 2017
Instructor / Advisor: Theodore Molla
Project Title: Iterative Optimization Algorithms - Summary and Visualization
Explored several iterative optimization methods (Newton, Steepest Descent, and Conjugate Gradient) by presenting theoretical proofs to the professor and creating visualization for algorithm performance.
CS 450 Graduate 4th-Hour Project
Course Title: Numerical Analysis
Course Term: Fall 2016
Instructor: Michael T. Heath
Project Title: Python Implementation of Numerical Methods for PDEs
Implemented textbook algorithms (method of lines, upwind forward finite difference, and centered difference) in Python to solve common PDEs (heat equation, wave equation, advection equation, Burger’s equation, and Poisson equation). Explored relationship between errors, computation time, and mesh size.