Los Angeles, California, United States
I am a PhD candidate at the University of Southern California. I study robust interaction effect size measures with Dr. Rand Wilcox and emotional distance measures with Dr. Meng Chen. Outside of studies, I row with the Los Angeles Lions Rowing Club.
- Designing and implementing nonparametric interaction methods, the Patel-Hoel measure and the signed explanatory measure of interaction effect, in the presence of covariates. - Building robust generative models by embedding the Harrell-Davis estimator into the sliced Wasserstein Distance to improve robustness under outliers and distribution shift in Python. - Managing interdisciplinary projects and delivering lectures to foster cross-functional collaboration among robust statistics, materials science, and physics; creating and presenting data visualizations to clearly convey simulation results.
- Supported 80+ clients (graduate students, post-docs, and faculty) on statistical modeling and study design, improving analysis quality and reproducibility across projects. - Led 8 workshops on robust statistics and deep learning, helping researchers build models resilient to outliers and non-normal data; provided reusable R/Python templates and documentation.
- Lectured in an undergraduate psychological statistics course, graded homework and exams, and held office hours to support over 70 students per semester. - Provided guidance on statistical concepts, data analysis, and research methodologies to enhance student understanding and performance.
- Simulated and evaluated five reinforcement learning algorithms (Q-learning, Deep Q-learning, Deep Q Networks, Monte Carlo methods, and policy-based algorithms) on the inverted pendulum balancing problem. - Analyzed vector-matrix multiplications (VMMs) and computational complexity to assess algorithmic efficiency and performance.
- Assisted undergraduate statistics majors with R and SQL coding for fundamental data science concepts. - Provided support in debugging, data manipulation, and analysis to enhance students’ programming proficiency and understanding of statistical applications.
- Developed and implemented a Dual-N Back game in a mobile environment using JavaScript, collecting user data from gyroscope, accelerometer, and touch pressure sensors. - Conducted time series analysis in Python to examine user interaction patterns. - Implemented 3D stacked images of autistic mice brain scans in MATLAB for stochastic modeling, enhancing visualization and analysis of neuroimaging data.
- Developed and tested image recognition algorithms using Convolutional Neural Networks (CNNs) in C++ on an NVIDIA Jetson module running Linux. - Contributed to the company's new mobile vision device for visually impaired individuals, optimizing real-time image processing for accessibility applications.