- Design and apply computational tools to build the future of biotechnology and pharmaceutical research- Leverage high-performance computing (HPC) cluster — including GPU resources — to optimize RNAseq and DNA-seq assay data analysis- Developed proprietary, end-to-end integrated pipeline of genomics analysis tools in Python, Bash, and C++, cutting analysis times by >75%

Section Leader for Economics 1011a (Intermediate Microeconomics: Advanced)

- Designed computational analysis workflow in Python, R, and Bash capable of rapidly processing 10+ TB of genomics data per experiment- Integrate deep-learning-based sequencing tools and leveraged HPC cluster to speed up data processing from sequencing experiments- Presented primate comparative genomics research at the 2022 American Society for Human Genetics conference in Los Angeles, CA- Create intricate data visualizations using Numpy, Pandas, and ggplot, and advised lab team on appropriate protocol adjustments- Identify genes responsible for immune system disorders and determine optimal animal models for drug development- Derive insights from RNA-seq, DNA-seq, and FACS assays on human and primate immune/stem cells to elucidate disease susceptibility

- Developed PyTorch and TensorFlow-powered deep learning bioimaging solutions for contract research organization- Integrated imaging and medical record data into a suite of CNN and RNN models for liver disease severity detection- Leveraged visual-understanding CNN architectures, including U-Net and ResNet, for blood vessel disease diagnosis from retinal scans

- Taught algorithms in C and C++ to students in grades 4 - 12- Mentored RoboCup Junior national competition teams and taught problem-solving skills