Vision

• Build well-documented, user-friendly modules for omics datasets
• Provide tutorials for early-stage data scientists in bioinformatics
• Standardize ML/DL and bioinformatics tools

Implemented Projects

• Streamlining Differential Gene Expression and Gene set enrichment analysis in GDC Data
• Ensemble Classifiers for Kidney Cancer Classification
• Disease Stratification using UMAP and DBSCAN

Data source: Genomic Data Commons

Codebase: OmixHub

Code RTD: readthedocs

Website omixhub.com

Vision

• Develop generalizable tools for e-commerce analysis
• Demonstrate advanced Python programming (OOP) with real-world data

Projects

• Customer Segmentation using K-means Clustering
• Analysis of Groupon Deals using Propensity Scores

Data source: Kaggle

Codebase: E-Commerce Projects

Vision

• Assemble deep learning algorithms for medical imaging analysis
• Create unified modules for 2D and 3D image processing

Projects

• Multi-label Classification of X-Rays using DenseNet

Data source: Contact via email

Codebase: AI for Medicine

During my masters at UC Davis, I developed skills in quantitative genetics and AI:

• Bayesian Regression Models in Animal Genomics
• Deep Learning for Intracranial Hemorrhage Detection
• Real-time Strategy Agents for Starcraft II