•Designed first formal fine-tuning pipeline •Developed and deployed automatic code generation scripts•2nd Author for 3 papers in ML research

•Served as an AI Consultant for SAP Re-Commerce, identifying potential use-cases and building/implementing modern machine learning models•Conducted research and comparison of multiple deep learning models for AI use-cases and designed an AWS pipeline for seamless integration•Built and enhanced the cross-platform enterprise mobile web applications•Onboarded team members on modern machine learning methods that enhance application functionality

•Develop trading strategies and perform quantitative research in global equity and futures markets

•Aghaeepour Lab for Artificial Intelligence, Machine Learning, and Multiomics Integration for Translational Medicine•Department of Anesthesiology, Perioperative and Pain Medicine at Stanford Medicine•Performed CyTOF-based single cell analysis and deep learning•Evaluated the performance of geometric deep learning methods for single-cell data in multiple predictive settings•Utilized Python and deep learning frameworks PyTorch, Tensorflow, and Keras

•Oversaw 300+ Stanford mathematics undergraduates•Proposed rubrics, gave constructive feedback, and graded problem sets