Investigating cases of product failures and implementing data-driven strategies to diagnose issues, using tools like Python for in-depth analysis, with the aim of imporving and and reducing recurrence in Cisco’s NPI process.
Leading B2B startup that provides business solutions from data science insights (i.e. attending meetings with VC firms);
Directing development of a team of three ML engineers, spearheading ML R&D
Developed and deployed dashboard with anomaly detection models including Autoencoders, SVM, CADE, Isolation Forests; Achieved high model accuracy and efficiency, as evidenced by consistent detection rates in test datasets
Automated analysis process by analyzing and clustering device failure data with H2O.ai and Python, significantly reducing troubleshooting time and operational costs.
Automated GTM workflows for Ansible Tower through full-stack development, streamlining workflows.
On intern team tasked with saving $24M/year by launching discounting feature rather than third parties (presented to CIO).
Led intern license plate recognition software implementation and development of pip package for company API.
R&D of iOS/Android apps that enable engagement between an ML platform, patients, and physicians.
Developed I2C communication code; designed and soldered circuits (i.e. IMU).
As a high school intern, I researched tensile strength of ABS ASTM D638 3D printed and injection molded samples.
Machine Learning and Data Science M.S.
Electrical Engineering B.S.