Improving device failure analysis by leveraging data science techniques and tools like H2O.ai, OpenAI API, and Generative AI, leading to more accurate identification of root causes and enhanced reliability of Cisco hardware.
Implemented various models (including Classifier-Adjusted Density Estimation, Autoencoder, Isolation Forest) to detect fraud score anomalies in transaction data from major banks in the US, UK, Canada, India, and Brazil.
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.