About Me
Hi there! I am a Computer Science PhD candidate and NSF Graduate Research Fellow at the University of California, Irvine.
My research involves the integration of brain-inspired computing paradigms to popular deep reinforcement learning algorithms.
Prior to my graduate studies, I worked as a full-stack software engineer in the FinTech space.
Work Experience
- Lead research projects on the integration of brain-inspired computing paradigms into deep reinforcement learning algorithms (PyTorch)
- Presented several research talks in both academic and industry settings
- Mentored both Undergraduate and Masters students
- Experimented on various negative sampling techniques to mitigate cold content start problems for the Facebook Reels feature
- Integrated and implemented a credit policy model to dynamically calculate a customer’s credit risk; generated $1.2M+ savings
- Automated operations work using AWS Textract, reducing queue load by 40% with 1.2% FPR (Ruby on Rails)
- Built system for faster contractor payments ( i.e., electronic payments paid out faster than the ACH credit window) to onboarding customers
- Built and monitored products’ Redash dashboards (SQL)
- Supported the Risk Operations Team during risky credit escalations
- Implemented categorical entity embedding to replace the Bayesian Target Encoded categorical data to improve the company’s fraud detection models
