I'm currently working as an Integration Engineer at Lyft. I hold a Master's in Computer Science from San José State University and have previously built experience at Atlassian and Micro Focus. I'm highly interested in Software Engineering, Machine Learning, and Enterprise Systems, and I love diving into new technologies across the CS landscape.
Co-authored a paper titled 'Survival Analysis for Cancers of the Brain, CNS and Bone using Retrieval Augmented Generation on the SEER Database' and presented it at the AAAI Spring Symposium 2025 (AI for Health).
Our work on cancer survival analysis was accepted for presentation at the 8th Annual Stat4Onc Symposium, held at the Stanford University School of Medicine.
Grad Slam is a competition at SJSU where graduate students present their research to a live audience and a panel of judges.
Technical Mentor at Cal Hacks 2025 - Guided hackathon participants on Generative AI and presentation pitches.
Mentor at TreeHacks 2026 - Mentored students, guiding them through ideation and problem-solving
Speaker at WE Local Ohio - led a session on effective networking for early-career students, covering authentic relationship-building online and in-person, and real-world examples.
Mentored student teams at UCSD DataHacks from initial ideation through to their final judging presentations. Provided technical direction on stack selection and solution architecture while coaching teams on project scoping and effective product pitching.
Below, you will find links to project demos, applications, and GitHub repositories for my projects based on Software Engineering and Machine Learning.
A versatile application using Next.js and OpenAI, capable of fetching precise answers
A web application to track expenses. Built using HTML, CSS, Flask, and MongoDB.
A Next.js and Firebase based app that enhances overall household management and reduces grocery costs
A smart mobile application designed to optimize email communication by tracking recipient engagement, and ensuring timely follow-ups.
Android learning journal app built with Java and SQLite that integrates Claude AI API to analyze notes and generate insights including key themes, topic distribution, and learning summaries across different time periods.
A Next.js chat application that leverages LlamaIndex to generate knowledge graphs for any term, enabling users to receive accurate, context-based responses to their queries.
A system with user reviews and connections’ data, to recommend restaurants based on Yelp dataset. Built using Python, Collaborative filtering, link prediction, and GraphRec.
An ML system built using an e-commerce dataset to identify fake reviewers. Built using Python, Hadoop, and OpenRefine.