resume

Machine Learning Intern

UXLY

• Developing a multi-agent chatbot, leveraging Retrieval-Augmented Generation (RAG) with FAISS/Pinecone and LLaMA to enhance knowledge retrieval for customer inquiries.
• Building an intent classification pipeline using LangChain and LangGraph, reducing misrouted requests by 40% and ensuring accurate query handling.
• Optimizing product catalog data management, splitting and indexing it across multiple vector databases, enabling efficient retrieval for specialized chatbot agents and improving response efficiency by 35%.

Software Engineering Intern

Beau

• Bridging the gap between client and make-up artist by developing a matching and booking system using React Native, Python and Firebase, setting the stage for a seamless user experience and generating pre-launch interest.
• Enhanced software design, coding, and testing, accelerating feature deployment by 25% and integrated Jest for unit testing, ensuring robust and maintainable code.
• Collaborated with co-founders and engineers to ensure scalable launch readiness, focusing on robust system design and data integrity.

Software Engineering Intern

NASA

• Implemented and enhanced 10+ features for the CMS Celestial Mapping System using Java, improving 3D simulation accuracy and supporting mission planning initiatives.
• Integrated GDAL updates, increasing image projection accuracy by 30%, while implementing vector-based enhancements that improved crater analysis efficiency by 40%.
• Developed data pipeline and algorithms for HORUS AI, improving lunar crater clarity by 25%, and presented the project at the NASA Better Together 2023 conference.

Software Engineering Intern

Kitu Systems

• Created a Python program using regex to automate requirement extraction for Kitu-Inverter-Client, improving efficiency by 70% and reducing development time by 35%.
• Conducted TPM testing on the OnLogic Board, achieving a 95% success rate in secure key storage and file decryption while improving team accessibility.

Bachelors

University of California Santa Cruz

Computer Science and Mathematics Minor

• GPA: 3.84
• Data Structures/Algorithms
• Object Oriented Programming
• Software Engineering
• Deep Learning
• Machine Learning
• Operating Systems
• Natural Language Processing

PlayPicks

• React | Flask | SpaCy | Firebase | Llama | Odds API | RAG
• Built an AI-powered sports betting chatbot using LlamaIndex (RAG) and GPT-4 for real-time odds, AI predictions, and personalized insights.
• Integrated spaCy for NLP, Firebase for data management, and Odds API for real-time sports data, deploying via AWS Amplify to reach 100+ users.

PantryPal

• Streamlit | Flask | Pandas | NLTK | SKLearn | BeautifulSoup
• Engineered an AI-powered recipe recommendation tool, using Streamlit for an interactive UI and Flask for backend processing.
• Built a machine learning model using scikit-learn and NLTK, leveraging BeautifulSoup for web-scraped recipe data to enhance recipe recommendations based on user-inputted ingredients.

Wasteless

• 1st Place Overall | Best Use of Google Cloud | Best Golden State Hack
• Firebase | Firebase Cloud Messaging | Google Maps API | Flutter | Google Cloud
• Developed a food waste app using Firebase, Google Maps API, and Flutter, allowing users to find and collect excess food from dining halls and restaurants, reducing food waste costs by an estimated $162 billion annually.