About Me
Applied Mathematics graduate from UCLA, passionate about building intelligent systems and exploring the intersection of AI and software engineering. Currently focused on developing serverless multi-agent frameworks using TypeScript and Cloudflare Workers, with experience spanning everything from low-level systems programming in Rust to AI orchestration and real-time data processing.
Technical Expertise
AI & Serverless Architecture
Architecting serverless multi-agent workflow frameworks with intelligent tool selection, SSE streaming, and optimized caching strategies for complex AI orchestration systems.
Web & API Development
Building high-performance web APIs with advanced TypeScript patterns, implementing sophisticated caching and retry logic for distributed systems.
Systems Engineering
Expertise in low-level systems programming with Rust achieving sub-20ms performance, Go for high-throughput services, and Python for data processing pipelines.
Machine Learning & AI
Extensive experience with Python's ML ecosystem, building and deploying various systems including sentiment analysis, malware classification, and vector similarity search engines. Achieved >96% precision in deep learning image detection and 92% accuracy in content moderation systems.
Data Infrastructure
Experience with both traditional databases and specialized data structures for high-performance applications.
Security & Cryptography
Implemented security systems including network monitoring, anomaly detection, and cryptographic libraries.
Mathematical Expertise
Strong theoretical foundation applied to algorithm design, performance optimization, and machine learning implementations.
Analytics & Development Tools
Experience with professional development workflows, user analytics tools, and data-driven optimization strategies demonstrated through production-ready project implementations.
Professional Journey
Software Engineer - AI Systems
PlungeAI
Nov 2024 - Present
Architecting serverless multi-agent workflow frameworks using TypeScript and Cloudflare Workers, creating flexible systems for AI orchestration. Developed optimized core for building SSE and streamableHttp MCP clients with high-performance caching and retry logic. Designed extensible architecture patterns allowing seamless integration of new capabilities while maintaining system performance.
Data Analyst Intern
Lull Ventures
Sep 2021 - Aug 2022 · Goleta, CA
Analyzed user behavior with Hotjar and Heap to drive a 10% increase in conversion rates for Lull's website. Spearheaded A/B testing program to optimize product page layouts and checkout processes. Quantified product bundling trends to achieve a 3% boost in conversion rates.
Data Science Intern
AMNESIA Media
Jun 2021 - Jul 2021 · Silicon Valley, CA
Implemented deep learning image detection models to identify non-compliant marketing content with >96% precision. Developed object detection systems using Detectron2 and PyImageSearch models with optimized false-positive rates. Created NLP compliance verification tools with spaCy to analyze text for regulatory violations in marketing content. Achieved 92% accuracy in content moderation by optimizing YOLOv5 and Detectron2 models.
Education
University of California, Los Angeles
B.S. in Applied Mathematics
GPA: 3.923/4.0 (Cum Laude)
Class of 2024
Academic Background
My academic journey in Applied Mathematics has shaped my approach to solving complex technical problems, providing a foundation that bridges theoretical rigor with practical applications.
Theoretical Foundations
Developed rigorous mathematical thinking and abstract problem-solving skills essential for algorithm design and system optimization.
Strengthened formal reasoning abilities, directly applicable to cryptographic system design and security protocol verification.
Computational Mathematics
Mastered computational techniques for solving complex mathematical problems, crucial for implementing efficient algorithms and optimizing system performance.
Studied advanced optimization techniques, now applied to enhance performance in distributed systems and machine learning models.
Applied Mathematics
Explored theoretical foundations of modern cryptography, informing my current work on secure system design and implementation.
Combined statistical theory with practical implementation, enabling me to develop sophisticated AI systems and optimization algorithms.
Interdisciplinary Applications
Applied mathematical modeling to strategic decision-making, valuable for designing robust distributed systems and security protocols.
Built a strong foundation in statistical analysis, essential for machine learning and system performance evaluation.
My mathematical background from UCLA helps me bridge conceptual understanding with practical implementation, whether I'm architecting scalable serverless systems, developing intelligent agents, or optimizing performance. This foundation enables me to create intelligent tool orchestration systems that span from deterministic automation to fully agentic behavior, always eager to work on challenging problems that blend mathematical reasoning with practical implementation.
Beyond the Code
Public Speaking
V.P. of Membership at Bruin Toastmasters, passionate about technical communication and leadership.
Mathematics
Deep interest in applied mathematics, particularly in its applications to machine learning and algorithmic optimization.
System Design
Enthusiast of distributed systems architecture and high-performance computing solutions.