Software Engineer | Backend & Full-Stack Development | Applied AI

• 🎓 M.S. in Computer Science @ Northwestern University · Expected June 2027
• 🎓 B.S. in Computer Science & Applied Mathematics; B.A. in Economics @ UC Davis · Phi Beta Kappa
• 💼 Former Software Engineer Intern @ IDX Exchange — built React interfaces, Express REST APIs, and MySQL-backed search features for a platform with 53K+ property listings
• 🛡️ Worked on an Allstate Identity Protection industry-sponsored software engineering project — OCR, AI-assisted scam analysis, and resilient workflows
• 🤖 Building a multilingual RAG chatbot for Northwestern ECE, supporting 1,000+ users with Flask, FAISS, and analytics
• ⚙️ Built a real-time multi-user bill-splitting platform using STOMP, GraphQL, JPA transactions, and concurrency control
• 🧩 Practicing data structures and algorithms on NeetCode
• 🌱 Interested in backend engineering, distributed systems, reliable software, and applied AI

A multilingual retrieval-augmented generation (RAG) system built to help students, faculty, and prospective applicants find department information.

• Supported 1,000+ users across 18 inquiry categories with a JavaScript widget, Flask APIs, analytics, and session persistence
• Built a fault-tolerant ingestion pipeline for 26 university knowledge files, improving ingestion coverage from 96.2% to 100%
• Reduced representative query latency by 60% (15s → 6s) using startup preloading and reuse of a 714K-vector FAISS index

Tech: Python · Flask · JavaScript · FAISS · RAG · OCR

A real-time application for coordinating shared bill payments and handling concurrent item claims.

• Implemented live synchronization using STOMP messaging and GraphQL snapshots, achieving approximately 16 ms p95 claim-event propagation latency
• Used JPA pessimistic locking and transactional workflows to prevent conflicting claims on the same bill item
• Added a policy-constrained lightweight agent to handle eligible unclaimed items when participants become inactive

Tech: Java · Spring Boot · STOMP · GraphQL · JPA

An industry-sponsored software engineering project focused on analyzing potentially fraudulent text and image submissions.

• Combined OCR, regex extraction, GPT-assisted reconciliation, and HTTP risk evaluation in an automated analysis pipeline
• Built explainable risk-analysis interactions and scan-to-chat follow-up
• Added recovery paths for third-party service failures to improve workflow continuity

Tech: OCR · LLM Integration · REST APIs

Languages

Backend & APIs

Frontend

Databases & Data Systems

Cloud & Tools

• Preparing for 2027 New Grad Software Engineering and Applied AI Engineering opportunities
• Deepening my understanding of Java/Spring Boot, backend architecture, databases, and concurrency
• Building and improving reliable AI-powered applications with retrieval and production-oriented engineering practices
• Strengthening problem-solving skills through NeetCode

Always interested in building useful software and learning from other engineers.