About Me
Builder. Engineer. Visionary.
I'm a Computer Engineering & Computer Science student at UW–Madison who loves building AI systems that solve real-world problems at scale. I have worked in industry, research, and projects, and am actively looking for 2026 summer internships in SWE or AI/ML.
At Blue Cross Blue Shield, I built an in-call AI assistant that transcribes calls, searches internal databases, and generates responses in under 5 seconds, cutting Customer Service Representatives' lookup time by 95%, impacting 3M+ members. I engineered the full RAG pipeline with LangChain, Azure OpenAI, and real-time transcription, integrating it into a desktop app with automated post-call summaries.
As a Machine Learning Researcher in the Computational Optics Group, I developed ML pipelines for non-line-of-sight imaging, optimized neural network inference by 20% for embedded deployment, and trained models on large-scale, noisy datasets.
I co-founded ClaimReady, a 5x award-winning AI web app that cuts insurance claim valuation from 20+ hours to under 2 minutes. We scaled to 350+ users, valued $800K+ in items, and deployed a YOLO11 + Gemini pipeline on AWS, earning recognition from YC partners and the UW–Madison CS dept.
Check it out here: useclaimready.ai
As Lead SWE & Co-founder of FiPet, I built a cross-platform mobile app delivering gamified financial literacy for Gen Z. We grew a 200+ user waitlist pre-launch and shipped a React Native + Firebase MVP with AI-powered personalization and automated quest generation.
Check it out here: fipet.dev
Awards & Recognition
Recognition for technical excellence and innovative software engineering projects
1st Place MadData25 Hackathon
24 hour hackathon with 30+ teams and 120+ competitors. Won first place and best presentation.
Top 3 at University Madness Startup Pitch Competition
Placed Top 3 and were the Audience Favorite among 30+ teams across 9 universities.
Top 3 at Badger Launchpad Startup Pitch Competition
Competed against 20+ teams from UW-Madison in a university startup competition.
Experience
My professional journey in software engineering and AI/ML
Blue Cross Blue Shield
Software Engineering Intern
Developed an in-call support app for customer service reps, transcribing live calls, retrieving answers from internal databases, and delivering AI-generated responses in under 5 seconds, serving 3M+ members. Engineered a Python-based RAG pipeline with LangChain (custom agents, RetrievalQA) using hybrid keyword + semantic search, Azure real-time transcription, and Azure OpenAI LLMs, cutting CSR lookup time by 95%+. Integrated the pipeline into a desktop app with automated post-call summaries for seamless real-time call assistance.
FiPet
Lead SWE/Co-founder (Part-Time)
Architected a cross-platform mobile app with AI-powered, gamified financial education modules tailored for Gen Z audiences. Scaled pre-launch to a 200+ user waitlist using ML-driven personalization for adaptive learning. Led a 15-person engineering team to build the MVP using React Native, Firebase (Firestore, Auth, Cloud Functions), and AI/LLM pipelines for automated bonus quest generation and progress tracking.
Computational Optics Group
Machine Learning Researcher
Developed ML pipelines with optical sensor data, enabling non-line-of-sight object imaging and reconstruction. Achieved 20% reduction in neural network inference overhead, improving edge deployment feasibility on embedded systems. Engineered embedded Python software for lasers and high-speed cameras for real-time photon capture, and trained/fine-tuned convolutional neural networks in Python/MATLAB on 3 large-scale datasets with varied scenes, noise, and sensor setups.
Wisconsin Autonomous
Software Engineer
Architected a perception system for autonomous vehicles enabling real-time lane, cone, and boundary detection. Achieved sub-100 ms inference latency for safe high-speed navigation by optimizing ML algorithms with OpenCV. Integrated the perception module into a software pipeline coordinating sensor fusion, control systems, and vehicle decision-making, collaborating with a 30+ person team on Git-based workflows and CI/CD pipelines.
Skills & Technologies
A comprehensive overview of my technical expertise and proficiency levels
Languages
Frameworks/Libraries
Developer Tools
Portfolio
A showcase of my recent projects and technical accomplishments
ClaimReady
Co-founded a 5x award-winning AI web application that generates complete home inventories and reduces insurance claim valuation time from 20+ hours to under 2 minutes, accelerating post-disaster recovery for homeowners and adjusters. Scaled to 350+ users by deploying an image valuation pipeline via Docker AWS EC2, using YOLO11 for detection, Gemini API for brand/price identification, and SupabaseDB; processing 1,500+ images and valuing $800K+ in items. Recognized as 'investor-ready' by judges and acknowledged by YC partners and UW-Madison CS Dept for technical excellence.
Hyperacing
Created and scaled a Formula 1 analytics platform to 1000+ users, delivering AI insights and live telemetry in real-time. Integrated Firebase Auth for secure login and session management, and used F1 WebSockets to stream real-time race data. Engineered a Next.js frontend with dynamic dashboards, a live F1 news feed, and live analytics.
Voice-Controlled Robot Arm
Architected a full-stack voice interface to control a robot arm by transcribing real-time speech into robot commands. Validated the entire pipeline with async audio input and physics-based simulation built in Python, achieving sub-200 ms end-to-end response time and 90% task completion accuracy for natural, hands-free operation. Engineered a Claude LLM pipeline to convert prompts like 'clear the table' into JSON robot actions executed via MCP.
Greenhouse IoT Monitoring System
Innovated an IoT system tracking temp, humidity, and brightness on Raspberry Pi in Python, optimizing GPIO control. 10K+ data points transmitted daily in real time by configuring Azure IoT Hub and REST APIs. Deployed a Dockerized Django-React app on Azure App Services, enabling remote monitoring by parents in India.
Smart Budget Tracker
Built a full-stack budget tracking application with .NET 8.0 backend and React frontend for comprehensive financial management. Implemented Entity Framework Core with MySQL database for robust data persistence and transaction handling. Integrated Chart.js for dynamic data visualization and jsPDF for automated financial report generation. Added AI integration capabilities using OpenAI SDK for intelligent budget insights and recommendations with RESTful APIs.
Machine Learning Activity Recommender
Built a full-stack Flask web app with MultiOutput Random Forest classifier trained on 10K+ datapoints for activity recommendations. Achieved ~75% accuracy and 25% Hamming loss using Scikit-learn with 80/20 train-test split for multi-label classification. Implemented confidence-based scoring and SQL database storage for user behavior analysis and performance improvement.