🎓Grad Student (UPenn) 🎓Alum (Cornell) 😸Cat Dad 🎸Artist 🏒Novice Hockey Player
Hey, welcome to my GitHub!
I'm currently pursuing my Master's in Computer Science at the University of Pennsylvania.
When I'm not busy with coursework, I enjoy working on projects that combine my interests in AI,
machine learning, and software development. This Summer 2025 semester, I'm taking:
📚 CIT 5960 - Algorithms and Computation (divide-and-conquer, dynamic programming, graph algorithms, NP-completeness)
📚 DATS 5750 - Cloud Technologies Practicum (Google Cloud & AWS, cloud architecture, data pipelines, ML model deployment)
I'm currently pursuing my Master's in Computer Science at the University of Pennsylvania.
When I'm not busy with coursework, I enjoy working on projects that combine my interests in AI,
machine learning, and software development. This Summer 2025 semester, I'm taking:
📚 CIT 5960 - Algorithms and Computation (divide-and-conquer, dynamic programming, graph algorithms, NP-completeness)
📚 DATS 5750 - Cloud Technologies Practicum (Google Cloud & AWS, cloud architecture, data pipelines, ML model deployment)
✈️ AiTinerary
Planning trips with friends made easier! Seamlessly organize travel plans, discover must-visit spots,
and optimize your itinerary based on preferences and real-time data.
Tech Stack: React (Next.js), TypeScript, PyTorch, Framer Motion, Supabase, Vercel, Highlight.io
Planning trips with friends made easier! Seamlessly organize travel plans, discover must-visit spots,
and optimize your itinerary based on preferences and real-time data.
Tech Stack: React (Next.js), TypeScript, PyTorch, Framer Motion, Supabase, Vercel, Highlight.io
☕ CaféCompass
A personalized, AI-powered web app that helps you discover the best study-friendly cafés based on
filters such as amount of seating, noise levels, outlet availability, and WiFi. The app leverages
Google Places API for location-based search and Yelp Fusion API to data scrape café reviews.
After cleaning review data through methods like tokenization, lemmatization, and stopword removal,
the app embeds it for processing. It then applies a machine learning-based sentiment analysis model
to evaluate and rate cafés across different filters, helping you find your next perfect study spot.
Tech Stack: React (Next.js), TypeScript, Python, PyTorch, Pandas, Supabase, Vercel
A personalized, AI-powered web app that helps you discover the best study-friendly cafés based on
filters such as amount of seating, noise levels, outlet availability, and WiFi. The app leverages
Google Places API for location-based search and Yelp Fusion API to data scrape café reviews.
After cleaning review data through methods like tokenization, lemmatization, and stopword removal,
the app embeds it for processing. It then applies a machine learning-based sentiment analysis model
to evaluate and rate cafés across different filters, helping you find your next perfect study spot.
Tech Stack: React (Next.js), TypeScript, Python, PyTorch, Pandas, Supabase, Vercel
