Hi, I'm Anthony 👋
Software Engineer | AI/ML and Full-Stack Developer
AN
About
I'm currently a Software Engineering student at UT Dallas. My interests are in AI/ML, full-stack development, and working on products that is innovative and helps people. Feel free to contact me if you'd like to chat!
Skills
React
Next.js
Tailwind CSS
Firebase
Python
Java
C
TypeScript
Firestore
TensorFlow
LangChain
Cheerio
Shadcn UI
Radix UI
AWS
GCP
Vercel
Vercel Blob
Upstash Redis
Jupyter Notebook
Streamlit
Linux
Pinecone
OpenCV
Plotly
Ngrok
Kotlin
My Projects
Check out my latest work
I've worked on a variety of projects, from simple websites to complex web applications. Here are a few of my favorites.
Intelligent LLM Router
Engineered a chat app that routes queries to optimal models from 12+ LLMs with customizable preferences.
Implemented routing analytics, rate limiting (20 req/min), and enterprise modal system.
Developed with Next.js 15, OpenRouter API, Shadcn UI, and TypeScript.
NEXT.JS
TYPESCRIPT
OPENROUTER API
SHADCN UI
TAILWIND CSS
AI Audio Transcription & Translator
Built a web application for automated transcription and translation of audio content, leveraging OpenAI's Whisper model and Groq's API.
Enables users to upload or record audio, segment transcripts with timestamps, and convert non-English segments to English in real-time.
The application provides downloadable results, real-time status updates, and robust error handling for a seamless user experience.
OPENAI
NEXT.JS
TYPESCRIPT
TAILWIND
TRANSLATION
Banking Customer Churn Predictor
Built an ensemble model using XGBoost, Random Forest, and K-Nearest Neighbors to assess customer churn risk.
Leveraged the Groq API to provide automated retention emails and SMOTE for imbalanced data handling.
Created a Streamlit interface for user data input and visualization of churn predictions.
PYTHON
GROQ
MACHINE LEARNING
MODEL INFERENCE
Brain Tumor MRI Classification
Engineered a deep learning model with Xception transfer learning, achieving 92% accuracy in classifying MRI scans.
Developed a Streamlit app for real-time classification with AI explanations via Google Gemini and saliency maps.
Deployed via Ngrok with comprehensive evaluation using TensorFlow, OpenCV, and Plotly.
TENSORFLOW
GOOGLE GEMINI API
PYTHON
STREAMLIT
OPENCV
Contact
Get in Touch
Want to chat? Just shoot me a dm with a direct question on twitter and I'll respond whenever I can. I will ignore all soliciting.