I am an Artificial Intelligence and Machine Learning undergraduate (Class of 2026) passionate about developing intelligent, data-driven solutions.
My interests include applied AI, Deep Learning, NLP, and Speech Processing. I enjoy building end-to-end machine learning projects that combine innovation, functionality, and real-world application.
I am currently exploring:
- Large Language Models (LLMs) and Prompt Engineering
- Speech Processing with Whisper and TTS
- Real-time AI Applications using Flask and Streamlit
- Stammer Detection & Speech Correction — AI pipeline for detecting and correcting stammered speech using Whisper, TTS, and Flask.
- Stock Price Prediction (Apple) — LSTM-based time series forecasting model with Streamlit dashboard.
- Fake News Detection — NLP-based Streamlit web app with Logistic Regression (99% accuracy).
- Age & Gender Prediction — CNN-based model for facial attribute recognition (VGG16, IMDb-Wiki).
LinkedIn • GitHub • Email • LeetCode • CodeChef
“Innovating with Intelligence — Building AI that Matters.”