Built an AI investment agent that fetches real-time stock data (via yfinance) and uses a conversational LLM (Hugging Face) to answer natural language questions about any stock ticker.

Implemented a Gradio web interface so users can chat (like ChatGPT) and dynamically change the ticker (e.g., "/ticker TSLA") to get instant insights.

Integrated real-time market data (Open, High, Low, Close, Volume) and conversational AI to generate personalized stock summaries and investment insights.

Developed a full-stack web application using Python, Flask, and the seam carving algorithm, enabling users to upload images, specify resizing parameters, and download optimized results.

Leveraged Pillow and NumPy to implement intelligent content-aware resizing by dynamically removing horizontal and vertical seams, preserving critical visual details.

Analyzed Chicago ride-sharing data in RStudio, using the sf package for spatial analysis and infer package for hypothesis testing.

Applied LASSO and Ridge regression in tidymodels for predictive modeling and cluster analysis for pattern detection.

Created a Java program to analyze video data of polystyrene beads undergoing Brownian motion, applying image processing techniques.

Calculated Avogadro's number and Boltzmann's constant using Einstein's theory of Brownian motion.