Projects

Building a Self-Playing Guitar using Arduino and Servo Motors. Will also use Machine Learning to compose Guitar Covers for any Song.

Creating a Reading App for iOS using React Native. The app will have features like Reading Progress, Book Recommendations, and a Friends List to share books with.

Designed Convolutional Neural Network (CNN) for both 3D and 2D MRI brain scans, to diagnose Multiple Sclerosis with an accuracy rate of 85% across various stages of the disease.

Digitized handwritten math by capturing images of handwritten symbols, using bounding boxes for detection, and classifying each with a trained model to convert into LaTeX. We improved efficiency by adopting FloodFill for symbol detection over traditional machine learning, overcoming challenges in model accuracy due to similar symbols and characters.

The Bollinger Bands algorithm generated a 43.23% profit on Microsoft stock using moving averages and standard deviations. The EMA10 RSI14 strategy yielded a 242.41% profit on Tesla by utilizing market condition indicators. The LSTM Machine Learning model accurately forecasted Google's closing prices, showcasing the power of neural networks in analyzing market dynamics.

The custom-developed method for predicting mudslides outperforms the Mohr-Coulomb method by 32%. It slightly underperforming compared to 2D modeling, but is nearly 10x faster. This demonstrates the model's effectiveness and efficiency in improving mudslide prediction accuracy and speed across various U.S. locations.