Led a team of 2 and developed a model that combines the power of Continuous Wavelet Transform (CWT), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) to effectively detect and classify different types of heartbeats in electrocardiogram (ECG) signals.

Led a team of 2 and developed a recommendation system employing collaborative filtering techniques, which analyzes and learns from users' previous listening behaviors to offer highly accurate song recommendations aligned with their preferences and optimize their future listening experiences.

Utilized the power of Deep Learning and leveraged the Librosa library to construct a model capable of accurately classifying environmental sounds, specifically identifying urban sounds. This innovative approach enables precise recognition and categorization of various urban soundscapes for enhanced analysis and understanding of urban environments.

Designed an Artificial Neural Network (ANN) model specifically tailored for predicting patient mortality in ICU settings.

Developed a dynamic website, leveraging HTML and CSS for the frontend, and Django for the backend, to facilitate the optimal pairing of roommates in hostels. Employed a robust stable matching algorithm to ensure that the resulting roommate assignments are stable, with no instances of mutual preference between roommates. The website provides a seamless and user-friendly experience for finding the best and most compatible roommates in hostel settings.

Led a team of 3 and designed a model employing signal processing algorithms to accurately identify and classify individual musical notes within an audio file based on their corresponding frequencies.