• Classified During and Before mental arithmetic tasks.

• Used five entropies to extract features from the signal.

• Created a dataset using the onboard sensor of a smartphone.

• Designed the whole experiment.

• Classified Abnormal and Normal human gait using Ml and DL.

Analyzed 13 different activities performed by humans from smartphone sensor data using machine learning and deep learning. Applied some traditional machine learning algorithms and 2D CNN algorithms.

Applied attention-based seq2seq LSTM encoder-decoder model on the Twitter corpus from lince.

Technology used:  HTML, PHP, & Mysql.

This is a simple library management system that allows users and librarian to manage things over online efficiently.

As a part of the Embedded course, designed a safe distance maintaining kit for COVID19, pandemic situation using Arduino and sonar sensor.

• Ongoing