Indian Institute of Technology Madras, India

•  Designed experimental setups and visual paradigm to record EEG signals from both healthy and motor-disabled individuals.
• Employed linear and non-linear feature extraction techniques to investigate brain patterns of the subjects during real and motor imagery movements of their limbs.
• Analyzed the relationship between brain patterns and real and motor imagery movements of the limbs.
• Employed machine learning (SVM, LDA, NB, etc.) and deep learning (CNN, RNN, LSTM, etc.) models to classify the real and motor imagery movements of the subjects.

National Institute of Technology Rourkela, India

• Designed low-cost hydrogen gas and smoke detectors using ARM-microcontrollers.

• Investigated the heart rate variability (HRV) of athletes, smokers, and sedentary people using various machine learning (ANN, RF, SVM, etc.) models.

Silicon Institute of Technology Bhubaneswar, India

• Biomedical Signals and Image Processing

• Brain-Computer Interface

• NLP and Large Language Models (LLMs)

• Machine Learning and Deep Learning

• Computer Vision

• Data Science

• Coursera: Generative AI with Large Language Models (LLMs)

• Coursera: Neural Networks and Deep Learning Course

• Udemy: Generative AI for Beginners: Google Gemini and Google Cloud

• Udemy: Fine Tuning LLMs with Hugging Face Transformer for NLP

• Udemy: Python for Computer Vision with OpenCV and Deep Learning

• Udemy: Fine Tuning LLM with Hugging Face Transformers for NLP

Real-time recording and monitoring of EEG Signal