• Researched and implemented machine/deep learning algorithms on EEG and ECG data for biomedical applications, including neurological recovery prediction and sleep stage classification.• Conducted data preprocessing, feature extraction, and model training for time-series data, contributing to improved classification accuracy in EEG and ECG analyses.• Reviewed current literature to inform project methodology, ensuring a foundation grounded in recent advancements and established practices… Show more • Researched and implemented machine/deep learning algorithms on EEG and ECG data for biomedical applications, including neurological recovery prediction and sleep stage classification.• Conducted data preprocessing, feature extraction, and model training for time-series data, contributing to improved classification accuracy in EEG and ECG analyses.• Reviewed current literature to inform project methodology, ensuring a foundation grounded in recent advancements and established practices in biomedical signal processing.• Wrote research papers, grant proposals, and created visually engaging presentations to communicate findings effectively in academic and professional settings Show less

• Wrote research paper, reports, reviews, and summaries about biomedical data processing and machine learning.• Perform time, frequency, and time-frequency analysis of biomedical time-series data• Implemented various machine learning models including SVM, Decision Tree, Random Forest, K-NN, ANN, and CNN.• Collected cardiac and pulmonary data from different hospitals in Peshawar.• Achieved over 80% accuracy with AI models on real data.