I completed a Bachelor of Science degree in Electrical and Electronic Engineering from American International University-Bangladesh (AIUB). I have worked on different technologies like C, C++, Java, Python, R, and MySQL. Additionally, courses like Artificial Intelligence, Machine Learning, and Digital Image Processing intrigued me the most and fueled my enthusiasm to contribute to this field. I aspire to be a leading contributor to new breakthroughs in machine learning and computer vision. I plan to pursue a Master’s degree in Data Science from a university abroad, where the program will help me materialize my long-cherished ambitions and connect with some of the brightest minds in the world. Following this, I aim to join a Ph.D. program to conduct research in artificial intelligence, machine learning, deep learning, data mining, and statistical modeling.

Y. Ahmed, M. N. Uddin, S. M. Masud, and M. H. Imam, "Design of an Arrhythmia Detection System Using Wearable PPG Sensor," 2019 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health (BECITHCON), Dhaka, Bangladesh, 2019, pp. 73-76

Conducted research on developing a heart rate monitoring system utilizing a low-cost PPG sensor for continuous heart rate monitoring, particularly for patients in rural areas with limited access to clinical facilities. This system aims to detect arrhythmias and alert the concerned person immediately via a GSM module and an alarm. The reliability of the PPG sensor-based readings was validated against the KardiaMobile data, an FDA-approved clinical-grade ECG device, showing promising results.

Research Interests

Machine Learning, Computer Vision

Data-driven modelling & optimization, Medical Imaging Analysis, Object Detection, Activity Recognition, Object Recognition, video surveillance and security (real-time video analysis, object tracking, and anomaly detection in surveillance systems), and video analytics.