Principal Investigator: 

​​Dr Raqibul Mostafa

Dean, School of Science and Engineering

Professor, Department of EEE

United International University

Co-Supervisor:

• Dr Ahsan Habib Khandoker,

Associate Professor, 

Dept. of Biomedical Engineering

Khalifa University, UAE

• Dr Khawza Iftekhar Uddin Ahmed,

Professor, Department of EEE

United International University

• Dr M Nurul Akhtar Hasan,

FCPS, Pediatric Intensivist & Associate Professor, 

Pediatric & Congenital Cardiac Program, Children & Women Cardiac Unit, 

National Heart Foundation Hospital & RI

Project:

1. Development of Low-Cost Technology for Remote Pediatric Cardiac Consultation

• Design a data collection method and check usability. 

• Responsible for preprocessing the signal for analysis.

• Develop a CHD classification model using Machine Learning.

Collaborate:

• National Heart Foundation Hospital and Research Institute

• Bangladesh Shishu Hospital and Institute

Funded By:

• Institute of Advanced Research (IAR), United International University.

Supervisor: 

Dr Tanzilur Rahman

Assistant Professor

Dept. of Electrical and Computer Engineering

North South University

Responsibilities:

• Perform original research.

• Use various sources for background study, including related database publications.

• Work under tight deadlines.

• Collaborate on other projects as needed.

• Maintain a Research Notebook (Code, Data, so on).

• Responsible for proposals and report writing.

Project:

1. Continuous and Real-Time Monitoring of ECG

   • Design an IoT-enabled device for acquiring ECG signals.

   • Develop an algorithm to extract vital signs.

   • Develop the model to classify abnormalities of ECG signals.

2. Measure Glucose level using Smartphone Camera

   • Collect data with ground-level truth.

   • Develop the Machine Learning model for measuring glucose levels using a smartphone with the lowest standard error of prediction (SEP) at 17.02 mg/dL.

3. Transmission electron microscopy (TEM) Virus Image Classification

   • Developed a Deep Learning model for 14 virus classifications

   • Used transfer learning using pretrained model InceptionV3

   • Achieved 99.27% of accuracy on test data.

4. Smart Traveler Assistant App

   • Develop an algorithm to remove the noise of sensor data.

   • Analyze sensor data to develop Smart Traveler Assistant App.

5. Analyze Green Tea effects

   • Develop a system to acquire ECG and PPG signals using NI-DAQ USB-6001.

   • Verify signals to PAT analysis.

   • Analyze signals to extract vital signs.

Funded By:

1. Worked on Bangladesh Govt. ICT Ministry fund.

2. Worked on North South University research fund NSU-CTRG.

Responsibilities:

• Assist subject Electrical Circuits II and counsel students during office hours.

• Evaluate the exam script and proctoring in the exam hall.

• Created homework, quizzes, exams, and solutions

• Graded quizzes and exams

• Gave recitations one session per week

• Held office hours on a regular basis of 8 hours per week and by appointment