HAQUE MD AMDADUL

• Ph.D. Researcher at Nanjing University of Information Science and Technology specializing in Electronic and Information Engineering, focusing on sensor measurement and control circuits. Holds a master’s degree from SWUST, with expertise in deep learning (CNN), data analysis, and project management. Currently developing and testing a naturally ventilated radiation shield for ground temperature monitoring. Proficient in Python, with a proven track record of delivering high-quality research outcomes and effective communication skills.

• Participated in international academic and research programs in China.
• Conducted research on battery modeling, sensor circuits, and natural ventilation systems.
• Volunteered in mentoring junior students and fostering cross-cultural academic exchange.
• Engaged in collaborative lab research projects and publication efforts.

• Recipient of NUIST Research Grant for Ph.D. project on natural ventilation systems.
• Successfully defended MSc dissertation at SWUST with distinction (73 marks).
• Published research paper: High-order Electrical Equivalent Circuit Modeling Research For Accurate Lithium-Ion Battery State Prediction.
• Achieved 85% academic performance in MSc program (1190/1400 marks).
• Recognized for quality supervision work at Ericsson and Zass Telecom Ltd.

• Neural Network and Deep Learning – March 2021
  (Artificial Intelligence, Backpropagation, Deep Learning, Python)
• Convolutional Neural Network in TensorFlow – June 2020
  (Image data handling, overfitting prevention, augmentation, dropout, transfer learning)
• English Proficiency Training – FM Method Education, Dhaka (2016–2017)
• Advanced Research Methodology Training – NUIST
• English Proficiency Certificate – NUIST (medium of instruction)
• Electrical Technical Training – Dhaka Electric Supply Company (2015–2016)

I am a passionate researcher in sensor systems, machine learning, and electronics. With international academic experience in China and a strong practical background in telecom engineering, I aim to contribute to cutting-edge innovations that improve sustainability and smart monitoring. I value teamwork, innovation, and continuous learning.