Profile – Bangladesh University

Experience

Academic Qualifications:
1. B.Sc in Electrical and Electronic Engineering, Khulna University of Engineering and Technology.
2. HSC (Science), Dinajpur Govt. College.
3. SSC (Science), Dinajpur Zilla School.

Professional Experience:
1. Lecturer, Department of Computer Science and Engineering, Bangladesh University. From Jan 2025 to till date.

Research

Area of Interest

1. Languages: Python, C++, HTML
2. Robotics: Arduino, Raspberry Pi
3. Design and Simulation: AutoCAD, MATLAB, Quartus(VLSI), Proteus
4. Graphics and Editing Software: Origin Pro, Adobe Photoshop, Illustrator

Research Work

Projects:
1. Unarmed Aerial Vehicle(UAV) payload drop mechanism.
a. Developed an innovative UAV-based solution for controlling mosquito-borne diseases.
b. Integrated a Customized Rotational Dropping Mechanism (HARDM) for precise deployment.
c. Implemented advanced image processing algorithms to autonomously identify mosquito breeding sites.
d. Technology Used : KK2.1.5 flight control, OpenCV, Arduino,

2. Development of IR Modulated Circuit System for Data Transmission |
a. Integrated a 38 kHz carrier frequency modulation for secure and efficient data transfer.
b. Designed and implemented both transmitter and receiver circuits using Arduino and IR components.
c. Designed 3D PCB models for both IR transmitter and IR receiver.
d. Technology Used:Arduino Uno, Proteus, EasyEDA.

3. Project on Mars Rover Control System Design |
a. Enabled long-range connectivity with CPE, providing wireless communication for outdoor operations.
b. Employed 5.8GHz video transmitter and receiver for reliable video communication and FPV applications.
c. Technology used: Raspberry Pi, Arduino Mega.

Publications

1. An IoT Enabled UAV Platform for Real Time Patient Health Monitoring and Medical Response – IEEE Explore (2026) Indexed: Scopus.
2. Development of a Non-Invasive Multispectral Glucose Measurement System: Integrating Optical Sensor and VisNIR Spectroscopy – IEEE Explore (2025) Indexed: Scopus
3. Non-Invasive Blood Glucose Monitoring with Machine Learning Enhanced Transmittance Spectroscopy – ACS Omega (under review)
4. Development of a Non-Invasive Glucose Monitoring System: Integrating VIS-NIR Spectroscopy and Optimized Machine Learning – Undergraduate Thesis

Siam Sadik Nayem