Chittagong University of Engineering and Technology | Bangladesh
Aditta Chowdhury is an electrical and electronic engineering researcher and academic whose work focuses on advancing biomedical signal processing, embedded systems, and sustainable energy technologies. He holds both a Bachelor of Science and a Master of Science in Electrical and Electronic Engineering from the Chittagong University of Engineering and Technology, graduating with top academic distinction. His professional journey includes teaching and research roles in reputed engineering institutions, where he has contributed to curriculum development, laboratory instruction, and collaborative research. His research experience spans FPGA-based biomedical signal processing, photoplethysmogram-driven cardiovascular and metabolic disease detection, multimodal physiological signal analysis, plasmonic biosensing, microgrid feasibility assessment, and low-power VLSI system design. He has published extensively in high-impact journals and international conferences, demonstrating expertise in hardware–software co-design, machine learning applications in healthcare, and emerging sensor technologies. His work has resulted in several innovative solutions, including cardiovascular disease classifiers, hypertension detection systems, EOG-based eye-movement processors, and microgrid sustainability assessments. He has received multiple academic scholarships and awards recognizing his exceptional academic performance and research accomplishments. Driven by a commitment to impactful scientific contribution, he aims to continue developing intelligent, efficient, and accessible engineering solutions through interdisciplinary research and innovation.
Featured Publications
Chowdhury, A., Das, D., Eldaly, A.B.M., Cheung, R.C.C., & Chowdhury, M.H. (2024). “Photoplethysmogram-based heart rate and blood pressure estimation with hypertension classification.” IPEM–Translation, 100024.
Joy, J.D., Rahman, M.S., Rahad, R., Chowdhury, A., & Chowdhury, M.H. (2024). “A novel and effective oxidation-resistant approach in plasmonic MIM biosensors for real-time detection of urea and glucose in urine for monitoring diabetic and kidney disease.” Optics Communications, 573, 131012.
Chowdhury, A., Das, D., Hasan, K., Cheung, R.C.C., & Chowdhury, M.H. (2023). “An FPGA implementation of multiclass disease detection from PPG.”
IEEE Sensors Letters, 7(11), 1–4.
Islam, M.A., Chowdhury, A., Jahan, I., & Farrok, O. (2024). “Mitigation of environmental impacts and challenges during hydrogen production.”
Bioresource Technology, 131666.
Chowdhury, A., Das, D., Cheung, R.C.C., & Chowdhury, M.H. (2023). “Hardware/software co-design of an ECG–PPG preprocessor: A qualitative and quantitative analysis.”
Proceedings of the 2023 International Conference on Electrical, Computer and Communication Engineering, 9.