Electrical and Electronic Engineering
Afsana Sharmin Shanta joined the Department of Electrical and Electronic Engineering at Jamalpur Science and Technology University as a Lecturer in April 2026. She completed both her B.Sc. and M.Sc. in Electrical and Electronic Engineering from University of Dhaka.
Her research interests include electrical and biomedical signal processing, as well as the application of machine learning techniques in biomedical signal analysis. She is particularly interested in integrating intelligent computational methods with healthcare-related signal processing systems.
Prior to joining the university, she worked as a Trainee Engineer at Huawei and served as a Lecturer at Notre Dame University Bangladesh. She has also actively participated in various engineering and technology-related events and activities.
| Degree Name | Group/Major Subject | Board/Institute | Country | Passing Year |
|---|---|---|---|---|
| MSc | EEE | University of Dhaka | Bangladesh | 2021 |
| BSc | EEE | University of Dhaka | Bangladesh | 2019 |
| HSC | Science | Shaheed Bir Uttam Lt Anwar Girls’ College, Dhaka | Bangladesh | 2015 |
| SSC | Science | Tejgaon Government Girls' High School, Dhaka | Bangladesh | 2013 |
| Title | Organization | Location | From Date | To Date |
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Research Interest
| Subject | Description | Research Interest (Goal, Target Indicator) |
|---|---|---|
| Biomedical Signal Processing, Image Processing, IoT-based Healthcare System Design, Machine Learning, and Neural Networks for Healthcare Applications | Research focuses on biomedical signal and medical image processing, IoT-based healthcare system development, and AI-driven healthcare technologies. Current interests include intelligent health monitoring systems, disease diagnosis and prediction models, wearable healthcare devices, and deep learning approaches for medical data analysis and automation. | Developing intelligent, efficient, and reliable healthcare technologies through biomedical signal analysis, medical image processing, IoT-enabled monitoring systems, machine learning, and neural network models, with a focus on real-time healthcare monitoring, automated diagnosis, predictive analytics, and smart clinical decision-support systems. |
Project/Research Supervision
| Level of Study | Title | Supervisor | Co-Supervisor(s) | Name of Student(s) | Area of Research | Current Completion |
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Project/Research Work
| Subject | Project Name | Source of Fund | From Date | To Date | Collaboration |
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| SL | Collaboration & Membership Name | Type | Membership Year | Expire Year |
|---|---|---|---|---|
| 1 | IEEE | Graduate Student | 2026 |
Journal :
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Conference :
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