I specialize in AI-driven software development, deep learning, and medical image processing, with a strong focus on explainable AI (XAI), feature selection, and scalable AI architectures. My expertise extends to bioinformatics, AI-powered IoT systems, and intelligent automation, where I build high-performance AI applications for real-world challenges.
Currently, I am working as an AI Software Engineer at DIU AI Research Lab, where I develop AI-powered solutions, manage research-driven projects, and optimize AI systems for scalability and efficiency. Additionally, I serve as a Research Assistant at the Centre for Advanced Machine Learning and Applications (CAMLAs), contributing to cutting-edge research in medical AI, computational biology, and feature selection techniques.
With a deep background in software engineering, I develop scalable AI-driven platforms using FastAPI, PyTorch, and React, optimizing AI inference pipelines, real-time data processing, and cloud-based AI systems. My work integrates computer vision, medical AI, and feature engineering to improve model interpretability and efficiency.
 Medical AI & Bioinformatics |
AI for oncology research, whole-slide image (WSI) processing, and AI-assisted diagnostics. |
|---|---|
 Software Development & AI Systems |
Architecting scalable AI software solutions with FastAPI, React, and cloud services. |
 AI & IoT Integration |
Developing AI-powered IoT systems for smart automation and real-time analytics. |
| 🤖 AI/ML | 🔌 IoT | 🔬 Research | 💻 Development |
|---|---|---|---|
| Computer Vision | Embedded Systems | Medical Imaging | Full-stack Apps |
| Deep Learning | Sensor Networks | Bioinformatics | Cloud Solutions |
| Neural Networks | Edge Computing | Algorithm Design | Mobile Development |
| NLP | Smart Agriculture | Data Analysis | API Integration |
| # | Achievement | Year |
|---|---|---|
| 1 |
People's Choice Award 3MT (3-minute thesis) competition organized by Daffodil International University |
2025 |
| 2 |
3rd Poster Presentation Award DIU-DoR Poster Presentation 2025 |
2025 |
| # | Paper | Year |
|---|---|---|
| 1 | F. R. D. Cruze, A. Khatun, M. F. Hosen, M. S. H. Mollah, M. N. Kader and M. S. Uddin, "Leveraging Machine Learning to Uncover Molecular Pathways and Candidate Drugs in Ovarian Cancer and Polycystic Ovary Syndrome," 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong, Bangladesh, 2025, pp. 1-6, doi: 10.1109/ECCE64574.2025.11013839. | 2025 |
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| 2 | F. R. D. Cruze, A. Khatun, M. F. Hosen, M. S. H. Mollah, M. N. Kader and M. S. Uddin, "Leveraging Machine Learning to Uncover Molecular Pathways and Candidate Drugs in Ovarian Cancer and Polycystic Ovary Syndrome," 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong, Bangladesh, 2025, pp. 1-6, doi: 10.1109/ECCE64574.2025.11013839. | 2025 |
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