Professional Summary
Computer Science graduate and MSc researcher specializing in Deep Learning and Neural Network Architectures. Experienced Programmer with strong expertise in Python, TensorFlow, and PyTorch, currently managing large-scale Learning Management Systems (LMS) for the ICT Division. Proven track record in full-stack development (Django/PHP) and co-founding technical ventures focused on AI and digital solutions.
Work Experience
- Lead the development and enhancement of the Learning Management System (LMS), focusing on scalability and performance optimization using PHP in frontend, Python (Django) in the backend and MySQL for database management.
- Collaborate directly with stakeholders to translate business requirements into technical specifications and actionable code.
- Conduct code reviews and oversee system testing to ensure zero-downtime deployment and high data integrity.
- Collaborated with the core development team to design and implement key modules of the Learning Management System application.
- Improved user experience (UX) by assisting in frontend development and responsive design implementation.
- Performed rigorous unit testing and debugging to ensure the platform met project specifications.
- Assisted the IT department in daily operations, hardware maintenance, and network troubleshooting.
- Gained hands-on experience in software development lifecycles (SDLC) and HTML, CSS, JavaScript, PHP and MySQL.
- Translated theoretical knowledge into practical solutions by supporting senior developers on live projects.
Academic Projects & Research
Retrieval-Augmented Generation (RAG) System for Bengali Documents: Developed a pipeline to extract contextual information using OCR and NLP.
Student Attendance & Behavior Monitoring via Facial Recognition: Engineered a real-time automated attendance system using OpenCV.
Investigating Reliability in Conversational AI Systems: Analyzed hallucination rates to determine reliability of AI chatbots.
Handwritten Bangla Character Recognition: Conducted comparative analysis of Neural Network architectures using TensorFlow/PyTorch.