Projects
Selected technical projects exploring quantum machine learning, quantum algorithms, computer vision, and practical AI systems.
Developed a hybrid quantum neural network workflow for handwritten-digit classification. The project combines classical deep-learning tools with quantum technology from Classiq to explore quantum-enhanced image classification.
The work investigates how quantum circuits can be integrated into a machine-learning pipeline, including data preparation, model design, training, and evaluation.
A learning-oriented notebook covering quantum data encoding, qubit mapping, variational quantum eigensolvers, and quantum phase estimation. The project documents concepts and implementations used to develop practical quantum-computing skills.
Research and experimentation on evaluating YOLO architectures for vehicle detection in complex urban environments in Bangladesh. The project considers practical challenges such as varied traffic conditions, cluttered scenes, and visual complexity.
These projects support my broader interests in quantum computing, quantum software engineering, autonomous systems, trustworthy AI, and language-model evaluation. Visit the research page for publications and research areas.