Senior Lecturer & Researcher
Specializing in Explainable AI (XAI) and Multimodal AI (MMAI) for healthcare diagnostics and analytics.
Exploring the intersection of AI, healthcare, and human-centered computing
Developing AI-powered diagnostic systems for disease detection, medical imaging analysis, and clinical decision support to improve patient outcomes and healthcare delivery.
Applying machine learning to environmental monitoring, climate modeling, ecosystem conservation, and sustainable resource management for a greener future.
Creating transparent AI systems that clinicians and users can trust. Focus on interpretable models for critical applications with clear reasoning and decision pathways.
Integrating imaging, text, clinical records, and sensor data for complete analysis. Building systems that use diverse data modalities for deeper insights.
Analyzing satellite, drone, and aerial imagery for land use classification, disaster monitoring, agricultural assessment, and environmental change detection.
Researching efficient sorting, searching, and optimization algorithms. Exploring novel data structures and computational approaches for solving complex problems.
2024 IEEE Engineering in Medicine & Biology Society (EMBC), Annual International Conference (Accepted for poster presentation)
A poster presentation introducing a mobile health platform using relational agents to address the dengue crisis in Bangladesh, focusing on preventive measures and early intervention.
2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), Singapore
This paper explores advancements in Bangla speech emotion recognition using deep learning techniques with cross-lingual validation to improve emotion detection in multilingual contexts.
36th Australasian Joint Conference on Artificial Intelligence (AJCAI), AI 2023: Advances in Artificial Intelligence, Perth, WA, Australia. Lecture Notes in Computer Science, vol 14430. Springer, Cham
A machine learning approach for predicting Graft-versus-Host Disease outcomes before stem cell transplantation, improving patient risk assessment.
Leading research on enhancing dialect detection through AI and Machine Learning techniques, contributing to the preservation and understanding of Bangladesh's rich linguistic heritage.
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