My research interests include Disentangled Representation Learning, Causality, Explainability, Computational Entrepreneurship, Mathematical Modelling particularly in building end-to-end systems with high socio-technical impacts. [Curriculum Vitae] [Google Scholar]
February 16, 2024; “Learning Disentangled Audio Representations through Controlled Synthesis” accepted for oral presentation at ICLR Tiny Papers 2024.
February 15, 2024; “Understanding Self-Supervised Learning of Speech Representation via Invariance and Redundancy Reduction “ accepted for oral presentation at MDPI Information 2024, 15(2), 114.
December 10, 2023; Attended NeurIPS 2023 in New Orleans, USA where Presented research poster on disentangled speech representation learning via self-supervision. Sharing novel techniques for learning interpretable and robust speech representations.
September 23, 2023; “Self-Supervised Learning of Speech Representation via Redundancy Reduction” extended abstract published at Gesellschaft für Informatik e.V..
August 1, 2023; “Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images” published in arXiv preprint arXiv:2208.00953.
June 15, 2021; Published a dataset that was curated in collaboration between the Computer Science and Engineering Department, University of Dhaka and the National Institute of Neuroscience, Bangladesh. It comprise 5,285 T1-weighted contrast- enhanced brain MRI images belonging to 38 categories. Available here Brain MRI Dataset.