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Oct 07, 2026 Received the Lambda AI Research Grant for supporting large-scale multimodal biomedical AI research for infectious diseases.
Sep 14, 2026 Our manuscript titled “A Multimodal Explainable Deep Learning Framework for Alzheimer’s Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data” got accepted for publication in Springer Nature Cognitive Computation.
Sep 02, 2026 Our manuscript titled “From Visual Saliency to Anatomical Explanation: Generating Textual Diagnostic Reports from Brain MRIs with Saliency-Grounded LLMs” got accepted for publication in Springer Nature BioData Mining.
Aug 07, 2026 I am excited to be serving as program chair of the Pan-African Artificial Intelligence and Smart Systems Conference (PA-AISS 2026) taking place at the University of Technology, Kingston, Jamaica October 13-16, 2026.
Jul 21, 2026 My research project was awarded a Google Cloud Research Grant to fully fund our high-performance academic computing, storage, and data analytics infrastructure for the next year.
May 26, 2026 Our Tabular Foundation Model manuscript titled “Few-shot Learning with Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift” submitted to BioData Mining.
May 19, 2026 Our systematic review title “Transformers for 3D Medical Image Analysis: A Systematic Review of Architectural Innovations, Performance, and Clinical Applications,” got accepted at Artificial Intelligence Review.
Apr 20, 2026 Our LLM-Guided XAI for Medical Image Diagnostics manuscript titled “Bridging Visual Saliency and Large Language Models for Self-explainable Deep Learning in Medical Imaging” submitted to BioData Mining.
Apr 16, 2026 Our AI in NTD Consortium manuscript titled “Artificial Intelligence in Neglected Tropical Diseases: Current Applications, Challenges, and Opportunities” submitted to npj Digital Medicine.
Dec 24, 2025 Completed “ Evaluations of AI Applications in Healthcare by Stanford Online” with a focus on AI techniques and their applications in medical diagnosis. Certificate available at here.
Dec 24, 2025 Completed “ AI Applications in Healthcare Specialization by Stanford Online” with a focus on AI techniques and their applications in biomedicine. Certificate available at here.
Dec 18, 2025 Completed “Fundamentals of Machine Learning for Healthcare by Stanford Online” with a focus on machine learning techniques and their applications in healthcare. Certificate available at here.
Dec 17, 2025 Completed “Introduction to Clinical Data by Stanford Online” with a focus on clinical data types, sources, and applications in healthcare. Certificate available at here.
Dec 06, 2025 Completed “Introduction to Healthcare by Stanford Online” with a focus on healthcare systems, quality improvement, and patient safety. Certificate available at here.
Nov 19, 2025 PhD Thesis Published in the collection: FB08 - E-Dissertations: “Disentangled Representation Learning in Speech and Vocalization
Aug 28, 2025 Gave a talk on Artificial Intelligence and Its Role in Shaping Our Future at the University of Makeni Computer Science Alumni Forum.
Jun 27, 2025 Successfully defended my PhD thesis at the Institute of Cognitive Science, Osnabrück University.
Mar 30, 2025 Made a first commit to a Pytorch-based XAI for Dementia using 3D CNN and NIFTI Data
Mar 04, 2025 A systematic review of low-rank and local low-rank matrix approximation in big data medical imaging” published for publication in Springer Nature Neural Computing and Applications.
Feb 19, 2025 Talk on “Multimodal Federated Learning for Robust Lung Cancer Prognosis” at the Fraunhofer Institute for Algorithms and Scientific Computing (SCAI).
Jan 31, 2025 Completed the MUST Deep Learning Bootcamp, North-West University, South Africa MUST Deep Learning Bootcamp 2025.
Jan 22, 2025 PhD Dissertation Submitted and approved for examination and graduation: “Disentangled Representation Learning in Speech and Vocalization”.
Jan 20, 2025 The Association of Commonwealth Universities Case Study on “Advancing artificial intelligence for healthcare and developing human capital in low-resource settings” published in ACU Research.
Jan 11, 2025 Learning Disentangled Speech Representations” preprint published in arXiv:2311.03389v4.
Dec 16, 2024 Talk on “Trustworthy Healthcare AI for Mental Health Risk Prediction” at the Neurobiology Research Unit,Copenhagen University Hospital
Dec 10, 2024 Talk on “Assessing Explainability in Deep Learning for Medical Image Analysis” at the Fraunhofer Institute for Algorithms and Scientific Computing (SCAI).
Nov 11, 2024 Launched SyncSpeech Datasets: A large-scale collection of synthetic speech datasets for speech representation learning. Available at SyncSpeech Datasets.
Jul 10, 2024 Talk on “Assessing fusarium oxysporum disease severity in cotton using unmanned aerial system images and a hybrid domain adaptation deep learning time series model” at the Leibniz Institute for Agricultural Engineering and Bioeconomy
Jun 22, 2024 Saliency-driven explainable deep learning in medical imaging: bridging visual explainability and statistical quantitative analysis” published in BioData Mining 17, 18.
Mar 27, 2024 Bridging the Gap: Exploring Interpretability in Deep Learning Models for Brain Tumor Detection and Diagnosis from MRI Images” published in MDPI Information 2024, 15(4), 182.
Mar 21, 2024 Got accepted to attend in-person the Deep Learning + Reinforcement Learning (DLRL) Summer School 2024 by CIFAR and the Vector Institute in Toronto, Canada.
Mar 13, 2024 Talk on “Causal Representation Learning” at the Computer Vision Colloquium, Osnabrueck University.
Feb 16, 2024 Learning Disentangled Audio Representations through Controlled Synthesis” accepted for oral presentation at ICLR Tiny Papers 2024.
Feb 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.
Feb 12, 2024 Bridging the Gap: Exploring Interpretability in Deep Learning Models for Brain Tumor Classification from MRI Images” submitted to MDPI Information Special Issue: Deep Learning in Medical Image Analysis: Foundations, Techniques, and Applications.
Dec 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.
Nov 01, 2023 Learning Disentangled Speech Representations” accepted for poster presentation at New in ML, NeurIPS 2023.
Oct 17, 2023 Co-organizing with Ulf Krumnack and Lukas Niehaus a Seminar: Deep Representation Learning (Winter 2023/24) at Osnabrück University.
Sep 23, 2023 Self-Supervised Learning of Speech Representation via Redundancy Reduction” extended abstract published at Gesellschaft für Informatik e.V..
Aug 01, 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.
Jul 26, 2023 Self-Supervised Learning of Speech Representation via Redundancy Reduction” accepted for oral presentation at KI 2023 – 46th German Conference on Artificial Intelligence, Berlin, Germany.
Jun 13, 2023 submitted a manuscript to PLOS One A Mathematical Framework for Understanding Recognition Systems.
Sep 16, 2022 Launched the Graduate Assistance Initiative Network (GAIN) globally with 130+ attendees.
Sep 11, 2022 Attended Mediterranean Machine Learning school, Università Milano Bicocca, Milan, Italy.
Aug 06, 2022 Co-organized with Viktoria Zemliak the “Bridging the Gap between Biological and Artificial Neural Networks” at the (Research Training Group (RTG) in Computational Cognition).
Jul 29, 2022 Attended and presented a poster at the Bridging the technological gap – spreading technological innovations in the study of the human and non-human mind at the German Primate Center in Göttingen, Germany.
Jul 11, 2022 Participated in the Neuromatch Academy: Deep Learning intensive hands-on training.
Aug 16, 2021 Transfer Learning for the Detection and Diagnosis of Types of Pneumonia Including Pneumonia Induced by the COVID-19 from Chest X-Ray Images” published in MDPI Special Issue on Machine Learning Applications for COVID-19 and Its Complications: Screening, Diagnosis, Treatment, and Prognosis.
Jun 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 comprises 5,285 T1-weighted contrast-enhanced brain MRI images belonging to 38 categories. Available here Brain MRI Dataset.