Multimodal Representation for Robustness and Generalization in Biomedical Applications
Talk, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
Talks and presentations
Multimodal Federated Learning for Robust Lung Cancer Prognosis
Talk, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Bonn, Germany
A presentation on leveraging federated learning and multimodal data integration to enhance lung cancer prognosis while preserving patient privacy. Available here
Assessing Explainability in Deep Learning for Medical Image Analysis
Talk, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Bonn, Germany
A presentation on evaluating explainability methods in deep learning models for medical image analysis. Available here
Trustworthy Healthcare AI for Mental Health Risk Prediction
Talk, Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
A talk discussing the role of trustworthy healthcare AI in predicting mental health risks. Available here
Assessing Fusarium Oxysporum Disease Severity in Cotton Using Unmanned Aerial System Images and a Hybrid Domain Adaptation Deep Learning Time Series Model
Talk, Leibniz Institute for Agricultural Engineering and Bioeconomy, Potsdam, Germany
A talk on leveraging deep learning and domain adaptation techniques for assessing crop disease severity using aerial imagery. Available here
Causal Representation Learning
Talk, Computer Vision Colloquium, Osnabrueck University, Osnabrück, Germany
A talk on causal representation learning and its applications in computer vision and AI. Available here
Disentangled Speech Representation Learning via Self-Supervision
Poster Presentation, NeurIPS 2023, New Orleans, USA
A research poster presentation on novel techniques for learning interpretable and robust speech representations through self-supervision. Available here
Self-Supervised Learning of Speech Representation via Redundancy Reduction
Oral Presentation, KI 2023 – 46th German Conference on Artificial Intelligence, Berlin, Germany
An oral presentation on self-supervised learning methods for speech representation through redundancy reduction. Available here
Supervised Contrastive Representation Learning for Individual Recognition in the Wild
Talk, Language and Communication colloquium, Institute of Cognitive Science, Osnabrueck University, Germany, Building 50, Room 50/E07, Wachsbleiche 27, Osnabrueck, Germany
Talk title: “Supervised Contrastive Representation Learning for Individual Recognition in the Wild.” On-going reaching into the application of state-of-the-art deep learning techniques for speaker recognition in the wild.
Supervised Contrastive Deep Learning for Individual Recognition in Chimpanzees in the Wild
Talk, Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Germany, Virtual
Poster title: “Supervised Contrastive Deep Learning for Individual Recognition in Chimpanzees in the Wild “ This talked peered into the study of the origin of human language as a communicative tool. It narrowed down on Individual Recogntition (IR) – the ability of an individual (a receiver) to uniquely identify another individual (a signaler) based on signature cues, a ubiquitous practice of animals that live in fission-fusion systems. IR is crucial to startification of groups, formation of trust and behaviour direction towards others. This talk connect the problem of IR from the perpective of a receiver as an computational problem modelled using deep learning.
Supervised Contrastive Deep Learning for Individual Recognition in Chimpanzees in the Wild
Talk, Language and Communication colloquium, Institute of Cognitive Science, Osnabrueck University, Germany, Building 50, Room 50/E07, Wachsbleiche 27, Osnabrueck, Germany
Workshop Title: BRIDGING THE TECHNOLOGICAL GAP – SPREADING TECHNOLOGICAL INNOVATIONS IN THE STUDY OF THE HUMAN AND NON-HUMAN MIND
Date: JULY 31ST, 2022 – AUGUST 6TH, 2022
URL: https://www.primate-cognition.eu/de/veranstaltungen/bridging-the-technological-gap-workshop.html —
Transfer Learning for the Detection and Classification of traditional pneumonia and pneumonia induced by the COVID-19 from Chest X-ray Images
Talk, African Institute of Mathematical Sciences (AIMS), Rwanda, AIMS Centre Remera, Kigali, Rwanda
[MSc. Mathematical Sciences thesis] Transfer Learning for the Detection and Classification of traditional pneumonia and pneumonia induced by the COVID-19 from Chest X-ray Images. Available here
Big Data for Healthcare Analytics
Talk, African Institute of Mathematical Sciences (AIMS), Rwanda, AIMS Centre Remera, Kigali, Rwanda
Deep Transfer Learning for Magnetic Resonance Image Multi-class Classification. Available here
African Accents International (AAI-SL): Engaging youths, transforming lives
Talk, African Institute of Mathematical Sciences (AIMS), AIMS Centre Remera, Kigali, Rwanda
African Accents International (AAI-SL): Engaging youths, transforming lives. Available here
Big Data for Healthcare Analytics
Talk, University of Dhaka, Department of Computer Science and Engineering, Bangabandhu International Conference Center, Dhaka, Bangladesh
A talk on prospects of Big Data for Healthcare Analytics. Available here
Detecting malaria using a deep convolutional neural network
Talk, University of Dhaka, Department of Computer Science and Engineering, Department of Computer Science and Engineering, Dhaka, Bangladesh
A talk on Detecting malaria using a Deep Residual Convolutional Neural Network. Available here
Introduction to the Internet
Talk, University of Makeni, Department of Computer Science, Sylvanus Koroma Campus Yoni, Makeni, Sierra Leone
A lecture on the foundations of Internet Programming, full-stack web application development and mastering.Available here