MSc Data Science graduate building machine learning systems at the intersection of research and real-world impact — from wireless network optimisation to medical image analysis.
I'm a data scientist from Dar es Salaam, Tanzania, with an MSc in Data Science (First Class) from Chandigarh University, India. My work sits at the intersection of machine learning research and real-world data analysis.
I've published research on deep learning for wireless networks, built computer vision systems for medical diagnostics, and delivered data insights across telecoms, consulting, and engineering sectors.
Currently exploring PhD opportunities in machine learning and AI while working as a data and systems consultant in Dar es Salaam.
Automated classification of diabetic retinopathy severity from retinal fundus images using ResNet18 transfer learning in PyTorch — helping clinicians identify DR severity from images in seconds rather than hours.
A deep learning model that automatically identifies wildlife species — buffalo, elephant, rhino, and zebra — from camera trap images in Serengeti National Park, built with EfficientNet-B0 transfer learning to support anti-poaching and conservation monitoring efforts.
A comprehensive benchmarking study comparing CNN, RNN, and SVM architectures for wireless network intrusion detection across NSL-KDD, CICIDS2017, and KDDCup99 datasets. Demonstrated CNN accuracy of 99.4% on intrusion detection tasks, with analysis of supervised, unsupervised, and deep learning approaches for real-world network optimisation.
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