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Schedule Interview NowMy name is Onisa M. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Deep Learning, PyTorch, LLM Prompt Engineering, OpenCV, etc.. I hold a degree in Associate's degree. Some of the notable projects I've worked on include: Ads Impression Estimation Via Geo Spatial data, Computational Analysis of Drug Efficacy in Murine Models, Transformer-based Crowd Counting Model, Advanced Biometric Verification System for KYC, AI-Powered Vehicle Counter with Dynamic Region of Interest, etc.. I am based in Dar es Salaam, Tanzania. I've successfully completed 7 projects while developing at Softaims.
I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.
My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.
I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.
Main technologies
5 years
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1 Year
4 Years
Potentially possible
ATG Properties LLC
Developed a scalable system to estimate ad impressions for e-bike advertisements in urban areas. Processed real-time movement data every 10 seconds, using geospatial foot traffic scores to calculate v
The project focuses on analyzing drug efficacy in murine models using computational techniques. It involves segmenting specific regions where the drug interacts with biological tissues, typically thro
This project implements a transformer-based model to estimate crowd density in images. The model leverages self-attention to capture both local and global features, enabling accurate crowd counting ev
BioVerify is a facial recognition and liveness verification system for KYC processes. This project includes a Flask backend for processing identity images and verifying live multi-pose facial scans
Developed a Python-based system for automated vehicle counting from video footage. The application allows users to dynamically draw lines or define regions of interest on any road or intersection, reg
Associate's degree in Mechatronics Engineering
2021-01-01-2023-01-01