Universal Exam Proctoring System

AI-powered platform for monitoring and verifying exam candidates in real time. It combines a FastAPI backend, a dedicated face recognition service built on InsightFace, a React + Vite dashboard, and a live video streaming layer via MediaMTX, all orchestrated through Docker. The AI worker handles face detection, pose estimation, and identity verification by comparing candidate faces against stored embeddings using pgvector, with tunable thresholds for how strict the verification needs to be. Redis handles caching and task queuing between services, while the dashboard gives proctors a live view of the entire session. The whole system is designed to run anywhere Docker runs, making deployment straightforward without any local Python or Node setup required.

FidelGen: Visual Amharic Text Generation Using a Multi-Conditional Diffusion Model

A multi-conditional diffusion model for generating visually accurate Amharic text in images. Built on PyTorch and the Hugging Face diffusers ecosystem, it tackles the unique challenges posed by Ge'ez script, whose complex syllabic structure is largely unsupported by existing text-to-image systems trained predominantly on Latin-based writing. By conditioning generation on multiple signals, the model learns to produce legible, faithful renderings of Amharic characters, with direct applications in document synthesis, OCR dataset generation, and digital accessibility for Amharic speakers.

Drought Prediction Using Hybrid CNN-LSTM

Designed a hybrid CNN-LSTM deep learning model in Python combining spatial feature extraction with temporal sequence modeling to forecast drought occurrences across Ethiopian regions. Preprocessed and structured multi-source climate data into training-ready sequences, applying feature engineering and normalization to improve model reliability.

YenePay Python SDK

An open source library that lets developers add YenePay as a payment method in a Python application with a few lines of code. Rather than hand rolling HTTP calls and signature checks against the payment gateway, a developer creates a client with their merchant credentials, describes the items being sold, and gets back a checkout link to send the customer to. I designed and built the library from scratch, shaping the public API around what felt natural to a Python developer instead of mirroring the raw gateway endpoints. That meant modelling items, carts and checkouts as plain objects, wrapping payment verification and instant payment notifications behind a small interface, and validating inputs early so mistakes surface at the call site rather than as a failed transaction. I set up the full open source workflow around it as well, with automated tests and linters running on every change, hosted documentation, and continuous publication to PyPI so a release is a tag away. Built with — Python, pytest, Sphinx, GitHub Actions, PyPI

ASTU Inventory

A web application for organizations that own a lot of equipment and need to know where all of it is. It replaces paper ledgers and spreadsheets with a single system that keeps a live record of what is in stock, who is holding what, and where every item sits across stores and laboratories. I built this as a full stack developer, carrying it from requirements gathering and system design through to a live deployment. On the back end I designed the relational schema and implemented the application in Django over PostgreSQL, adding role based authorization, the borrow request engine, spreadsheet import and export for reporting, and stock analytics. The dashboard and user facing pages I wrote from scratch in HTML, CSS, JavaScript and Bootstrap rather than adapting a theme. I also owned deployment, from provisioning and securing the server to hosting it behind a domain, with continuous integration running tests and linters on every change. Built with — Python, Django, PostgreSQL, JavaScript, Bootstrap, Gunicorn, Sentry, Git, GitHub Actions

Solar Farm Insight — Solar Energy Data Analysis and Dashboard

A project that analyzes solar farm data from Benin, Sierra Leone, and Togo to identify trends in solar radiation, temperature, and wind conditions. It includes statistical calculations, data quality checks, and visualizations to evaluate operational factors such as cleaning efficiency, delivered through an interactive Streamlit dashboard. The objective is to provide actionable insights to improve solar energy performance and operational sustainability. I built the project end to end, from the initial data work through to the deployed dashboard. That began with profiling the raw measurements and dealing with what real sensor data brings with it, including missing readings, implausible values and outliers caught through statistical flagging. Built with — Python, pandas, Streamlit, Matplotlib, pytest, GitHub Actions

Competitive Programming — Algorithm and Data Structure Practice Archive

A personal archive of over 220 solved competitive programming problems from LeetCode, HackerRank, Codeforces and GeeksforGeeks, organized by platform and difficulty. Solutions are written primarily in Python with a portion in C++, covering the standard range of algorithmic topics from arrays and strings through trees, graphs and dynamic programming. I maintain the repository as ongoing practice in algorithms and data structures, solving problems across both an interpreted and a compiled language to keep the underlying reasoning independent of a single toolchain. Each solution is committed with its problem metadata so the archive stays searchable by topic and difficulty over time. Built with — Python, C++, JavaScript, Git