I worked as a Computer Vision Engineer at the Ethiopian Artificial Intelligence Institute. My primary responsibilities involved:✭ Having technical discussions with clients ✭ Working with skilled software engineers to develop and implement AI solutions ✭ Collaborating with a team of scientists and engineers to create novel AI methods, approaches, and prototype systems. ✭ Writing proposals, reports, and research papers and pursuing novel AI. During my stay at EAII, I have accomplished:✭ Published an article titled ”Lightweight Multireceptive Field CNN for 12-Lead ECG Signal Classification” with a 12% increase in the f1 score and with a smaller number of parameters.✭ Developed a deep learning model with 98% accuracy for detecting Tuberculosis from Chest X-ray.✭ Developed an ECG Annotation tool that assisted in automating the data annotation process for a project involving diagnosing heart disease using explainable AI from ECG signals.

In my role as a machine learning engineer, I am actively engaged in leveraging Large Language Models (LLM) to extract valuable information from diverse documents. This involves the development of sophisticated algorithms and models aimed at enhancing information extraction accuracy and efficiency.My responsibilities extend beyond the mere implementation of machine learning models; I play a key role in the end-to-end process, from designing and training models to deploying them in practical applications.

✭ Organized tech-related events, and study jams in which more than 100 students were introduced to Flutter, and Kotlin for android app development.✭ Organized a hackathon competition in which more than 50 students used their knowledge from the study jam and solved real-world problems.

✭ Developing embedded systems using microcontrollers, sensors, and communication devices.✭ Writing firmware for the microcontrollers using the C programming language.