Academic Portfolio
2018-present
I am a dedicated Lecturer, Researcher, and technology professional with a strong interdisciplinary background in Computer Science, Geographic Information Systems (GIS), and Remote Sensing. I hold an MSc in GIS and Remote Sensing from Dilla University with a CGPA of 3.83, an MSc in Computer Science from Arba Minch University with a CGPA of 3.98, and a BSc in Computer Science from Woldia University with a CGPA of 3.73. I have served as a Lecturer and Researcher at Dilla University since 2019 and previously worked as an ICT Team Leader at the National Election Board of Ethiopia during the 6th General Election. My professional interests and expertise cover programming, web and mobile application development, database management, GIS, remote sensing, data visualization, artificial intelligence, data analysis, and emerging technologies such as blockchain and cloud computing. In addition to my academic qualifications and professional experience, I have developed a broad range of skills through specialized training and professional certifications. These include blockchain and BNB Chain technologies, programming, Android development, data analysis, artificial intelligence, AWS/cloud technologies, online teaching, academic writing, LaTeX manuscript preparation, research methodology, quantitative and qualitative data analysis, grant proposal writing, and educational technology. I am also committed to curriculum development, instructional design, classroom management, student assessment, research, and innovative digital learning. With this combination of academic knowledge, technical expertise, research experience, and teaching skills, I am well positioned to contribute to technology-driven research, education, software development, digital transformation, and multidisciplinary projects that address real-world challenges.
2025
I completed my MSc in GIS and Remote Sensing at Dilla University**, under the College of Social Science and Humanities. I was admitted in the **2022/23 academic year and successfully completed the program with a cumulative average of 3.83 . During my graduate study, I developed advanced knowledge in **Cartography and Mapping, Principles of Remote Sensing, Geographic Information Systems, Geospatial Data Management, Research Methodology for Remote Sensing and GIS, Advanced Remote Sensing and Image Processing, Spatial Information Systems, GIS and Remote Sensing Applications, and Sustainable Natural Resources Management**. These courses strengthened my theoretical understanding and practical capabilities in geospatial science, satellite data analysis, spatial data management, and environmental applications. As part of my MSc study, I conducted research on **“Cloud-Based Spatiotemporal Data Mining Using Google Earth Engine and Machine Learning Approach for Vegetation Cover Change Assessment in Nech Sar National Park, Ethiopia.”** Through this research, I gained practical experience in using **Google Earth Engine, cloud-based geospatial processing, satellite imagery, machine learning, spatial analysis, and vegetation-cover change assessment**. I successfully completed the program and was awarded my degree in **February 2025**, demonstrating my strong academic preparation and research capacity in GIS, remote sensing, and geospatial technologies.
2021
3.98/4.00
2017
GPA 3.73/4.0
Industry-recognized certifications, each verified with a unique credential ID.
IBM SkillsBuild · 2024
Certificate Authenticity ConfirmedGoogle Developers · 2023
Certificate Authenticity ConfirmedAmazon Web Services · 2024
Certificate Authenticity ConfirmedInternational Conference on Applied Computing (ICAC), 2025
Evaluates supervised models that forecast hardware failures from streaming sensor data, cutting unplanned downtime by 34% in test deployments.
Read publication →Journal of Software Engineering & Applications, 2024
Benchmarks Flutter, React Native and native Kotlin across render latency, memory footprint and battery drain on mid-range Android devices.
Read publication →Symposium on Cloud Systems (SoCS), 2024
Proposes an event-driven AWS Lambda pipeline that sustained 12k requests/second during simulated flash-sale traffic at 40% lower cost.
Read publication →