Isaac Ege

I’m a data-driven engineer with a strong foundation in machine learning, computer vision, and signal processing—now actively pivoting toward clean energy, with a deep interest in wind energy, sustainability, and energy analytics.

At the University of Dayton Research Institute, I’ve worked on enhancing vision-aided navigation systems using cutting-edge ML techniques and hyperspectral data analysis. This experience has sharpened my ability to handle complex datasets, build intelligent systems, and create real-world impact through technology.

I’m now looking to apply my data and machine learning skills in the renewable energy space—particularly in roles involving wind energy analytics, clean tech innovation, or sustainability-driven data projects. While I’m still building experience in this domain, I’m actively learning about SCADA systems, wind resource modeling, and energy systems optimization.

The University of Dayton Research Institute                 May 2023 – Present

Research Engineer                        Dayton, OH

• Spearheaded exploration of cutting-edge research in alternative navigation methods, with a primary focus on machine learning and hyperspectral resources.
• Developed innovative machine-learning models leveraging hyperspectral imagery to estimate position, location, and timing solely from visual data.
• Presented findings at important conferences including:
  • “Quantifying Feature Richness of Aerial Imagery through Learned Deep Embeddings” at Joint Navigation Conference in 2023
  • “ An Investigation In The Use Of Hyperspectral Imagery Using Machine Learning For Vision Aided Navigation” at NAECON in 2023
• Mentored and supported fellow graduate assistants in their studies, particularly in machine learning and vision-aided navigation techniques.

University of Dayton             Aug 2022 – Aug 2023

Graduate Assistant                   Dayton, OH

• Researched machine learning techniques with a focus on leveraging hyperspectral imagery for vision-aided navigation.
• Developed a neural network architecture optimized for utilizing hyperspectral imagery in navigation systems, enhancing accuracy and reliability.
• Engineered a data trawler specifically tailored for the AVIRIS dataset, enabling streamlined access to various downloadable datasets for research purposes.
• Collaborated on the development of an image chipping code, ensuring consistent extraction of small images with standardized coordinates across different datasets.

Terra.do             Aug 2025 – Oct 2025

Learning for Action

• Understanding the science of climate change and strategies for carbon reduction and renewable energy.
• Learning how to apply systems thinking to create sustainable solutions across industries and communities.

University of Dayton                                Aug 2022 – May 2023 

Master of Science in Electrical Engineering                    Dayton, OH

• Concurrently worked part-time as a graduate student at the University of Dayton. 

Bachelor of Electrical Engineering                Aug 2018 – May 2022

• Completed a work-study program with the Dayton Food Bank, leading a project to design, create, and install a comprehensive monitoring system for their composter, focusing on temperature, oxygen levels, and moisture content.