Courage Ekoh

  • Data Scientist | Machine Learning Researcher | Sustainability PhD Student @ RIT

AI for Sustainability

Hello, I'm Courage

I am a machine learning engineer/researcher interested in applying artificial intelligence to sustainable projects. Previously, I have worked in fintech as well as in the energy space and hope to continue working on projects that directly impacts the needs of the average human.

In my current research, I seeks to understand the temporal and spatial relationship between other infrastructural growth and electricity demand as studied from the sky (i.e. remote sensing, geospatial imaging, nighttime lights, ML).

I am skilled in various programming languages, building ML models from scratch and with existing libraries, MLOps and foundational software engineering

Get In Touch


Aug 2022 - Present
PhD @ Rochester Institute of Technology
Sustainability & AI
Aug 2020 - Dec 2021
Master's degree @ Carnegie Mellon University
Information Technology

Concentration: Applied Machine Learning

Jun 2014 - May 2019
Bachelor's degree @ University of Ibadan
Industrial and Production Engineering



Python, Java, C/C++, SQL

Data Science

NumPy, Pandas, Matplotlib, Seaborn, Scipy, StatsModel, Tableau, Metabase, SQL, A/B Testing, MS EXCEL, Google Data Studio

Machine Learning

Sci-Kit Learn, Pytorch, Tensorflow, Tensorflow Data Validation, Hugging face, Flask


PostgreSQL, MySQL, AWS, Git, Docker, Linux, DevOps


SimaPro, QGIS, ArcGIS, Google Earth Engine, Envi

Work History

Aug 2022 - Present
Research Assistant @ INSYST Lab RIT, Rochester, NY

• Working with Dr. Nathan Williams on electrification problems in Sub-Saharan Africa. Current Project in Nigeria, to estimate the latent demand for electricity in the region

Jun 2022 - Aug 2022
Data Scientist (Research Intern) @ Plentify, Cape Town, South Africa

• Came up with proprietary ML algorithms for flow detection on home heaters with potential to save the company over 40% installation cost on every HotBot installed in the homes of customers

Sep 2021 - Jan 2022
Data Scientist @ Koa Technology, Nairobi, Kenya

• Worked with the operations team to provide insight from the data produced by all departments and foster growth in the company

• Maintained and updated back-end queries to constantly meet business needs in terms of the data pulled out

• Created over 90% of the data engineering processes as well as the various reporting and visualizations used by the various departments in the daily running of the company

Sep 2021 - Dec 2021
Machine Learning Consultant @ TFE Energy, Cape Town, South-Africa

• Utilized Machine learning to build a yield prediction algorithm for mini-grid connections in rural Africa

• Evaluated the possibility of data-backed refinancing for mini-grid connections by combining clustering, and classification algorithms

• Worked extensively with geospatial data to understand how development affects electricity access and consumption in rural villages.

May 2021 - Sep 2021
BI Developer & Data Analyst @ Koa Technology, Nairobi, Kenya

• Conducted statistical and data analysis with captured data and provide business intelligence to aid decision processes for the Operations, Marketing and Tech departments.

• Achieved 2,650% increase in active savers within 3-months from launch by pioneering data-driven initiatives on customer acquisition and retention.

• Built tools from ground-up that provided 100% visibility into KPIs across the entire company.

Aug 2017 - Feb 2018
Well Services Maintenance Engineer (Internship) @ Schlumberger, Port-Harcourt, Nigeria

• Deployed GPS trackers and Maintenance Information Systems on over 200 oilfield assets (covering about 60% of the project, within a month) for better asset and maintenance management as part of the Global Traceability Project

• Maintained and certified pressure control equipment such as treating lines and valves to provide up to 99.99% availability on the field

• Conducted routine maintenance on oilfield equipment, i.e., pumps, engines, mixers, etc. that ensured downtime was near 0 hours.

Research Papers

  • Kolawole, Adekunle, and Courage. O. Ekoh. "A multivariate model to predicting vibration features for equipment prognosis." Nigerian Journal of Technology 41, no. 4 (2022): 739-749.
  • Oshingbesan, Adebayo, Courage Ekoh, Germann Atakpa, and Yonah Byaruagaba. "Extreme Multi-Domain, Multi-Task Learning With Unified Text-to-Text Transfer Transformers." arXiv preprint arXiv:2209.10106 (2022).
  • Oshingbesan, Adebayo, Courage Ekoh, Chukwuemeka Okobi, Aime Munezero, and Kagame Richard. "Detection of Malicious Websites Using Machine Learning Techniques." arXiv preprint arXiv:2209.09630 (2022).

Some Projects

Fraud Detection

This project trains a fraud detection classifier for monetary transactions using a number of techniques for anomaly detection (i.e isolation forest and autoencoders) and deploys the model as an API to production using the Heroku server.

MLOps @ Coursera

This is a repo containing all assignments submited in the MLOps specialization on Coursera