Ebuka Osunwoke

Mechanical / Energy Engineer

Ebuka is a data analyst and energy engineer for ENERlite Consulting. He has substantial experience as a data scientist and graduate research and teaching assistant. He developed models to predict buildings’ monthly utility data and an algorithm to perform automatic building energy model calibration for ENERtune while attaining a Master’s degree in Engineering at the University of Louisiana at Lafayette. He is now pursuing a master’s degree in Computer Science. His specialties include deep learning, cloud solutions, and computer hardware.

Education:

  • Federal University of Technology Owerri, Nigeria — Bachelor of Science in Petroleum Engineering

  • University of Louisiana at Lafayette — Master of Science in Engineering

  • Currently at University of Louisiana at Lafayette — Master of Science in Computer Science

Professional Experience:

  • dbHMS (Databased+) Building Performance Company — Data Scientist/ Building Performance Intern

  • University of Louisiana at Lafayette; Electrical Engineering Department — Graduate Research Assistant/ML Engineer

  • University of Louisiana at Lafayette; Petroleum Engineering Department — Graduate Teaching Assistant

PROJECTS:

  • Developed a novel ML model for large-scale classification of Solar-PV data at the University of Louisiana at Lafayette.

  • Developed a prototype database system for UL Lafayette student housing using MySQL and PHP.

  • Explored skip connections in residual convolutional neural networks for image classification.

  • Developed an algorithm for the automatic calibration of building energy models using machine learning and multi-objective optimization.

  • Explored Azure storage management services and deployed computer vision software using object detection cognitive service on Azure.

PUBLICATIONS:

  • "Machine learning enabled clustering approach for large-scale classification of solar data" (NAPS Conference, 2021).

  • "Comparative analysis of VOLT-VAR control parameter settings of smart PV inverters: A case study" (NAPS Conference, 2021).

  • "Validation of analytical model and identification of salt effect on wellbore temperature in underbalanced drilling" (JPEPT 2022).