Dr. Olatunde Mosobalaje is a faculty member at the Petroleum Engineering Department of Covenant University, where he is currently promoting digital innovations in engineering education. He is a member of the American Society for Engineering Education (ASEE), and the Society of Petroleum Engineers (SPE). His commitment to knowledge transfer is unmistakable as it manifests in his ongoing projects aiming at enhancing the petroleum engineering curriculum with digital and data analytics content.

In 2023, he was part of a team that designed and published a module on introducing Python coding to petroleum engineering undergraduates – an award-winning effort. Most recently, he played a significant role in a team that developed an integrated framework for the integration of data analytics and machine learning into the petroleum engineering curriculum. He recently founded and is coordinating the Petroleum Data Analytics Special Interest Group (PDA\_SIG) of students and young professionals.

In teaching, Dr. Mosobalaje adopts a balanced blend of analogical reasoning, concept visualization, field application, and workflow coding as a pedagogy style. His research interest is in engineering education, as well as in the deployment of data analytics and machine learning tools to petroleum engineering applications. In a modest way, his research undertakings have produced content-assessment-pedagogy alignment of innovative curriculum ideas and extended the functionality of some existing geostatistical routines. As a testimonial of his pursuit of excellence in teaching, he received the Dean’s award as the best teacher in the department. He also received the Best Paper award in an international conference featuring over 100 authors from 17 countries, and a bronze medal in another. Notably, Dr. Mosobalaje is currently participating in the 2025 Spring Cohort of the prestigious 'Empowering-the-Teachers' (ETT) fellowship, at the Massachusetts Institute of Technology (MIT).

Lecturer – Petroleum Engineering
Covenant University, Ota
February, 2013 – Present

Teaching areas:

• Reservoir engineering
• Fluid flow through porous media
• Python programming with oil and gas applications
• Petroleum data analytics and machine learning (with Python)
• Statistical methods in petroleum engineering (with implementations in R)
• Reservoir simulation (unboxing with Python)
• Oil well testing analysis
• Enhanced oil recovery
• Petrophysics
• Reservoir rock and fluid properties
• Engineering mathematics

Notable contributions:

• 2024: Secured 100 free licenses to Datacamp Classroom offer – giving full access to over 400 data science online courses to students.
• 2024: Initiated and coordinating an industry-academia team to develop a framework for teaching petroleum data analytics and machine learning.
• 2023: Founded PDA Special Interest Group - a learning, upskilling, and research group of students with interest in petroleum engineering applications of data science, machine learning, and artificial intelligence.
• 2023: Initiated a pedagogical project aiming to unbox reservoir simulation with Python.
• 2023: Secured free licenses (90) to Datacamp Classroom offer – giving full access to over 400 data science online courses to students.
• 2021: Pioneered the curriculum development and teaching of Python programming with petroleum engineering applications.
• 2019: Mentored the all-time university Best Graduating Student, with a perfect 5.0 CGPA (Ajia, Motunrayo Victoria).
• 2015: Mentored the Winner of the 2014-2015 SPE African Regional Student Paper Contest (Titus, Zainab Diana).