Fatai Anifowose

Lead Research Scientist Saudi Aramco

Fatai Anifowose, SPE, is a lead research scientist at Saudi Aramco. His research focuses on automating geological and petroleum engineering workflows and application of machine learning to increase accuracy, improve efficiency, and enhance productivity. He is an accomplished researcher with 90 papers, 10 granted patents and several filed, and has received a number of R&D awards, including the 2021 SPE Middle East North Africa Regional Service Award, 2021 SPE Middle East North Africa Regional Data Science and Engineering Analytics Award, and the 2024 IChemE Learning and Development Award. He is a technical reviewer for international conferences and reputable journals. He is a member of EAGE, SPE, AAPG, Dhahran Geoscience Society.

Digital Transformation

Artificial Intelligence and Machine Learning: Practical Frameworks in the Energy Sector

The energy sector is rapidly transforming toward a data-driven, decentralized future where combining human expertise with AI and machine learning unlocks new efficiencies, solves complex challenges, and creates a decisive competitive advantage.

December 12, 2025 • Chimeremma Jennifer Okolodibe • The Way Ahead
Digital Transformation

The Basic Elements of Artificial Intelligence and Recipe for a Successful Career Kick Start

The enthusiasm for AI practice is growing rapidly across all industries. This article gives a brief overview of AI's key elements.

December 7, 2021 • Fatai Anifowose • The Way Ahead
Digital Transformation

Ensemble Machine Learning Explained in Simple Terms

If you have used the random forest algorithm, then you already have used the Ensemble Machine Learning (EML) method, probably without realizing it. This article will explain, in very simple terms, the principle behind this relatively new ML paradigm.

July 7, 2020 • Fatai Anifowose • The Way Ahead
Digital Transformation

Artificial Intelligence Explained for Non-Computer Scientists

This article gives a succinct overview of artificial intelligence, its emerging opportunities, prospects, and challenges, and concludes with recommendations to accelerate the admission of AI into workflows.

January 13, 2019 • Fatai Anifowose • The Way Ahead