Dr. Aniefiok Livinus is a Senior Lecturer at the Petroleum Engineering department, University of Uyo. He joined the University of Uyo in December, 2012 as a Lecturer II. He had both his B-Eng and M-Eng degrees in Petroleum Engineering from, (FUTO), Federal University of Technology Owerri, Imo State, Nigeria. In 2019, He obtained his doctoral degree (PhD) in Oil and Gas Engineering from Cranfield University, UK.
For the past six years, Livinus has been working on multiphase flow related projects to understand and predict their behaviors. He has carried out multiphase flow experiments using CT-scan, gamma rays, high speed camera and light diodes for measurements in low-pressure flow loop at Multiphase Flow Department of IFE, Norway. He has performed several numerical studies on multiphase flow in both pipes and reservoirs.
As an academic, He has taught several undergraduate and postgraduate courses related to oil and gas engineering, fluid flow engineering. He has supervised over fifty (50) undergraduate projects. He has completed the supervision of over three M-Eng dissertations, and currently supervising four (4) active PhD students. He has published over twenty (20) scholarly articles in reputable journals both locally and internationally and also attended conferences and presented papers. He has reviewed over ten (10) manuscripts for some journals. He is an Associate Editor for Petroleum and Petrochemical Engineering Journal, Subject Editor in Petroleum Engineering for Engineering Perspective –An International Journal, and Member of Editorial Board– Journal of Oil and Gas Research Reviews.

Livinus is a registered Engineer with the Council for the Regulation of Engineering in Nigeria (COREN); Member, Nigerian Society of Engineers; Member, Nigerian Institution of Petroleum Engineers (NIPetE) of which he is the Financial Secretary of the South-South Chapter, and Member, Society of Petroleum Engineers (SPE International).
His research interests include; multiphase flow modelling and simulation in both porous media and pipelines, modelling and simulation of underground Carbon IV Oxide and hydrogen gas storages in depleted reservoirs, and application of machine learning in petroleum industry activities.