Professor Shuyu Sun, Head of KAUST Computational Transport Phenomena Laboratory, has been appointed as the
Associate Editor of Gas Science and Engineering for Deep Learning related researches.
The objective of Gas Science and Engineering is to bridge the gap between the science and engineering of natural gases by publishing articles that are intelligible to both scientists and engineers working in the Earth sciences.
The journal aims to advance the environmentally sustainable exploration, processing, and utilization of gas resources to support energy transition and net-zero carbon goals. General topics include, but are not limited to, carbon capture, utilization and storage (CCUS), gas to hydrogen, and underground gas storage. Application of artificial intelligence, machine learning and data analytics in gas science and engineering are encouraged.
