Javad Rafiee

Javad Rafiee has worked in the oil and gas industry since 2011. From 2011 to 2012, they were a Reservoir Engineer at the Research Institute of Petroleum Industry (RIPI). At RIPI, they collaborated to enhance and maintain the company's multi-purpose reservoir simulator and developed a methodology for determining neighboring grid blocks in faulted 3D reservoirs. From 2012 to 2018, they were a Research Assistant at The University of Tulsa. During their time there, they developed a compositional coupled wellbore and reservoir simulator and designed and implemented an efficient two-stage linear solver preconditioner. From 2018 to 2019, they were a Reservoir Engineer at Paradigm, where they developed history-matching and optimization tools and designed and implemented a fast proxy model based on artificial intelligence. Lastly, from 2019 to present, they have been a Senior Data Scientist / Reservoir Engineer at Tachyus, where they have developed and deployed frontend and backend for some of the company's apps on Microsoft Azure, built a general framework to speed up development and deployment of new apps, and performed end-to-end modeling and optimization workflows.

Javad Rafiee's education history includes a Doctor of Philosophy (PhD) in Petroleum Engineering from The University of Tulsa, which they obtained between 2012 and 2017. Javad also obtained a Master of Science (MS) in Petroleum Engineering from Sharif University of Technology between 2009 and 2011, and a Bachelor of Science (BS) in Petroleum Engineering from Petroleum University of Technology between 2005 and 2009. Additionally, Javad has obtained various certifications from Kaggle and Coursera, including Feature Engineering from Kaggle in 2021, and Machine Learning from Coursera in 2018.