Dr. Kayali holds an M.S. in mathematics from the University of Cambridge, an M.S. and Ph.D. in physics from Texas A&M University. He was a postdoctoral fellow at Baylor College of Medicine and later served as a faculty member at Baylor College of Medicine, University of Houston, and Virginia Tech. During these years, his work focused on combining brain imaging data and mathematical modeling to study the neural underpinnings of social and economic decision-making.
In 2014, he left academia to join a startup company, Lumina Technologies, where he served as chief scientist leading R&D efforts to create new algorithms for seismic data analysis.
In 2018, he joined Baker Hughes as a technical lead for data science initiative within digital technology. At Baker Hughes, he delivered innovative solutions for well integrity prediction, automation of well log interpretation, enhancing the resolution of conventional well logging and many use cases in inventory optimization, cash-flow forecasting, and natural language processing. Currently, he is chief data scientist at Woodside Energy where he is leading a team of data scientists to find innovative solutions for E&P challenges using artificial intelligence and high performance computing.