Diego is a petroleum engineer with eight years of international oil and gas industry experience. In his current role, he is part of Anadarko's Advanced Analytics and Emerging Technologies (AAET) team, helping the company adopt data analytics and develop digital technologies to operate more efficiently. Diego has wide working reservoir engineering and data analytics experience, having developed projects in the major unconventional basins in the USA, as well as international experience, having been involved in assignments in Europe, Canada, Latin America and the Middle East.

Diego has just completed in 2018 a MS Analytics degree from Texas A&M University, where he was the recipient of the Roland Acra Award for the most outstanding masters project in analytics. Diego also has completed a MS in Petroleum Engineering in Italy and a BS Petroleum Engineering degree in Venezuela.

Justin Lo leads the data science team at Chevron.  He is focused on growing the use of data science across the enterprise. This includes rapidly building and delivering the analytics portfolio and scaling solutions across Chevron’s globally distributed business units. He joined Chevron in 2013 as a data scientist in Drilling & Completions where he was responsible for applying modeling and analytics to support Drilling & Completions and Chevron North America Exploration and Production IT strategies. He received dual bachelor’s degrees in biomedical engineering and liberal arts Plan II from the University of Texas in Austin. He also holds a doctorate in biomedical engineering from Duke University.  He is married and has four children.

Damian Burch is the data analytics advisor for ExxonMobil Upstream Research Company. He has worked at URC for 9 years, and has been involved with projects spanning exploration, development, and production.  He specializes in combining physics, statistics, and machine learning to distill meaningful information and actionable knowledge from data.  Damian was an undergraduate at Caltech with a double major in Mathematics and Computer Science, and he has a PhD in Applied Mathematics from MIT.  Before working at ExxonMobil, he earned hundreds of dollars in the dot-com boom and worked for a Department of Defense research company.

 Dr. Hector Klie is an experienced computational and data scientist primarily focused on the development of artificial intelligence solutions to simplify and automate Oil & Gas operations. Dr. Klie is currently Data Science Technical Lead and Chief Executive Officer of DeepCast.ai and Adjunct Professor of the Dept. of Computational and Applied Mathematics at Rice University. Before his current positions, he was Director of Enterprise Data Solutions and Lead Data Scientist at Sanchez Oil & Gas Corporation (2016-2017) and Staff Reservoir Engineer and Lead Data Scientist at ConocoPhillips (2008-2016). He was previously Associate Director at the Center for Subsurface Modeling in The University of Texas at Austin (2003-2008). Dr. Klie has been involved in numerous multi-disciplinary projects and published over 80 papers in the fields of Reservoir Engineering, Geophysics, Applied Mathematics and Computational Science. He has made notable contributions in the areas of sparse linear solvers, stochastic optimization, uncertainty quantification, high performance computing, reduced order modeling and machine learning. He has chaired multiple technical venues at SPE, SIAM, EAGE and SEG and has patented 5 inventions. Dr. Klie completed his Ph.D. in Computational Science and Engineering at the Dept. of Computational and Applied Mathematics at Rice University, 1997.