Mukul M. Sharma is Professor and holds the “Tex” Moncrief Chair in the Department of Petroleum and Geosystems Engineering at the University of Texas at Austin where he has been for the past 36 years. He served as Chairman of the Department from 2001 to 2005. His current research interests include hydraulic fracturing, oilfield water management, formation damage and improved oil recovery. He has published more than 450 journal articles and conference proceedings and has 21 patents. He founded Austin Geotech Services an E&P consulting company in 1996. He also co-founded Layline Petroleum in 2006 (which had very successful exit in 2013), Navidad Energy in 2018 and Geothermix, LLC in 2020. Sharma has a Bachelor of Technology in chemical engineering from the Indian Institute of Technology and an MS and PhD in chemical and petroleum engineering from the University of Southern California.

Among his many awards, Dr. Sharma is a member of the US National Academy of Engineering and an Honorary Member of the Society of Petroleum Engineers (SPE). He is the recipient of the 2017 John Franklin Carll Award and the 2009 Lucas Gold Medal, SPE’s highest technical awards. He has also received the 2004 SPE Faculty Distinguished Achievement Award, the 2002 Lester C. Uren Award, the 1998 SPE Formation Evaluation Award and the Distinguished Alumnus award from IIT Kanpur. He served as an SPE Distinguished Lecturer in 2002, has served on the Editorial Boards of many journals, and taught and consulted for industry worldwide.

Dr. Chochua has 20 years of experience in the Oil and Gas, Turbomachinery, and Aerospace Industries, specializing in Computational Fluid Dynamics and heat transfer. Early on in his career, Gocha obtained his Ph.D. degree in Aerospace Engineering from the University of Florida. Dr. Chochua is currently a Technical Advisor in Modeling and Simulation at Schlumberger. His research interests include CFD, simulation-driven design, erosion modeling and mitigation, turbomachinery, thermal management, multiphase flows, and machine learning. He has authored or co-authored 26 journal and conference publications and holds 28 patents and trade secrets.

Xinghui “Lou” LIU is a Senior Production Engineering Advisor with Chevron Technical Center and has 30 + years of industry experience. His expertise includes hydraulic fracturing, acidizing, formation damage, completion and unconventional development. Lou has published numerous technical papers in these areas and coauthored a textbook titled “Petroleum Production Engineering,” ISBN: 978-0-12-809374-0, Gulf Professional Publishing (2017). Lou holds Ph.D. and M.S. degrees in petroleum engineering from University of Oklahoma and Montana Tech, respectively.

Praveen Gonuguntla is currently a Senior CFD Engineer at Tridiagonal Solutions Inc., based out in San Antonio. For the past 13 years, he has performed extensive CFD analysis of Upstream and Downstream Oil&Gas applications. The experimental analysis in the field of erosion is another such area where he worked. He holds a master’s degree in mechanical engineering. His areas of interest are erosion, optimization of downhole tool designs and refinery equipment, multiphase flows in oil & gas production systems and combustion modeling.

Prof. Mayank Tyagi is Chevron #3 designated associate professor at the Craft & Hawkins department of petroleum engineering, Louisiana State University (LSU). He also holds a joint faculty appointment at the Center for Computation & Technology (CCT), LSU since 2007. He obtained his Ph.D. in mechanical engineering from LSU and undergraduate in mechanical engineering from Indian Institute of Technology (IIT), Kanpur. His current research interests span across physics-based simulations using high performance computing (HPC) and data analytics for interdisciplinary petroleum engineering applications such as image-based pore-scale modeling using lattice Boltzmann method (LBM), multiscale multiphase computational fluid dynamics (CFD), geothermal reservoir engineering, and unconventional reservoir simulations. He has also worked on the issues in the quantitative risk assessment (QRA) of offshore petroleum engineering operations and their impacts on regional economy. He has given numerous invited talks in India, China, and several US universities and published over sixty (60) peer-reviewed journal articles and conference papers.

Among many courses he has taught at LSU, data analytics and machine learning applications for petroleum engineering as a senior technical elective compliment the data visualization and computational methods courses. Since the beginning of 2020, he is serving as the Data Science and Petroleum Engineering Fellow at Enovate Upstream, Inc. At Enovate, digitalization technologies combine big data components with advanced artificial intelligence (AI) to offers exploration and production (E&P) companies to improve operational efficiencies as well as reservoir productivity across the entire value chain of upstream operations.

Ronnie Russell is a Staff Engineer with 25 years of experience at Baker Hughes where he worked since 1996 specializing in computational fluid dynamics (CFD), developing erosion models, and mechanical design and analysis of downhole completions and production tools. He is a graduate of Texas A&M University, College Station, TX, with a Master of Science in Mechanical Engineering, and is a registered Professional Engineer in Texas. He holds 17 patents (downhole valves, supersonic airguns, etc.) and has published 14 papers on erosion testing and CFD modeling of downhole valves.

Dr. Rupesh Reddy is currently working as a “Lead Simulation Scientist” at National Oilwell Varco. He has over 12 years of experience in cutting edge simulation analysis and design optimization in a wide range of applications such as multiphase flows, turbulence modeling, free-surface flows, FSI, and particle technologies. He has an extensive experience in application of simulation analysis to the design of the oil and gas equipment like multiphase separators, BOP, and Downhole tools. In recent years, he has been involved in developing Digital Twins using a hybrid approach of data science and physics-based simulations