Annual Symposium: AI Accelerated Physics Based Modelling and its Role in Energy Industry

Laurent Alteirac began his career in 2001, driven by a passion for innovation. Throughout his journey, he gained expertise across all three core divisions of the company. In the Production Systems division, in the Sand Screen Department, Laurent developed the industry’s first intelligent multi-zone completion system, revolutionizing efficiency and productivity beyond gravel pack. A decade later, post Macondo, he validated the industry first API 17G cut and seal subsea landing string valve. Transitioning to the Well Construction division, Laurent developed the first Orion II mud pulse modulator. In the Reservoir Performance division, he played a pivotal role in creating and patenting Music telemetry, which improved data transmission in oil and gas testing operations. Additionally, in the Digital Division, he commercialized the Valve Commander project, enhancing North America Land stimulation automation. Laurent also contributed to sustainable energy solutions in the New Energy realm delivering the first high temperature geothermal frac plug for the Utah Forge research project. Currently, he serves as the Enabling Technology Development (ETD) Manager. Laurent’s academic achievements include two Master’s degrees in Engineering: one from Arts & Métiers France and one from Georgia Tech USA. Laurent strives to create performing teams. He is a SLB dual career and has 3 kids.

Madhu Vellakal is a Solutions Engineering Manager at Rescale. Madhu brings several years of experience in computational science, high-performance computing, analytics, and machine learning to Rescale. He is part of the AI Physics team at Rescale chartered with accelerating the adoption of AI technologies in CAE workflows. He received his Masters of Engineering from The University of Illinois Urbana-Champaign and has authored numerous technical publications throughout his career.

Harpreet Sethi is a Solutions Architect for Energy at NVIDIA. His work focuses on building AI factories and digital twins for scientific applications using Generative AI and Physics-ML. He received his PhD in Geophysics from Colorado School of Mines and obtained an integrated Masters/Bachelor’s degree in the same discipline from IIT Roorkee.

Dr. Anchal Jatale manages the team of application engineers working in Energy, Chemical and Process industry. He is championing the efforts in developing cutting-edge simulation solutions for new clean energy including wind, hydrogen and carbon capture. He has 15 years' experience in CFD modeling and simulations. For the past few years, he is spearheading Ansys Digital twin engagements in O&G and the energy industry. His expertise is in reduced order modeling, system modeling, reacting flow, combustion, multi-phase flow. Prior to joining Ansys, he received his doctorate in Chemical Engineering from the University of Utah and bachelors in chemical Engineering from Indian institute of technology (IIT), Kanpur."

Dr. Jun Zhang is a research associate at the Erosion/Corrosion Research Center in the Department of Mechanical Engineering and the School of Cyber Studies at the University of Tulsa. With over 10 years of research experience in both academia and industry, Jun specializes in CFD modeling, cybersecurity in the energy and engineering sectors, fired equipment design, combustion, and particulate flow. He leverages machine learning and AI models to address complex problems across engineering and security domains. Jun has published extensively in leading journals and conferences and has served on several technical committees

Vinicius Girardi is Technology Development Manager at ESSS O&G, a business unit dedicated to high-end digital tools for the O&G Industry. He has Bachelor’s degree in Mechatronic Engineering and Masters in Mechanical Engineering, both from the University of São Paulo and Petroleum Engineer Degree by PUC-Rio. Vinicius’ experience spans 12 years in the use of simulation tools and in the development of innovative software technology in the areas of reservoir engineering, drilling, production and flow assurance

Romit Maulik is an Assistant Professor in the College of Information Sciences and Technology at Pennsylvania State University (PSU) as well as a joint appointment faculty at Argonne National Laboratory (ANL). He is also a co-hire in the Institute for Computational and Data Sciences at PSU. He obtained his PhD in Mechanical and Aerospace Engineering at Oklahoma State University in 2019 and has been the Margaret Butler Postdoctoral Fellow as well as an Assistant Computational Scientist at ANL before starting his current position in August 2023. His research has been funded by the DOE, NSF and ANL and Los Alamos National Laboratories and he is also a member of RAPIDS, a DOE SCIDAC Institute for Artificial Intelligence. His research group, the Interdisciplinary Scientific Computing Laboratory, studies scientific machine learning algorithm development for various applications in engineering, energy, and the environment.

Vedanth Srinivasan is the Head of Solutions for Engineering & Design and Go To Market (GTM) at Amazon Web Services. His focus includes modeling, simulations and high performance computing as well as higher order workloads including model based system engineering, digital thread and digital twins solutions development. He has over 20 years of experience in development and application of advanced engineering simulation processes across oil & gas, aerospace, automotive and healthcare industries. He has a PhD in Mechanical Engineering from University of Kentucky.

Dr Chao Xu is a Research Scientist at Argonne National Laboratory's Transportation and Power Systems Division. His research focuses on computational fluid dynamics (CFD) with detailed chemistry, turbulence and turbulent combustion modeling, as well as reduction and algorithmic acceleration of complex reacting flows for applications in industrial and aero gas turbines, piston engines, industrial burners, and offshore wind. His work leverages leadership HPC to tackle both fundamental and applied problems in turbulence, mixing, combustion, heat transfer, detonation, and emissions formation related to practical energy and propulsion systems. He is the PI on multiple DOE and industry-funded projects where he collaborates extensively with partners at GE, Solar Turbines, Caterpillar, ExxonMobil, NETL and academia toward the decarbonization of transportation, power generation, and industrial sectors. He is also the lead developer of the reacting flow solver within the spectral element based high-order CFD code Nek5000/RS. He is a four-time Impact Argonne Award receiver (2020, 2022, 2023, 2024) for his innovative and impactful research at Argonne. He is a member of the Propellants and Combustion (P&C) Technical Committee of the American Institute of Aeronautics and Astronautics (AIAA). He received his PhD in Mechanical Engineering from University of Connecticut and his Bachelor's degree in Thermal Engineering from Tsinghua University.

Ani Rajagopal has been serving as an Industry Process Consultant at SIMULIA since 2019, joining the Worldwide Fluids team following the integration of Exa Corporation. With nearly 8 years of expertise in fluids and thermal sciences, he serves as an expert voice in supporting customers across all industries including Industrial Equipment and Transportation & Mobility. In his role within the Worldwide SIMULIA Fluids team, he focuses on enhancing fluid solutions through physics-testing, and deploying these solutions to optimize customer processes, particularly through automation. Recently, he has been a key member of the core validation group for SIMULIA’s AI/ML initiatives, specifically for fluids-related applications.

Vinod Kumar is a Professor and Chair of the Mechanical & Industrial Engineering Department at Texas A&M University - Kingsville and a Co-Founder of deepVein Inc., a startup that develops predictive technologies for the detection, prediction, and tracking of deep vein thrombosis (DVT) and pulmonary embolism (PE) using data-driven and physics-based approaches. Vinod is interested in applying artificial intelligence/machine learning (AI/ML), high-performance computing (HPC), and computational fluid dynamics (CFD) to investigate complex engineering and health challenges through R&D, innovation, and entrepreneurship.

Vinod bring many years of academic, administrative, and research experience through interdisciplinary collaboration with various DOD and DOE labs, Princeton University, Rice University, and Calysta, a biotechnology company.  He has worked on projects involving CO2 sequestration modeling, climate modeling, concentrating solar power simulations, exascale computing, multiphase and multiphysics flows, and compressible and incompressible flows. He has also deployed data analytics, big data, ML, and AI for solving engineering problems and enhancing predictive capabilities. Vinod has extensive experience with multiple engineering software, programming languages, and HPC platforms. He has published multiple papers, patents, and books on my topics of interest and expertise.

Dr. Kuochen Tsai has spent 18 years with Shell as a SME in multiphase, particulate, combustion, and erosion/corrosion modeling. Before joining Shell, he worked for the Dow Chemical Company at Freeport, TX for 9 years in Engineering Sciences. His current interests are in multiphase flows, biomass processing, erosion, flow assisted corrosion and physics-based machine learning. Kuochen has a Ph.D in mechanical engineering from SUNY Stony Brook.