SGL Members Present at Texas A&M Conference on Energy

College Station, TX-

On Friday September 29th, two team members from the Stochastic Geomechanics Laboratory (SGL) shared their research via a poster presentation at the Texas A&M Conference on Energy, presented by Texas A&M Energy Research Society (TAMU ERS), in cooperation with the Texas A&M Energy Institute.

The Conference focused on new and ground-breaking advancements pertaining to multiple sectors of energy, according to the conference website. The event also included keynote speakers from industry and networking sessions.

Graduate research assistants and PhD students, Guillermo Duran Sierra and Abdullah Al Hashib shared their research titled, \”Bayesian Risk Assessment Modeling of the Electric Power Supply Chain: a Case of Study in the North American Region.\”Their work will help to inform Early Warning Systems for critical supply chain threats and disruptions across the North American electric power supply chain.

This project has been supported by a multi-year partnership with the U.S. Department of Homeland Security (DHS) and Cross-Border Threat Screening and Supply Chain Defense Center of Excellence (CBTS) at Texas A&M University (TAMU). The project has been led by Dr. Zenon Medina-Cetina, SGL Director and PhD advisor to both Duran and Hashib.

Duran is a PhD student in the Zachry Department of Civil and Environmental Engineering at Texas A&M University. He is also a former President of the TAMU chapter of the Society of Underwater Technology (SUT), a member of TAMU Graduate Student Consulting Club, and has been a part of the SGL team since 2017. Duran\’s research has focused on static and dynamic Bayesian Risk Assessment and Management to model social, economic, and environmental systems subjected to anthropogenic and environmental threats such as the COVID-19 pandemic.

Hashib is a PhD student in the Department of Multidisciplinary Engineering at Texas A&M University, with a general focus in the Interdisciplinary Engineering Program. He has also been an SGL team member and research assistant since 2022. Hashib’s research focuses on probabilistic calibration to solve inverse problems using the Bayesian paradigm.

Their work with Bayesian Risk Assessment Modeling has also been applied to study eight other supply chains in North America for the project supported by DHS and CBTS.