CO₂ capture and storage (CCS) technology is likely to be widely deployed in coming decades due to major climate and economic drivers. CCS is part of every major climate policy that limits global warming to 2 °C and significant CO₂ tax credits have recently been enacted in the U.S. These drivers are likely to stimulate capture and storage of hundreds of millions or billions of tonnes of CO₂ annually. Challenges of safely and permanently sequestering such large volumes of CO₂ include real-time forecasting of storage reservoir performance, optimization of reservoir management and monitoring solutions, CO₂/brine leakage risk assessment modeling, and prediction of CO₂ phase behavior from deep storage reservoir to shallow subsurface. The goal of this session is to advance the application of computational methods such as optimization, data assimilation, uncertainty quantification, integrated assessment modeling, and machine learning to address these critical challenges/issues. Other CCS related topics are also welcome.