AI & Scientific Machine Learning for Engineering Systems
Trustworthy, efficient, and scientifically meaningful AI that integrates physical knowledge, simulation, and data.
Explore theme →Applied Systems Modeling, Analytics, Research & Technology (A-SMART) Lab
We develop trustworthy computational methods to support robust, risk-informed decisions across energy transition, CCUS, subsurface systems, and infrastructure. Our work integrates AI, machine learning, and optimization with domain expertise in energy systems, carbon capture and storage, and subsurface geoenergy — enabling decision-makers to navigate complexity, uncertainty, and risk with confidence. We collaborate with industry, government, and international partners to translate research into practical tools and frameworks that support a secure, resilient, and sustainable energy future across the Asia-Pacific and beyond.
Our Research
Advanced computational methods support infrastructure and geoenergy decisions.
Trustworthy, efficient, and scientifically meaningful AI that integrates physical knowledge, simulation, and data.
Explore theme →Risk-informed computational frameworks for systems with competing objectives and complex technical and economic trade-offs.
Explore theme →Models and decision-support tools for CO₂ capture, transport, storage, infrastructure reuse, and low-carbon networks.
Explore theme →Computational methods for geological storage, geothermal energy, hydrogen storage, and subsurface risk.
Explore theme →Current Work
Risk-adjusted techno-economic modeling for Singapore-linked transport corridors under technical, economic, and operational uncertainty.
Data-driven technologies for tracing, verification, and visibility across rebar delivery and construction value chains.
Training and research supporting carbon capture, transport, storage, and regional deployment.
Selected Work
Ma, Z., Chen, B., and Pawar, R. Scientific Reports, 2023.
View publicationMa, Z., Kim, Y. D., Volkov, O., and Durlofsky, L. J. Mathematical Geosciences, 2022.
View publicationMa, Z., Pachalieva, A. A., Sweeney, M. R., Chen, B., Viswanathan, H., and Hyman, J. D. Mathematical Geosciences, 2025.
View publicationMa, Z., Chen, B., and Pawar, R. Geoenergy Science and Engineering, 2025.
View publicationMa, Z., and Leung, J. Y. Knowledge-Based Systems, 2020.
View publicationServices & Collaboration
We work with industry, government agencies, research institutions, and academic partners on AI-enabled modeling, optimization, uncertainty analysis, and decision-support challenges.
Explore Services