Dr. Martin Ma
Assistant Professor, Singapore Institute of Technology
Adjunct Faculty, New Mexico Institute of Mining and Technology
Principal Investigator, A-SMART Lab
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Dr. Martin Ma leads the Applied Systems Modeling, Analytics, Research & Technology (A-SMART) Lab at the Singapore Institute of Technology. His research develops AI-enabled modeling, optimization, and decision-intelligence frameworks for secure, resilient, and economically sustainable energy and infrastructure systems under uncertainty.
By integrating scientific machine learning, physics-based modeling, mathematical optimization, techno-economic analysis, and uncertainty quantification, his work transforms complex engineering data and models into actionable, risk-informed decisions. His research spans CCUS and low-carbon infrastructure, subsurface and geoenergy systems, energy-system planning, and AI-enabled engineering, with a strong emphasis on translating advanced computational methods into practical tools for real-world planning, operation, and investment decisions.
Research
AI & Scientific Machine Learning · Optimization & Decision Intelligence · CCUS & Low-Carbon Infrastructure · Subsurface & Geoenergy Systems
Our research integrates data, physics, artificial intelligence, optimization, and uncertainty analysis to understand complex engineering systems and support better decisions. The work spans methodological development and real-world applications in energy, infrastructure, geoenergy, carbon management, and AI-enabled engineering.
Research impact
Dr. Ma has led and contributed to the development of computational tools and decision-support frameworks for carbon management, subsurface systems, and energy infrastructure, including SimCCS 3.0, SCO₂T, and CostMAP. His work integrates engineering models with optimization, techno-economic analysis, and uncertainty quantification to support infrastructure planning and risk-informed decision-making.
His research and software have been used in studies supporting U.S. federal agencies and national laboratories, helping inform policy analysis and strategic decision-making related to CCUS deployment, CO₂ transport and storage, and low-carbon infrastructure. His research has also contributed to major collaborative programs supported by the U.S. Department of Energy, A*STAR, NSERC, and international CCUS partnerships. He has authored and co-authored more than 60 journal and conference publications spanning AI, optimization, CCUS, subsurface systems, and energy infrastructure.
Professional leadership
Dr. Ma serves as an Associate Editor of Geoenergy Science and Engineering and contributes actively to international activities in CCUS, energy systems, artificial intelligence, and computational engineering. He has served on conference technical and program committees, including major CCUS events across the SPE, SEG, and AAPG communities, and has contributed as a session chair, moderator, abstract reviewer, and technical reviewer.
His professional activities also include guest editing, peer review, conference organization, invited presentations, and interdisciplinary initiatives supporting the development and application of emerging technologies and AI.
Academic & research appointments
Assistant Professor
Singapore Institute of Technology, Singapore
2025–Present
Adjunct Faculty
New Mexico Institute of Mining and Technology, USA
2025–Present
Research Scientist
New Mexico Institute of Mining and Technology, USA
2025
Staff Scientist
Los Alamos National Laboratory, USA
2023–2025
Academic background
Education
Ph.D. in Petroleum Engineering
University of Alberta, Canada
2013–2018
M.Sc. in Earth Science and Engineering
King Abdullah University of Science and Technology, Saudi Arabia
B.S. in Petroleum Engineering
China University of Petroleum (East China), China
Postdoctoral training
Postdoctoral Research Associate
Los Alamos National Laboratory, USA
2022–2023
NSERC Postdoctoral Research Fellow
Stanford University, USA
2020–2022
Postdoctoral Research Fellow
University of Alberta, Canada
2018–2019
Research philosophy
Better models should lead to better decisions.
Data + Physics → AI & Modeling → Optimization & Uncertainty → Decision Intelligence
The A-SMART Lab develops computational methods that are scientifically rigorous, practically useful, and capable of supporting real-world engineering and infrastructure decisions.