Research
I develop data engineering and software frameworks that advance environmental sustainability through life cycle assessment (LCA) modeling, chemical risk assessment, and computational tools. Drawing on chemical engineering principles, machine learning, and advanced software development, my work addresses how environmental data can be systematically integrated to support policy decisions and create tools used by researchers worldwide.
Research Themes
Environmental Data Engineering & Chemical Tracking
I develop comprehensive data engineering frameworks for tracking chemical flows, standardizing environmental inventories, and supporting regulatory decision-making through systematic data integration. This work bridges chemical engineering with software development to create scalable systems for environmental assessment.
Key Publications
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Hernandez-Betancur, J. D., Chea, J. D., Perez, D., & Ruiz-Mercado, G. J. (2026). Integrating data engineering and process systems engineering for end-of-life chemical flow analysis. Computers & Chemical Engineering, 204, 109414. https://doi.org/10.1016/j.compchemeng.2025.109414
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Hernandez-Betancur, J. D., Ruiz-Mercado, G. J., Abraham, J. P., Martin, M., Ingwersen, W. W., & Smith, R. L. (2021). Data engineering for tracking chemicals and releases at industrial end-of-life activities. Journal of Hazardous Materials, 405, 124270. https://doi.org/10.1016/j.jhazmat.2020.124270
Machine Learning for Chemical Risk Assessment
I apply machine learning and data science techniques to chemical risk assessment, developing predictive models for chemical behavior and exposure scenarios using molecular structure-based approaches. This research enables high-throughput screening and automated decision support for chemical safety evaluation.
Key Publications
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Hernandez-Betancur, J. D., Ruiz-Mercado, G. J., & Martin, M. (2023). Predicting Chemical End-of-Life Scenarios Using Structure-Based Classification Models. ACS Sustainable Chemistry & Engineering, 11(9), 3594–3602. https://doi.org/10.1021/acssuschemeng.2c05662
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Hernandez-Betancur, J. D., Martin, M., & Ruiz-Mercado, G. J. (2021). A data engineering framework for on-site end-of-life industrial operations. Journal of Cleaner Production, 327, 129514. https://doi.org/10.1016/j.jclepro.2021.129514
Life Cycle Assessment Software & Sustainability Tools
I lead the development of next-generation life cycle assessment software, focusing on the GREET model used globally for environmental policy and research. My work creates accessible Python interfaces and data interoperability solutions that bridge different LCA platforms and enable broader adoption of environmental assessment tools.
Key Publications
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Young, B., Ingwersen, W. W., Bergmann, M., Hernandez-Betancur, J. D., Ghosh, T., Bell, E., & Cashman, S. (2022). A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data. Applied Sciences, 12(7), 3447. https://doi.org/10.3390/app12073447
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Hernández-Betancur, J. D., Hernández, H. F., & Ocampo-Carmona, L. M. (2019). A holistic framework for assessing hot-dip galvanizing process sustainability. Journal of Cleaner Production, 206, 755–766. https://doi.org/10.1016/j.jclepro.2018.09.177
For a complete list of publications, see my Publications page.
Research Vision & Next Steps
My research program aims to establish data-driven frameworks for environmental decision-making and expand computational tools that integrate simulation, policy, and industrial applications. I focus on creating open, reproducible modeling environments that connect diverse data sources and bridge scientific insight with practical environmental management across scales, from regulatory compliance to global sustainability assessment.