Overview
Dr. Nelson da Luz is an Assistant Professor and the Blasland, Bouck and Lee Faculty Chair in the Department of Civil and Environmental Engineering at Manhattan University. His research focuses on advancing the management of drinking water and wastewater infrastructure systems through the integration of environmental engineering principles with data science methods. His work combines statistical modeling, machine learning, and high-performance computing to address challenges in water quality assessment, infrastructure planning, and environmental decision-making. His research has contributed to regulatory decision-making and the development of tools to better understand water infrastructure systems, including efforts to map decentralized wastewater systems and improve drinking water data quality. He has contributed to multiple externally funded projects focused on water infrastructure, data systems, and environmental health, and has served in leadership roles supporting multidisciplinary research initiatives. His research aims to develop practical, data-driven solutions to complex environmental engineering challenges with direct relevance to public and environmental health.
Education
- B.S. in Civil Engineering, Manhattan University
- M.E. in Environmental Engineering, Manhattan University
- Ph.D. in Civil Engineering, University of Massachusetts Amherst
Courses Taught
- CEEN 308 Reliab Analysis Civl & Envl En
- ENGS 204 Envl Eng Principles I
Publications
Peer-Reviewed Publications
- N. da Luz, J. Taneja, and E. Kumpel (2025), Look Out Below: Predicting Wastewater Infrastructure Service Type at the Land Parcel Scale. ES&T Engineering, DOI: 10.1021/acsestengg.5c00637
- N. da Luz, J.E. Tobiason, and E. Kumpel (2022). Water quality monitoring with purpose: Using a novel framework and leveraging long-term data. Science of the Total Environment, DOI: 10.1016/j.scitotenv.2021.151729
- N. da Luz and E. Kumpel (2020). Evaluating the impact of sampling design on drinking water quality monitoring program outcomes. Water Research, DOI: 10.1016/j.watres.2020.116217.
Conference and Technical Papers
- S. Imanirakiza, N. Sereboo, N. da Luz, E. Kumpel, and J. Taneja (2025). Graph Neural Networks for Predicting Wastewater Service Type at a Land Parcel Level. 39th Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, CA.
- G. Pierce, W. Callan, L. Blain, N. da Luz, E. Kumpel, A. Hernandez, J. Taneja, T. Klug, G. Harrison, J. Gorman, and E. de Guzman (2025). How have the LA Fires affected water systems in LA County? An Early Overview. UCLA: Luskin Center for Innovation. https://escholarship.org/uc/item/7km452tj
- K.J. Farley, N. da Luz, J. DeLorenzo, E. Farrelly, R.E. Landeck Miller, J. Lodge, R. Lohmann, and S. Vojta (2023). NY/NJ Harbor Contamination Assessment and Reduction Project, CARP II, Develop a method (or model) for predicting bioaccumulation of sedimentary contaminants in dredged material test organisms. Appendix A-3. https://www.hudsonriver.org/article/carp-appendices-2/
- N. da Luz and K.J. Farley (2017) Evaluation of Sediment Loads to the Tidal, Freshwater Hudson: Implications for Sediment Trapping and PCB Transport. Ninth International Conference on Remediation and Management of Contaminated Sediments. New Orleans, LA. E-041. ISBN 978-0-9964071-2-0, ©2017 Battelle Memorial Institute, Columbus, OH.
Professional Experience & Memberships
Professional Experience
- 2026 – Present: Assistant Professor, Manhattan University
- 2024-2026: Research Assistant Professor, University of Massachusetts Amherst
- 2023: Lecturer, University of Massachusetts Amherst
Professional Memberships
- American Society of Civil Engineers (ASCE)
- Water Environment Federation (WEF)
- American Water Works Association (AWWA)
- Association of Environmental Engineering and Science Professors (AEESP)
- National Onsite Wastewater Recycling Association (NOWRA)
- Tau Beta Pi National Engineering Honor Society
- Chi Epsilon National Civil Engineering Honor Society
Certifications
- Engineer in Training, E.I.T.
- Center for the Integration of Teaching and Learning (CIRTL) Associate
