Kumar Mahinthakumar


  • Fitts-Woolard Hall 3207

Dr. Mahinthakumar’s (referred to as Dr. Kumar by his students) long term goal is to develop efficient algorithms and tools to solve large scale civil and environmental engineering problems.

Dr. Kumar is currently focused on 1) real time optimization and inverse modeling for water distribution systems analysis, 2) large scale modeling and characterization of groundwater flow and transport systems, 3) parallel and distributed computing algorithms and tools for environmental applications.

In CCEE, Dr. Kumar collaborates with Dr. Arumugam, Dr. Brill, Dr. Berglund, Dr. DeCarolis and Dr. Ranjithan.

At the graduate level, Dr. Kumar teaches Introduction to Numerical Methods for Civil Engineers (CE 536), Hydraulics of Groundwater (CE 584), High Performance Computing for Civil Engineers (CE 791A), and Inverse Modeling for Civil Engineers (CE 791B). In Numerical Methods, he teaches application of common numerical methods to civil engineering problem solving. The high performance computing course is a project-based course focused on parallel and distributed computing algorithms for large scale civil engineering applications. The inverse modeling course focuses on heuristic and gradient based search techniques as well as Markov Chain Monte Carlo methods for the solution of civil engineering parameter estimation and system identification problems. The graduate students who work with Dr. Kumar enjoy computer programming and are interested in developing innovative methods and tools for large scale civil engineering problem solving.


Ph.D. 1995

Civil Engineering

University of Illinois, Urbana-Champaign

M.S. 1990

Applied Mathematics

Claremont Graduate School

M.Eng 1988

Environmental Engineering

Asian Institute of Technology

B.S. 1985

Civil Engineering

University of Peradeniya

Research Description

Dr. Mahinthakumar is interested in large scale modeling of subsurface flow and transport, parallel and distributed computing, optimization and inverse problems, water distribution system analysis

Honors and Awards

  • National Science Foundation CAREER Award, 2003
  • NCSU Faculty Research and Professional Development Award, 2001
  • US Fulbright Scholar to South Africa, 2017


Supervised Machine Learning Approaches for Leak Localization in Water Distribution Systems: Impact of Complexities of Leak Characteristics
Basnet, L., Brill, D., Ranjithan, R., & Mahinthakumar, K. (2023), JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 149(8). https://doi.org/10.1061/JWRMD5.WRENG-6047
A Sequential Pressure-Based Algorithm for Data-Driven Leakage Identification and Model-Based Localization in Water Distribution Networks
Daniel, I., Pesantez, J., Letzgus, S., Fasaee, M. A. K., Alghamdi, F., Berglund, E., … Cominola, A. (2022), JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 148(6). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001535
Correcting Power Leakage Equation for Improved Leakage Modeling and Detection
Kabaasha, A. M., Zyl, J. E., & Mahinthakumar, G. ''K. (2020), JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 146(3). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001172
GRAPS: Generalized Multi-Reservoir Analyses using probabilistic streamflow forecasts
Xuan, Y., Ford, L., Mahinthakumar, K., De Souza Filho, A., Lall, U., & Sankarasubramanian, A. (2020), Environmental Modelling & Software, 133, 104802. https://doi.org/10.1016/j.envsoft.2020.104802
Reducing error in water distribution network simulations with field measurements
Ricca, H., Patskoski, J., & Mahinthakumar, G. (2020), JOURNAL OF APPLIED WATER ENGINEERING AND RESEARCH, 8(1), 15–27. https://doi.org/10.1080/23249676.2020.1719218
Modeling chloramine decay in full-scale drinking water supply systems
Ricca, H., Aravinthan, V., & Mahinthakumar, G. (2019), WATER ENVIRONMENT RESEARCH, 91(5), 441–454. https://doi.org/10.1002/wer.1046
Multiphase Procedure to Design District Metered Areas for Water Distribution Networks
Pesantez, J. E., Berglund, E. Z., & Mahinthakumar, G. (2019), JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 145(8). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001095
Repurposing an energy system optimization model for seasonal power generation planning
de Queiroz, A. R., Mulcahy, D., Sankarasubramanian, A., Deane, J. P., Mahinthakumar, G., Lu, N., & DeCarolis, J. F. (2019), Energy, 181, 1321–1330. https://doi.org/10.1016/j.energy.2019.05.126
The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables
Seo, S. B., Das Bhowmik, R., Sankarasubramanian, A., Mahinthakumar, G., & Kumar, M. (2019), Journal of Hydrology, 570, 304–314. https://doi.org/10.1016/j.jhydrol.2018.12.076
Assessing the effects of water restrictions on socio-hydrologic resilience for shared groundwater systems
Al-Amin, S., Berglund, E. Z., Mahinthakumar, G., & Larson, K. L. (2018), Journal of Hydrology, 566, 872–885. https://doi.org/10.1016/j.jhydrol.2018.08.045

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Resilience-based Modeling for Water Infrastructure Systems
National Science Foundation (NSF)(8/15/18 - 7/31/24)
Groundwater Model Review and Technical Support
NC Department of Environmental Quality (DEQ)(1/01/22 - 6/30/24)
PFI-TT: Leakage Detection in Water Distribution Systems Using Routine Pressure Measurements
National Science Foundation (NSF)(8/01/19 - 10/31/23)
Cybersees: Type II: Cyber-Enabled Water and Energy Systems Sustainability Utilizing Climate Information
National Science Foundation (NSF)(9/01/14 - 2/28/21)
Coal Ash Groundwater Modeling Review and Technical Support
NC Department of Environmental Quality (DEQ)(11/01/18 - 11/30/20)
WSC - Category 3: Collaborative Research: Water Sustainability under Near-term Climate Change : A Cross-Regional Analysis Incorporating Socio-Ecological Feedbacks and Adaptations
National Science Foundation (NSF)(9/01/12 - 8/31/18)
Water Distribution Modeling Experiments with the Cary Network
Sensus USA, Inc.(10/01/14 - 7/31/16)
An Adaptive Leak Detection And Risk Analysis Framework For Urban Water Distribution Systems
National Science Foundation (NSF)(8/15/11 - 7/31/16)
Performance Engineering Research Institute (PERI)
US Dept. of Energy (DOE)(6/07/07 - 12/15/12)
Development of a Scalable Parallel I/O Module for Environmental Management Applications
US Dept. of Energy (DOE)(7/27/10 - 9/30/12)