Kumar Mahinthakumar


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


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
Conjunctive management of surface water and groundwater resources under drought conditions using a fully coupled hydrological model
Seo, S. B., Mahinthakumar, G., Sankarasubramanian, A., & Kumar, M. (2018), Journal of Water Resources Planning and Management, 144(9).
Multivariate downscaling approach preserving cross correlations across climate variables for projecting hydrologic fluxes
Das Bhowmik, R., Sankarasubramanian, A., Sinha, T., Patskoski, J., Mahinthakumar, G., & Kunkel, K. E. (2017), Journal of Hydrometeorology, 18(8), 2187–2205.
Successive linear approximation methods for leak detection in water distribution systems
Berglund, A., Areti, V. S., Brill, D., & Mahinthakumar, G. (2017), Journal of Water Resources Planning and Management, 143(8).
Synthesis of public water supply use in the United States: Spatio-temporal patterns and socio-economic controls
Sankarasubramanian, A., Sabo, J. L., Larson, K. L., Seo, S. B., Sinha, T., Bhowmik, R., … Kominoski, J. (2017), Earths Future, 5(7), 771–788.
Coupling agent-based and groundwater modeling to explore demand management strategies for shared resources
Al-Amin, S., Berglund, E. Z., & Mahinthakumar, K. (2016), (pp. 141–150).
Fenton oxidation of metsulfuron-methyl with application to permeable reactive barriers
Abdul, J. M., Vigneswaran, S., Kandasamy, J., & Mahinthakumar, G. (2016), Environmental Modeling & Assessment, 21(1), 149–158.
Identification of dominant source of errors in developing streamflow and groundwater projections under near-term climate change
Seo, S. B., Sinha, T., Mahinthakumar, G., Sankarasubramanian, A., & Kumar, M. (2016), Journal of Geophysical Research-Atmospheres, 121(13), 7652–7672.
Non-point source evaluation of groundwater contamination from agriculture under geologic and hydrologic uncertainty
Ayub, R., Obenour, D. R., Messier, K. P., Serre, M. L., & Mahinthakumar, K. (2016), (pp. 329–336).
Parallel evolutionary algorithm for designing water distribution networks to minimize background leakage
Shafiee, M. E., Berglund, A., Berglund, E. Z., Brill, E. D., & Mahinthakumar, G. (2016), Journal of Water Resources Planning and Management, 142(5).

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Water Distribution Modeling Experiments with the Cary Network
Sensus USA, Inc.(10/01/14 - 7/31/16)
Cybersees: Type II: Cyber-Enabled Water and Energy Systems Sustainability Utilizing Climate Information
National Science Foundation (NSF)(9/01/14 - 2/29/20)
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)
National Science Foundation (NSF)(8/15/11 - 7/31/16)
Development of a Scalable Parallel I/O Module for Environmental Management Applications
US Dept. of Energy (DOE)(7/27/10 - 9/30/12)
PERI: Application Engagement
US Dept. of Energy (DOE)(6/07/07 - 12/15/12)
Development of a Design Tool for Planning Aqueous Amendment Injection Systems
US Dept. of Defense (DOD)(3/31/06 - 3/31/12)
DDDAS-TMRP (Collaborative Research): An Adaptive Cyberinfrastructure for Threat Management in Urban Water Distribution Systems
National Science Foundation (NSF)(11/30/-1 - 12/31/09)
ITR: A Prototype to Enable Near Real-Time Environmental Characterization on the Grid
National Science Foundation (NSF)(9/01/03 - 8/31/07)
High-end Computer System Performance for Science and Engineering Applications
Oak Ridge National Laboratories - UT-Battelle LLC(10/01/02 - 12/31/06)