Team

The Computational Lab for Advanced Water Resources Informatics and Modeling (CLAWRIM) is Dr. Huidae Cho’s research group in the Department of Civil Engineering at New Mexico State University (NMSU).

Huidae Cho is an Associate Professor specializing in Water Resources Engineering, and Geospatial Analytics and Computing. He is also a Senior GIS Developer with more than 20 years of experience in industry and open-source software development since 2000.

Abdullah Azzam is a Ph.D. student with an experience of four years in Hydrology, Water Resources Engineering, Remote Sensing, and Geospatial Analytics. He is currently working on the “USGS WRRA 104b New Mexico Statewide Drought Vulnerability Analysis Under Future Climate Change Scenarios Using a Physically-Based Coupled Model” and “USGS Mesilla Aquifer – Transboundary Aquifer Assessment Program (TAAP) – Development of a New Groundwater Model Using Publicly Available Datasets for Transboundary Aquifer Modeling” projects.

Nelson Kandel is a Master’s student with a year of computational research experience. He is working on the “Quantum Routing of Shallow Water Flows” project. His research interests extend to the development of parallel and quantum algorithms for hydrologic and hydraulic problems.

Ujjwal Marasini is a Ph.D. student with a couple years of experience in Hydrologic and Hydraulic Modeling. He is currently working on the “NMED Elucidating Fate and Transport Processes and Impacts of Treated Produced Water in the Subsurface” project and snow water equivalent forecasting.

Hari Shreesh is a Master’s student. He is currently working on the “NSF DISES Water and Community Resilience Through Spatial Integration of Ecohydrological Processes and Traditional Sociocultural Knowledge” project. His research also encompasses advanced application of deep learning to flood inundation mapping.

Madan Pokhrel is a Ph.D. student with experience in Water Resources Engineering. He is working on the “USDA Resilient Agriculture-Water-Community Systems: Transcending Water Scarcity With Community-Based And Networked Western Water Management Solutions (RAWCS)” project and snow water equivalent forecasting. His areas of interest include hydrological modeling, the application of remote sensing in hydrology, and optimization.

Dung Tuan Ho is a Ph.D. student in Computer Science at New Mexico State University. His research focuses on multi-agent systems, learned representations, decision-making, and reasoning, with applications in adaptive task-solving and Large Language Model (LLM) agents. With over five years of enterprise software development experience, he is passionate about integrating AI and advanced computing techniques to build intelligent and scalable systems. He is currently working on the “NSF POSE Growing GRASS OSE for Worldwide Access to Multidisciplinary Geospatial Analytics” project.

Jason Pena is a Master’s student majoring in Computer Science. He specializes in software engineering and embedded systems programming. He is working on the “Internet of Things Large-Scale Particle Image Velocimetry (IoT LSPIV)” project. His areas of interest include real time operating system design, and emulator design.

Former Students

Baokun Li was a Master’s student majoring in Computer Science. He worked on hydrologic forecasting using deep learning. He holds a Ph.D. in Mathematics and has moved to Texas A&M University – Corpus Christi as a Postdoctoral Research Associate in Data Science.

Rene Diaz was a senior student majoring in Geography. He worked on data creation for the “NSF POSE Growing GRASS OSE for Worldwide Access to Multidisciplinary Geospatial Analytics” project.

Mahesh Maddineni was a Master’s student majoring in Computer Science. He had 1.5 years of work experience as a Software Engineer and 2 years of work experience as a Cloud & DevOps Engineer in the IT industry. He worked on the “NSF POSE Growing GRASS OSE for Worldwide Access to Multidisciplinary Geospatial Analytics” project.

S.M. Asaduzzaman Reshad was a Master’s student. He specializes in advanced large-scale watershed modeling. He worked on the “NMDOT Culvert Asset Management Program (CAMP)” project, with a focus on improving expertise and analytical skills through the integration of cutting-edge physical and machine learning models. He is an aspiring researcher dedicated to making substantial contributions to the field of water resources management and sustainability, aiming to address critical challenges and drive positive environmental impact.