Behrouz Mehdinejadiani | Porous Media | Best Researcher Award

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Md Lal Mamud | Hydrogeophysics | Best Researcher Award

Posted on by sciencefather

Dr. Md Lal Mamud | Hydrogeophysics | Best Researcher Award

 Postdoctorate at Pacific Northwest National Laboratory , United States

Md Lal Mamud is a Postdoctoral Research Associate in the Subsurface Science Group at the Pacific Northwest National Laboratory (PNNL). His expertise lies in hydrology, computational hydroscience, and geophysics, with a focus on predictive modeling of complex geosystems, groundwater flow, contaminant transport, and deep learning applications in geophysical exploration. His academic journey spans across Bangladesh and the United States, earning advanced degrees in Geology, Geophysics, and Hydrology. Throughout his career, he has contributed to cutting-edge Physics-Informed Machine Learning (PIML) models for CO₂ storage capacity prediction, geophysical data analysis, and critical mineral identification using AI-driven approaches. Before joining PNNL, he held research and teaching positions at Los Alamos National Laboratory (LANL), the University of Mississippi, and the National Center for Physical Acoustics (NCPA). His research contributions are widely recognized, with multiple peer-reviewed publications and international conference presentations in the field of hydrogeology and computational modeling.

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Education 🎓

Md Lal Mamud holds a Ph.D. in Hydrology and Computational Hydroscience from the University of Mississippi, where he focused on advanced groundwater modeling, uncertainty quantification, and AI-based geophysical exploration. He also earned an M.S. in Hydrology from the same institution, refining his expertise in subsurface modeling and environmental fluid dynamics. Prior to his studies in the U.S., he completed an M.S. in Geophysics from the University of Dhaka, Bangladesh, where he specialized in geophysical imaging, electrical resistivity tomography (ERT), and subsurface exploration. His academic foundation began with a B.S. in Geology from the University of Dhaka, where he developed expertise in earth sciences, structural geology, and remote sensing applications. His multidisciplinary education has provided him with a strong foundation in hydrogeological research, computational geophysics, and AI-driven subsurface modeling.

work Experience💼

Md Lal Mamud has a diverse background in academic research, national laboratories, and industrial collaborations. Currently, he is a Postdoctoral Research Associate at PNNL, where he is developing Physics-Informed Machine Learning (PIML) models for subsurface flow and contaminant transport. He previously worked as a Graduate Research Assistant at the National Center for Physical Acoustics (NCPA), where he conducted aquifer characterization, groundwater flow modeling, and geophysical data inversion. At Los Alamos National Laboratory (LANL), he contributed to high-performance computing (HPC) models for subsurface flow, uncertainty quantification, and deep learning applications in hydrology. Throughout his academic career at the University of Mississippi, he served as a Graduate Teaching Assistant, instructing courses in hydrogeology, geophysics, and computational modeling. His extensive fieldwork experience includes seismic surveys, electrical resistivity tomography (ERT), self-potential (SP) measurements, and electromagnetic (EM) surveys for environmental and energy applications.

Skills

Md Lal Mamud is proficient in multiple programming languages, including Python, MATLAB, FORTRAN, and Julia, for scientific computing and numerical modeling. His expertise in hydrogeological software includes PFLOTRAN, STOMP, MODFLOW, and PHREEQC, which he uses for groundwater and contaminant transport simulations. He is skilled in geophysical data analysis, utilizing tools such as EarthImager, Res2Dinv, GPRPy, and Petrel for subsurface characterization. His experience in GIS applications and geospatial modeling includes working with QGIS, ArcGIS, and Surfer for spatial data analysis and visualization. Additionally, he has hands-on experience with seismic data acquisition, ground-penetrating radar (GPR), and electromagnetic (EM) surveying techniques. His interdisciplinary skillset allows him to bridge geoscience, computational modeling, and artificial intelligence for innovative research solutions.

Research Focus

Md Lal Mamud’s research focuses on advanced computational modeling of hydrogeological and geophysical processes. He specializes in Physics-Informed Machine Learning (PIML) applications for subsurface flow, contaminant transport, and energy resource exploration. His work in AI-driven geophysical inversion includes deep learning models for CO₂ storage prediction, critical mineral identification, and multiphase flow modeling. He is actively involved in parameter estimation, uncertainty quantification, and high-performance computing (HPC) techniques for geoscience applications. His research also extends to remote sensing and UAV-based geophysical surveys, integrating drone-based electromagnetic and hyperspectral data for mineral exploration and environmental monitoring. With expertise in fluid dynamics, reservoir characterization, and predictive simulation, he aims to develop innovative solutions for sustainable energy and environmental challenges.

Awards & Honors🏆 

Md Lal Mamud’s research excellence has been recognized through multiple prestigious awards. He received the David Miller Young Scientist Scholarship (2022) from the American Geophysical Union (AGU) for his outstanding contributions to geophysical modeling. His excellence in teaching earned him the Outstanding Teaching Assistant Award (2022) from the National Association of Geoscience Teachers (NAGT). He was honored with the Outstanding Ph.D. Graduate Student Award (2020 & 2022) at the University of Mississippi, acknowledging his exceptional research contributions. He also received the On To the Future (OTF) Award (2022) from the Geological Society of America (GSA), which supports emerging researchers in the geosciences. Additionally, he has been awarded travel grants and summer research assistantship awards from esteemed institutions to support his participation in international conferences and field research.

Conclusion✅

Lal Mamud is a strong candidate for the Best Researcher Award, given his outstanding contributions to hydrology, geophysics, AI-driven modeling, and computational sciences. His scientific rigor, technical expertise, and leadership roles make him a distinguished researcher in his field. While he can further enhance his research profile by increasing his publication count and securing independent research funding, his innovative research, academic excellence, and impact on the scientific community make him a deserving nominee for the award.

 

📚Publications to Noted

 

Integrating ERT and SP Techniques for Characterizing Aquifers and Surface-Groundwater Interactions (2024)

Authors: M. L. Mamud, R. M. Holt, C. J. Hickey, A. M. O’Reilly, L. T. Wodajo, P. B. Rad, M. A. Samad

Journal: Groundwater

 

Quantifying Local and Global Mass Balance Errors in Physics-Informed Neural Networks (2024)

Authors: M. L. Mamud, M. K. Mudunuru, S. Karra, B. Ahmmed

Journal: Scientific Reports

 

Integrated Agrogeophysical Approach for Investigating Soil Pipes in Agricultural Fields (2022)

Authors: M. A. Samad, L. T. Wodajo, P. B. Rad, M. L. Mamud, C. J. Hickey

Journal: Journal of Environmental and Engineering Geophysics

 

Agrogeophysical Methods for Identifying Soil Pipes (2021)

Authors: L. T. Wodajo, P. B. Rad, S. I. Sharif, M. A. Samad, M. L. Mamud, C. J. Hickey, G. V. Wilson

Journal: Journal of Applied Geophysics

 

Structural Modeling of Fenchugang Gas Field, Sylhet, Bangladesh (2016)

Authors: M. L. Mamud, A. S. M. Woobaidullah, M. A. Baki, R. C. Chowdhury, M. Z. H. Sazal, M. S. Islam, M. A. Khan

Journal: International Journal of Emerging Technology and Advanced Engineering

 

Case Study on Surrounding Area of Barapukuria Coal Mine Impeding Soil Fertility (2016)

Authors: T. Mohanta, S. Akter, C. Quamruzzaman, M. L. Mamud, M. Z. H. Sazal, K. M. I. Hossain

Journal: International Journal of Scientific & Engineering Research