Pankaj Indurkar | Water Treatment | Research Excellence Award

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Mr. Pankaj Indurkar | Water Treatment | Research Excellence Award

Senior Scientist | Central Salt and Marine Chemicals Research Institute | India

Mr. Pankaj Indurkar is a researcher in membrane science, separation technology, and water purification, recognized for contributions that integrate advanced materials engineering with data-driven modeling. His work spans the development of high-performance ion-exchange membranes, mixed-matrix membranes, and polymeric frameworks designed for desalination, pollutant remediation, and industrial water processing. He has played key roles in designing electrodialysis, membrane distillation, and electro-deionization systems, contributing to indigenous technology development for saline water treatment, brackish water desalination, and ultrapure water generation. His research portfolio demonstrates strong expertise in synthesizing functional materials such as MOF-incorporated membranes, porous polymeric networks, nanocomposites, and metal-doped aerogels, complemented by extensive use of statistical modeling, multivariate optimization, response surface methodology, and machine learning for predicting membrane performance and enhancing process efficiency. He has published widely in high-impact journals on topics including heavy-metal remediation, fluoride and arsenic removal, electrodialysis modeling, neural-network-guided membrane design, and nanomaterial-based water purification strategies. His work also includes book chapters on MOF-based membranes for water and wastewater remediation and contributions to the development of computational frameworks for chemicals recovery from brines, integrating optimization, techno-economic analysis, and data analytics. Through collaborative and multidisciplinary projects, he has contributed to the fabrication, testing, and field deployment of membrane-based and adsorbent-based treatment units for industry and research institutions. His expertise reflects a blend of experimental innovation and computational intelligence aimed at advancing sustainable and energy-efficient water treatment technologies.

Profiles: Scopus | Orcid

Featured Publication

Pankaj, D. I., & Kulshrestha, V. (2025). Electrochemical informed machine learning models for prediction of electrodialysis desalination performance. Separation Science and Technology.

Kumar, P., Suhag, S., Indurkar, P. D., Shahi, V. K., & Kulshrestha, V.* (2025). Synthesis of polyacrylonitrile-based terpolymer cation exchange membrane for efficient brackish water desalination via electrodialysis with neural network prediction. Desalination.

Mishra, S., Upadhyay, P., Indurkar, P. D., & Kulshrestha, V.* (2025). Designing of PVDF-based cation exchange membranes with improved electrochemical properties for energy-efficient brackish water desalination. ACS ES&T Engineering.

Shukla, S., Gupta, A. R., Ratnakar, S. B., Ganguly, B., Indurkar, P. D., & Sharma, S. (2025). A revolutionizing polymeric framework with integrated aluminium fragment for superior water decontamination empowered by a statistical modeling approach. Journal of Materials Chemistry A, 13.

Sutariya, B., Sarkar, P., Indurkar, P. D., & Karan, S.* (2024). Machine learning-assisted performance prediction from the synthesis conditions of nanofiltration membranes. Separation and Purification Technology.

Zahra Askari | Water | Best Research Article Award

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Dr. Zahra Askari | Water | Best Research Article Award

Lorestan University | Iran

Dr. Zahra Askari is a postdoctoral researcher in water science whose work focuses on the complex interactions between hydrological processes, sediment dynamics, and climate change. Her research integrates experimental modeling and computational analysis to explore bed-load sediment transport, bed morphology changes, and the hydraulic behavior of open channels under unsteady flow conditions. She has contributed to advancing flood simulation and river discharge forecasting by applying soft computing, hybrid time series models, and machine learning approaches. Her academic interests span sediment transport mechanics, flood control, and the impact of climatic variability on river systems. Dr. Askari has authored and co-authored several publications in international journals such as Applied Water Science, Geosciences, Chinese Soil and Water Conservation, and Acta Geophysica. She is skilled in using advanced analytical and simulation tools, including Flow3D, HECRAS, MATLAB, and Python, to model complex hydraulic and hydrological phenomena. In addition to her research, she has experience teaching subjects related to hydraulic systems and applied mathematics at the university level. Recognized for her academic excellence, she has received awards for outstanding performance during her graduate studies and has served as a reviewer for scientific journals. Her ongoing work contributes to developing sustainable water management strategies and improving predictive modeling techniques for hydrological and environmental applications.

Profiles: Orcid | Google Scholar

Featured Publications

Askari, Z., Samadi-Boroujeni, H., Fattahi-Nafchi, R., Yousefi, N., Eslamian, S., … (2017). Prediction comparison of flow resistance in channels with rounded and angular coarse rough beds. American Research Journal of Civil and Structural Engineering, 3(1), 1–15.

Yousefi, N., Reza, K. S., & Eslamian, S. A. Z. (2016). Estimating width of the stable channels using multivariable mathematical models. Arabian Journal of Geosciences.

Moughani, S. K., Osmani, A., Nohani, E., Khoshtinat, S., Jalilian, T., Askari, Z., … (2024). Groundwater spring potential prediction using a deep-learning algorithm. Acta Geophysica, 72(2), 1033–1054.

Marani-Barzani, M., Eslamian, S., Amoushahi-Khouzani, M., Gandomkar, A., … (2017). Assessment of aridity using geographical information system in Zayandeh-Roud Basin, Isfahan, Iran. International Journal of Mining Science (IJMS), 3(2), 49–61.

Askari, Z., Afzalimehr, H., Singh, V. P., & Fattahi, R. (2015). Prediction of flow velocity near inclined surfaces with varying roughness. International Journal of Hydraulic Engineering, 4(1), 1–9.