Data Analytics and Artificial Intelligence for Earth Resource Management

Dr. Deepak Kumar is a Research Scientist in the Atmospheric Sciences Group at Texas Tech University. He previously served as a Research Scientist at the Atmospheric Sciences Research Center, State University of New York at Albany, and as an Assistant Professor at Amity University, Delhi-NCR. His research focuses on geospatial sciences, computational sciences, climate change, sustainability, and the urban–climate–energy nexus. His work integrates remote sensing, geoinformatics, environmental studies, energy systems, urban weather, and climate modelling to support interdisciplinary research and policy applications. Dr. Kumar has experience in research design, data analysis, modelling, visualization, and implementation across environmental and climate-related projects. He also contributes to academic and professional activities through conference participation, outreach, training, and scholarly associations. Dr. Tavishi Tewary has over 16 years of experience in policy research and trade impact assessment. She has published various research papers in international journals of high repute. She has academic experience teaching postgraduate business school students. She also has experience in providing scientific leadership to high-profile strategic sustainability and conservation initiatives with several years of research experience. She managed cross-sectoral and interdisciplinary teams of professionals to deliver on complex research projects. Currently, she is working as an Assistant Professor at FORE School of Management, New Delhi (India). Her area of interest covers international trade analysis, sustainability, international economics, socioeconomic development, energy, circular economy, and Industry 4.0. She has presented several research papers at international and national conferences on these topics. She has authored a book on circular economy with a publisher of international repute. She has also conducted FDPs on data analysis using SPSS, PLS-SEM, and EViews. Also, she has experience in providing scientific leadership to high-profile strategic sustainability and conservation initiatives with several years of research experience.Dr. Sulochana Shekhar is the Dean of the School of Earth Sciences at the Central University of Tamil Nadu, Thiruvarur, India. Her research interests include urban geography and the application of remote sensing and geospatial techniques in urban environments. She has worked on cellular automata-based urban growth models and urban sprawl assessment using entropy for her doctoral research. Object-based image analysis was the main theme of her postdoctoral research at ITC, the Netherlands. She has previously worked on projects involving spatial decision support systems for slums (UCL, UK) and extraction of slums and urban green space using object-based image analysis (UTAS, Australia). She has completed major funded projects on housing the urban poor (HUDCO) and the environmental impact of urbanization (UGC Major) using geospatial techniques. She has collaborated with Cambridge University, UK and completed the UKIERI research project on the interactive spatial decision support system for managing public health.

• Data analytics and artificial intelligence in Earth resource managementData analytics enabled by the Internet of Things and artificial intelligence for the management of Earth’s resourcesData preprocessing techniques for earth resource managementArtificial intelligence for sustainable stewardship of Earth resourcesAdvancing earth resource management through AI enhanced early warning systems and crisis communicationArtificial intelligence for analytical evaluation of landslide vulnerabilitySocioeconomic and environmental impacts analysis for climate resilient Earth resource managementData analytics for drought vulnerability under climate change scenariosNatural Language Processing for Earth resource management: a case of H2 Golden Retriever researchArtificial intelligence in efficient management of water resourcesGroundwater potential zone evaluations for improving resource management with spatial analysis approachFuture trends in computational data analytics and artificial intelligence for Earth resource management