Geospatial Information and Services for Climate Resilient Disaster Management

Dr. Deepak Kumar is an early career academic research professional with a multidisciplinary academic background in geospatial sciences, computational sciences, climate change, and sustainability with over 10 years of experience. Dr Kumar has been working in interdisciplinary research towards the urban–climate–energy nexus to advance policies considering humanities, social science, and technology perspectives. Presently, he is working as a Research Scientist at the Center of Excellence in Weather and Climate Analytics, Atmospheric Science Research Center (ASRC), State University of New York at Albany, New York (United States). He has been also associated as a full-time Assistant Professor with Amity University, Uttar Pradesh, Noida (India). He has been revisiting a wide range of issues associated with traditional research activities in the intersection area of remote sensing and geoinformatics, environment, energy, climate change, urban weather and climate modelling, analysis, and visualization. He has wide experience in research pipeline embracing idea conceptualization, research design, data collection, processing, analysis and result generation. He completed two government-sponsored research projects sponsored as a sole principal investigator, supervised cross-functional research group of 4 PhD and 29 postgraduate students, and conducted 15 academic, research, and industrial visits for undergraduate students. He has published 50+ research articles in a high-impact web of science/Scopus-indexed international journals by Elsevier, Springer, Taylor & Francis, Emerald, SAGE, and Wiley publications. He has reviewed more than 220+ research articles as an ad hoc/adjunct/invited reviewer or editorial board member for high-impact factor journals published by IEEE, Elsevier, Springer Nature, Taylor & Francis Group, Wiley, SAGE, Emerald, and MDPI. He has authored/edited/co-edited 9 books with Elsevier, Springer, Taylor & Francis, Emerald, SAGE, and Wiley publications. He has been dedicated to finding solutions to complex problems in the areas of climate change, urban planning, energy, the environment, and sustainability (SDGs 7, 10, 11, and 13).

Nick P. Bassill has several years of experience in climate computing research and its impact assessment. Dr. Bassill received his PhD in Atmospheric and Oceanic Sciences from the University of Wisconsin-Madison, with a research focus on ensemble and parameterization studies. Afterwards, he worked as a post-Doctoral researcher at the University of Utah, where he studied aspects of Hurricane Sandy’s unusual track (including what led some models to make an incorrect forecast). Afterwards, he began work as a Post-Doctoral researcher with the New York State Mesonet to begin building an operational analysis system that would utilize Mesonet observations. Concurrently, he is actively involved in building meteorological products for and doing basic research with the New York State Mesonet. Currently, Nick predominantly spends his time working with the Center of Excellence on a variety of projects. He has published various research papers in international journals of high repute. He has also conducted sessions on Numerical weather prediction, with a specialization in WRF modelling, Data assimilation, Weather forecasting, Tropical cyclones, Data analysis of both gridded model data and weather observations and the New York State Mesonet. He also has experience in providing scientific leadership to high-profile strategic computational sustainability and conservation initiatives with several years of research experience. Managed cross-sectoral and interdisciplinary teams of professionals to deliver on complex research projects. Currently, he is working as a Director of Research & Development the at Center of Excellence, State University of New York at Albany. His core area of Interest covers Financial Markets, Energy & Utilities, Emergency Management, Risk Management, Climate Computing, AI and Machine Learning, and Industry 4.0.