Data Driven Computing in Civil Engineering© A. Dasgupta
Challenges and Objectives
Recent progress in the fields of machine learning, data assimilation, Earth Observation and cloud computing, demands further research to unlock their full potential for disaster management, specifically in the context of water extremes. Novel research must leverage these cutting edge advances, to solve persisting challenges in flood science and contribute to operational disaster intelligence products.
Today, many satellites that record observations in the wavelength range of the electromagnetic spectrum with the highest water sensitivities, have been collecting data for decades. It is conceivable that these long term data archives contain information regarding the relationships between different hydrological variables at different scales which can be mined using deep learning.
The DDC Lab at IWW, thus, tackles these important issues related to understanding scale-relevant
hydrological processes improving resilience towards climate induced disasters, by leveraging the
latest technological advancements and innovative sensing techniques.
Tasks and methods of research© A. Dasgupta
We use Earth Observation and citizen science data, as well as advanced techniques such as machine learning and data assimilation, information theory and physics-based modelling of geohazards, to improve the prediction and post-event estimation of water hazards as shown in the figure. We also aim to improve science communication and accessibility, specifically for marginalised groups and the general public, by writing popular science
articles and organising scicomm sessions at international conferences.
The scientific objectives
are achieved through a multi-pronged approach to improve multiple aspects of high and low flow forecasting, monitoring, and preparedness. In addition to our own expertise being highly interdisciplinary, we regularly interface with computer scientists, social scientists, and philosophers of science, as well as NGOs, community partners and local and state governments to integrate local indigenous knowledge and develop tailored solutions. Each of these diverse sectoral perspectives are both horizontally and vertically integrated within our research to develop science for solutions aligned with the goals of the International Association of Hydrological Sciences’ Next Decade 2023-33.
We are open to hosting at-risk scholars through the Philipp Schwartz Initiative, postdocs through the
Humboldt Scholarship, DAAD PRIME Fellowship, the MSCA Scholarship and PhD exchange
students through DAAD Doctoral Fellowships. Apart from this, if your research is aligned to any of
my research interests, feel free to get in touch and we can try to find funding options for you together!