Engineering topics
Publications and source records attributed to Agarwall, Deb.
Focus areas: (1) Data assimilation enabled by machine learning, unsupervised learning (including deep learning), and (2) Predictive modeling through the use of AI techniques and AI-derived model components, comprising a hierarchy of models.
The experimental and observational data is the backbone of effective modeling of all aspects of water cycles. As the computer technology used for these data gathering efforts has improved dramatically in the recent decades, the environmental conditions these instruments are subjected to remain pretty much the same. These measuring instruments are exposed to the sun light, wind, rain, snow and ice; and they are immersed in dirt, water and mud. All of these are damaging to the electronics components used for data gathering, storage, and transmission, which creates many different kinds of data quality issues that affect the quality and reliability of modeling and prediction efforts.