What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Climate change
Balaji Rajagopalan mostly deals with Climatology, Sea surface temperature, Precipitation, Streamflow and Meteorology.
Balaji Rajagopalan specializes in Climatology, namely Monsoon.
His study in Sea surface temperature is interdisciplinary in nature, drawing from both Smoothing and Covariance.
His Precipitation study combines topics from a wide range of disciplines, such as Land cover, Statistics, Kriging and Evapotranspiration.
The concepts of his Streamflow study are interwoven with issues in Snow, Structural basin, Geopotential height and Water resources.
His biological study deals with issues like Subsidence, which deal with fields such as Climate model, Forcing and Atmospheric sciences.
His most cited work include:
- Analyses of global sea surface temperature 1856–1991 (1306 citations)
- On the Weakening Relationship Between the Indian Monsoon and ENSO (1118 citations)
- Unraveling the Mystery of Indian Monsoon Failure During El Niño (514 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Climatology, Precipitation, Streamflow, Meteorology and Statistics.
As part of his studies on Climatology, Balaji Rajagopalan often connects relevant subjects like Climate change.
Balaji Rajagopalan has included themes like Watershed, Surface runoff and Kriging in his Precipitation study.
His work in Streamflow covers topics such as Water resources which are related to areas like Snow.
His Statistics research includes elements of Feature vector and k-nearest neighbors algorithm.
His research in Monsoon is mostly focused on Monsoon of South Asia.
He most often published in these fields:
- Climatology (55.05%)
- Precipitation (28.72%)
- Streamflow (28.72%)
What were the highlights of his more recent work (between 2015-2021)?
- Climatology (55.05%)
- Precipitation (28.72%)
- Hydrology (15.43%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Climatology, Precipitation, Hydrology, Streamflow and Climate change.
His Climatology research is multidisciplinary, relying on both Arctic and Holocene.
His research in Precipitation intersects with topics in Covariate, Generalized linear model and Climate model.
His study looks at the relationship between Hydrology and topics such as Sewage treatment, which overlap with Random forest.
His Streamflow research is multidisciplinary, incorporating perspectives in Stochastic simulation, Wavelet, Surface runoff and Hidden Markov model.
The Climate change study combines topics in areas such as Water balance and Seasonality.
Between 2015 and 2021, his most popular works were:
- Climate Change and the Emergent Epidemic of CKD from Heat Stress in Rural Communities: The Case for Heat Stress Nephropathy (155 citations)
- Automated content analysis for construction safety: A natural language processing system to extract precursors and outcomes from unstructured injury reports (83 citations)
- Application of machine learning to construction injury prediction (74 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Climate change
Climatology, Climate change, Precipitation, Meteorology and Parametric statistics are his primary areas of study.
His studies in Climatology integrate themes in fields like Streamflow, Downscaling and Mode.
His work carried out in the field of Climate change brings together such families of science as Seasonality, Spatial variability, Monsoon of South Asia, Water balance and El Niño Southern Oscillation.
His Precipitation research is multidisciplinary, relying on both Climate model, Forcing, Evapotranspiration and Weather Research and Forecasting Model.
While the research belongs to areas of Meteorology, he spends his time largely on the problem of Data set, intersecting his research to questions surrounding Interpolation, Inverse distance weighting and Visual inspection.
His work deals with themes such as Random variable, Calibration, Structural engineering, Finite element method and Covariance matrix, which intersect with Parametric statistics.
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