Soumik Sarkar

This study evaluates GRU and LSTM for seizure detection in animal EEG data from rats exposed to kainate or Soman, showing better performance than classical models.

This study compares nanoscale mechanical properties of cotton fibers between two species and develops machine learning models to predict phenotypic traits using multi-omics data.

This paper compares genomic and phenomic prediction for soybean seed yield, protein, and oil content, finding phenomic prediction outperforms genomic for yield while genomic is better for protein and oil.

The paper compares spatial adjustment methods in plant breeding trials, finding that XGBoost improves yield estimates by incorporating soil feature modeling at different scales.

This paper uses deep learning to predict soybean yield by integrating genotype and weather data from historical trials.