U Kumaran
Papers
2
Total Citations
100
H-Index
2
About
U Kumaran is a researcher at the forefront of artificial intelligence applications in healthcare and human-computer interaction. His primary research areas span speech emotion recognition, biomedical informatics, and pharmacovigilance, where he leverages deep learning and natural language processing to solve real-world problems. Kumaran’s most impactful contribution is his work on speech emotion recognition, where he pioneered the fusion of Mel and Gammatone frequency cepstral coefficients using a deep convolutional recurrent neural network (C-RNN). This innovative approach, published in 2021, has garnered 84 citations, establishing a new benchmark for accurately detecting human emotions from speech signals. In the critical domain of drug safety, Kumaran developed a supervised classifier to predict adverse drug side-effects by mining open-source health forums. This 2020 study, with 16 citations, demonstrates his commitment to using AI for public health, offering a proactive method to identify dangerous drug reactions from patient-reported data. His work uniquely bridges the gap between signal processing and clinical informatics, making him a notable figure in applied machine learning.
Research Focus
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Top Papers
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