Shashi Kumar G S

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Phone8970094573
Emailshashi.gsmanipaledu
Websitehttps://manipal.edu/mit/department-faculty/faculty-list/shashi-kumar-gs/_jcr_content.html

MIT Campus, Manipal, Karnataka State. Pin 576104
India

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Research activity per year

Research interests

Signal Processing, Pattern recognition & Machine Learning

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Dive into the research topics where Shashi Kumar G S is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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4 Article
1 Chapter

Tamil sign language using relational bilevel aggregation graph convolutional network
Siddaramaiah, S. K. G. & Vinoth, R., 2025, In: International Journal of Systems, Control and Communications. 16, 1, p. 1-16 16 p.
Research output: Contribution to journal › Article › peer-review
Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers
Chadaga, K., Prabhu, S., Sampathila, N., Chadaga, R., Umakanth, S., Bhat, D. & G S, S. K., 12-2024, In: Scientific Reports. 14, 1, 1783.
Research output: Contribution to journal › Article › peer-review

Open Access
43 Citations (Scopus)
An explainable multi-class decision support framework to predict COVID-19 prognosis utilizing biomarkers
Chadaga, K., Prabhu, S., Bhat, V., Sampathila, N., Umakanth, S., Chadaga, R., Shashi Kumar, G. S. & Swathi, K. S., 2023, In: Cogent Engineering. 10, 2, 2272361.
Research output: Contribution to journal › Article › peer-review

Open Access
6 Citations (Scopus)
Classification of human emotional states based on valence-Arousal scale using electroencephalogram
Shashi Kumar, G., Sampathila, N. & Martis, R., 01-04-2023, In: Journal of Medical Signals and Sensors. 13, 2, p. 173-182 10 p.
Research output: Contribution to journal › Article › peer-review
9 Citations (Scopus)
Neural network approach for classification of human emotions from EEG signal
Shashi Kumar, G. S., Sampathila, N. & Shetty, H., 01-01-2019, Lecture Notes in Electrical Engineering. Springer Verlag, p. 297-310 14 p. (Lecture Notes in Electrical Engineering; vol. 478).
Research output: Chapter in Book/Report/Conference proceeding › Chapter
6 Citations (Scopus)

Shashi Kumar G S

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Research interests

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Collaborations and top research areas from the last five years

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Tamil sign language using relational bilevel aggregation graph convolutional network

Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers

An explainable multi-class decision support framework to predict COVID-19 prognosis utilizing biomarkers

Classification of human emotional states based on valence-Arousal scale using electroencephalogram

Neural network approach for classification of human emotions from EEG signal

Shashi Kumar G S

Personal profile

Research interests

Fingerprint

Collaborations and top research areas from the last five years

Research output

Tamil sign language using relational bilevel aggregation graph convolutional network

Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers

An explainable multi-class decision support framework to predict COVID-19 prognosis utilizing biomarkers

Classification of human emotional states based on valence-Arousal scale using electroencephalogram

Neural network approach for classification of human emotions from EEG signal