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Easter Suviseshamuthu
PeerJ Editor
300 Points

Contributions by role

Editor 300

Contributions by subject area

Computer Vision
Spatial and Geographic Information Systems
Bioinformatics
Computational Biology
Artificial Intelligence
Autonomous Systems
Computer Education
Data Mining and Machine Learning

Easter S Suviseshamuthu

PeerJ Editor

Summary

Dr. Suviseshamuthu is an Associate Research Scientist at the Human Performance and Engineering Research Lab, Kessler Foundation, West Orange, NJ, U.S.A., since Dec. 2015.

He received the B.E. degree in Electronics and Communication Engineering from the Government College of Engineering, Tirunelveli, India (1988), the M.E. degree in Applied Electronics from Bharathiar University, Coimbatore, India (2001), and the Ph.D. in Multispectral Satellite Image Analysis from the Laboratoire des Sciences de l’Information et des Systèmes, Université de la Méditerranée, Marseille, France (2007). He was Post-Doctoral Fellow at the Bioimaging and Biostructure Institute, Italian National Research Council, Naples, Italy, (2008 to 2010), the Department of Mathematical Engineering, Université catholique de Louvain, Louvain-la-Neuve, Belgium, (2010 to 2014), and the GIPSA-Lab, Université Joseph Fourier, Grenoble, France (2014 to 2015).
His research focus encompasses statistical signal processing, blind source separation, medical imaging, optimization on matrix manifolds, machine learning, biomedical signal analysis, and bio-inspired computing. He serves as Associate Editor of IEEE Access.

Artificial Intelligence Brain-Computer Interface Computer Vision Data Mining & Machine Learning Optimization Theory & Computation Radiology & Medical Imaging

Editorial Board Member

PeerJ - the Journal of Life & Environmental Sciences
PeerJ Computer Science

Work details

Associate Research Scientist

Kessler Foundation, NJ, USA
December 2015
Center for Mobility and Rehabilitation Engineering Research
I currently serve as a co-investigator in a project on neurophysiological evaluation of cancer weakness. I have been trained in EEG and EMG to process and analyze data from healthy, cancer, stroke, and traumatic brain injury subjects. With the help of advanced signal processing approaches, I try to understand the neural mechanisms underlying motor recovery, identify biomarkers that are crucial to design rehabilitation strategies, and evaluate the improvement due to therapeutic intervention. My research expertise also includes Riemannian optimization, machine learning, blind source separation, image processing, pattern recognition, bio-inspired computing, neural learning, and brain-computer interface.

Websites

  • Google Scholar

PeerJ Contributions

  • Edited 2

Academic Editor on

May 24, 2023
Postures anomaly tracking and prediction learning model over crowd data analytics
Hanan Aljuaid, Israr Akhter, Nawal Alsufyani, Mohammad Shorfuzzaman, Mohammed Alarfaj, Khaled Alnowaiser, Ahmad Jalal, Jeongmin Park
https://doi.org/10.7717/peerj-cs.1355
November 9, 2021
Gender and age detection assist convolutional neural networks in classification of thorax diseases
Mumtaz Ali, Riaz Ali
https://doi.org/10.7717/peerj-cs.738