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Fr. Dr. Joseph Mathew
B.E In Electronics & Instrumentation, ME IN EMBEDDED SYSTEM TECHNOLOGIES, Ph.D.
Asst Professor & Dean- Student Affairs
DEPARTMENT OF APPLIED ELECTRONICS AND INSTRUMENTATION

Fr. (Dr.) Joseph Mathew completed his Bachelor of Philosophy in 2002. In the same year, he began his Bachelor of Engineering studies in the Department of Electronics and Instrumentation at Sathyabama Deemed to be University, Chennai. In 2007, he pursued Theological studies at Dharmaram Vidya Kshetram.

In 2010, he joined Rajagiri School of Engineering College as a lecturer in the Department of Applied Electronics and Instrumentation. Concurrently, he completed his M.E in Embedded System Technologies from Anna University, Chennai. He earned his doctoral degree from the Department of Instrumentation and Control Engineering at the National Institute of Technology, Tiruchirappalli. His doctoral thesis, titled "Non-stationary Analysis of EEG Measurements for the Detection of Seizure Types and Localization of Epileptic Brain Tissues," highlights his focus on biomedical engineering.

He has significantly contributed to the academic community by attending numerous international conferences, publishing many papers in international journals, authoring a book chapter, and presenting research findings globally. Notably, he published a paper in IEEE Transactions on Instrumentation and Measurements, titled "Variational Mode Decomposition Based Moment Fusion for the Accurate Detection of Seizure Types from Scalp EEG Measurements."

He is associated with IEEE membership and the Instrumentation Society of India (ISOI). His research interests include biomedical signal processing, instrumentation, and machine learning.


RSET Unique Id: 31610
Email josephc@rajagiritech.edu.in
Website people.rajagiritech.ac.in/josephc
PUBLICATION-CONFERENCE/JOURNAL DETAILS
Year Title of the Paper-Conference/Journal Details
2023 Variational Mode Decomposition based Moment Fusion for the Detection of Seizure Types from the Scalp EEG Measurements
IEEE Transactions on Instrumentation and Measurement
2022 Detection of seizure types from the wavelet energy of scalp EEG
Biomedical sciences Instrumentation
2022 Automated Detection of Seizure Types from the Higher-Order Moments of Maximal Overlap Wavelet Distribution.
Diagnostics
PUBLICATION-BOOKS
Year Date of Publication Title of the Book Published By Edition
2022 22-Apr-2022 Detection of Tonic-ClonicSeizures Using Scalp EEG of Spectral Moments Cham: Springer International Publishing. Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders