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Dr. Rinku Jacob
Ph.D. (Physics), M.Sc. Physics
Asst. Professor
DEPARTMENT OF BASIC SCIENCE & HUMANITIES

Dr. Rinku Jacob completed his graduation in Physics from Aquinas College, Edacochin and post graduation from St. Albert's College, Ernakulam.  He started his teaching career as Ad hoc Lecturer in the Department of Physics, Aquinas College and then as Ad hoc Lecturer in the Department of Physics, St. Albert's College, Ernakulam.  Then he joined a Major project as a JRF fellow in The Cochin College, Kochi.   He has been working as Assistant Professor in Physics under the Department of Basic Sciences & Humanities of Rajagiri School of Engineering & Technology, Kochi since 11.09.2017.  He obtained his PhD in Physics from Mahatma Gandhi University, Kottayam in 2018.  His research area is in the nonlinear time series analysis of the light curves from black holes, especially multivariate light curves in different band using complex networks and recurrence plots.  He is an approved research guide of A P J Abdul Kalam Technological University, Kerala. He is also a Visiting Associate of Inter - University Centre for Astronomy and Astrophysics (IUCAA), Pune from August 2019 onwards. He has a research project with funding from DST-SERB which started in January 2021.

RSET Unique Id: 31860
Area of Interest: Nonlinear Dynamics, Nonlinear Time series Analysis, Astrophysics, Numerical computation, ECG analysis
Memberships(If Any) IAPT Life Member 12091L8048, ISTE Life Member LM 127650, Visiting Associate of IUCAA, Pune
ORCID_iD http://www.orcid.org/0000-0003-2167-1703
Google Scholar ID https://scholar.google.com/citations?user=OWV9578AAAAJ&hl=en&authuser=1
Website people.rajagiritech.ac.in/rinkuj
PUBLICATION-CONFERENCE/JOURNAL DETAILS
Year Title of the Paper-Conference/Journal Details
2018 Weighted recurrence networks for the analysis of time- series data
Proceddings of the Royal Society A
2017 Recurrence network measures for hypothesis testing using surrogate data: Application to black hole light curves
Communications in Nonlinear Science and Numerical Simulation
2016 Uniform framework for the recurrence-network analysis of chaotic time series.
2016 Characterization of chaotic attractors under noise: A recurrence network perspective
2016 Can recurrence networks show small – world property?.
2016 Measure for degree heterogeneity in complex networks and its application to recurrence network analysis
2016 Recurrence network measures for hypothesis testing using surrogate data : Application to black hole light curves
2016 Cross over of recurrence networks to random graphs and random geometric graphs