Website: https://srmap.edu.in/faculty/dr-tapas/
Research Area: Ad hoc and Sensor Networks, Agricultural support System using Machine Learning, IoT.
Website: https://srmap.edu.in/faculty/dr-tapas/
Research Area: Ad hoc and Sensor Networks, Agricultural support System using Machine Learning, IoT.
Department of Computer Science and Engineering,
SRM University, Andhra Pradesh.
Email: tapaskumar.m@srmap.edu.in
Google Scholar ID: fl10llMAAAAJ
DBLP ID: 124/9334-2
Teaching Experience: 8 years
Ph.D. in Computer Science (2017), Indian Institute of Technology (ISM), Dhanbad, India.
M.Tech in Computer Science (2013) Utkal University, Bhubaneswar, India.
UGC NET Qualified for Assistant Professor in 2012
GATE Qualified in 2010, 2011, 2013 in good percentile. Best Rank in 2013 (RANK 1966).
Research Publications: 11 Journals, 18 Conferences, 5 Patents, 2 Book chapters, 1 edited book.
Sponsored Project: 1 Sanctioned, Funded by TEQIP-III of BPUT.
Google Scholar, DBLP, ORCID, SCOPUS
I have worked in the project titled: "Design of Reliable and Energy Efficient Protocols in Ad-Hoc Networks". The models have been simulated using the simulator NS-2.35. The objective of the work was to improve various aspects of reliability along with energy consumption. Here, we have attempted to reduce congestion and energy consumption. Moreover, we have focused to manage fairness among heterogeneous applications with priority to achieve reliability.
GATE-2013: All India Rank 1966 out of 224160
UGC-NET : Qualified for lectureship in June-2012 (Conducted by University Grants Commission)
GATE-2011: All India Rank 7840 out of 136027
PGAT-2011: All Odisha Rank 7 in General Category (Conducted by OJEE for M.Tech)
GATE-2010: All India Rank 4727 out of 107086
OJEE-2007 : All Odisha Rank 52 in General Category (Conducted by OJEE for MCA)
Languages Known and Tools: C, C++, Java, AWK, Python, NS-2, MATLAB, GNUPLOT
Scripts and Environments: HTML, LaTeX, OpenOffice, Linux, Microsoft Windows
Reliability and Energy Efficiency in Ad Hoc and Sensor Networks, Localization in Wireless Sensor Networks.
Climate Prediction using Sensor Networks and Data Analytics, Internet of Things,
Design and Analysis of Algorithms,
Data Analytics using Machine Learning Approach.