Thippeswamy Muddenahalli Nagendrappa
NITTE Meenakshi Institute of Technology, University of KwaZulu-Natal, MS Ramaiah Institute of Technology, Jawaharlal Nehru National College of Engineering
About
Muddenahalli NagendrappaThippeswamy received the B.Eng (Computer Science and Engineering) degree from the Kuvempu University, India in 1995 and an M.tech (Computer Science and Engineering) degree from VTU, India in 2001 and Ph.D. in Electronic Engineering at the University of Kwazulu- Natal, Durban, South Africa. He is currently with the department of CSE, SVCE, Bangalore. Prior to joining the SVCE, he had been with University of Kwazulu- Natal, Durban, South Africa (2008-2012), the National University of Lesotho (2006 - 2007), the Bahir Dar University, Ethiopia (2002 – 2006) and with the SIT, India (1997 - 2002). His research interests include multiple access protocols, data networks and wireless sensor networks.
Employment
-
NITTE Meenakshi Institute of Technology Professor and HoD2015 - Present
Education
-
University of KwaZulu-Natal PHd2007 - 2012
-
MS Ramaiah Institute of Technology M.Tech1999 - 2001
-
Jawaharlal Nehru National College of Engineering BE1991 - 1996
Projects & Funding
Projects & funding information is unavailable.
Publications (28)
- Multi-level Hierarchical Information-Driven Risk-Sensitive Routing Protocol for Mobile-WSN: MHIR-SRmW Save
- Fake Product Identification System Using Blockchain Save
- Static and Dynamic Human Activity Detection Using Multi CNN-ELM Approach Save
- Smart College Camera Security System Using IOT Save
- MHCT: Determining Member Head of Cyber Terrorists in Social Blog Networks Save
- Application of Quantum Algorithms for Network Protocols Save
- Analysing Machine Learning Techniques in Python for the Prediction of Diabetes Using the Risk Factors as Parameters Save
- A customized 1D-CNN approach for sensor-based human activity recognition Save
- Sentiment analysis for user reviews using Bi-LSTM self-attention based CNN model Save
- PRGR-C19: Profiling Rapid Growth Regions of COVID-19 Pandemic, A Data-Driven Knowledge Discovery Approach Save