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PeerJ Editor & Author

2,100 Points

Contributions by role

Contributions by subject area

Nageswara Rao Moparthi

PeerJ Editor & Author

Summary

Dr. M. Nageswara Rao is a Professor within the Dept. of Computer Science and Engineering, K L University, India. He has over 19 years of experience in the S/W industry and academia. Dr. M. Nageswara Rao has published over 20 articles in reputed international journals, written 2 books and filed 2 Indian patents. He is a reviewer for a number of SCI/SCIE journals, including IEEE Access and Journal of Big Data(JBD) Journal of Database Management, Cluster Computing , NHIB and Information Sciences; and Scopus journals, such as IJAIP, IJDS, CIT and IJECE. Dr. M. Nageswara Rao is also an associate TPC member for the following International conferences: ICACII-2019-Springer (India), ICCET-2020-IEEE/WOS (New Zealand), ITIoT/ICCCS 2020-Shanghai (China), JCICE-Sydney (Australia), BDET-2020-ACM Digital Library (Singapore) and ICCMA 2019-IEEE (TU Delft, Netherlands).

Dr. M. Nageswara Rao's research areas are listed below:

1.Data Mining
2. Data Analytics
3.Machine Learning
4. Software Engineering
5. Artificial Intelligence

Artificial Intelligence Computer Networks & Communications Data Mining & Machine Learning Data Science Databases Internet of Things Software Engineering

Editorial Board Member

PeerJ Computer Science

Work details

PROFESSOR

KL University

June 2019

Computer Science and Engineering

I am working as professor in Department of Computer Science and Engineering. I had 7 years of research cum teaching and 12 years IT industry.

Associate Professor

Velagapudi Ramakrishna siddhartha Engineering College

December 2016 - April 2019

Computer Science and Engineering

Websites

PeerJ Contributions

Edited 18

Academic Editor on

November 11, 2024

A comparative analysis of variants of machine learning and time series models in predicting women’s participation in the labor force

Rasha Elstohy, Nevein Aneis, Eman Mounir Ali

https://doi.org/10.7717/peerj-cs.2430

September 23, 2024

Revolutionizing diabetic eye disease detection: retinal image analysis with cutting-edge deep learning techniques

Banumathy D, Swathi Angamuthu, Prasanalakshmi Balaji, Mousmi Ajay Chaurasia

https://doi.org/10.7717/peerj-cs.2186

March 27, 2024

Structural health monitoring of aircraft through prediction of delamination using machine learning

Rajeswari D, Osamah Ibrahim Khalaf, Srinivasan R, Pushpalatha M, Habib Hamam

https://doi.org/10.7717/peerj-cs.1955

October 12, 2023

Heart disease severity level identification system on Hyperledger consortium network

Sasikumar R., Karthikeyan P.

https://doi.org/10.7717/peerj-cs.1626

August 7, 2023

A federated learning framework based on transfer learning and knowledge distillation for targeted advertising

Caiyu Su, Jinri Wei, Yuan Lei, Jiahui Li

https://doi.org/10.7717/peerj-cs.1496

July 20, 2023

CAM-YOLO: tomato detection and classification based on improved YOLOv5 using combining attention mechanism

Seetharam Nagesh Appe, Arulselvi G, Balaji GN

https://doi.org/10.7717/peerj-cs.1463

February 15, 2023

Healthy-unhealthy animal detection using semi-supervised generative adversarial network

Shubh Almal, Apoorva Reddy Bagepalli, Prajjwal Dutta, Jyotismita Chaki

https://doi.org/10.7717/peerj-cs.1250

September 30, 2022

Artificial intelligence framework for modeling and predicting crop yield to enhance food security in Saudi Arabia

Mosleh Hmoud Al-Adhaileh, Theyazn H.H. Aldhyani

https://doi.org/10.7717/peerj-cs.1104

September 20, 2022

OES-Fed: a federated learning framework in vehicular network based on noise data filtering

Yuan Lei, Shir Li Wang, Caiyu Su, Theam Foo Ng

https://doi.org/10.7717/peerj-cs.1101

July 29, 2022

Is gender-based violence a confluence of culture? Empirical evidence from social media

Rimjhim, Sourav Dandapat

https://doi.org/10.7717/peerj-cs.1051

April 12, 2022

How to get best predictions for road monitoring using machine learning techniques

Imen Ferjani, Suleiman Ali Alsaif

https://doi.org/10.7717/peerj-cs.941

March 2, 2022

Development of a stock trading system based on a neural network using highly volatile stock price patterns

Jangmin Oh

https://doi.org/10.7717/peerj-cs.915

February 9, 2022

Bots in software engineering: a systematic mapping study

Sivasurya Santhanam, Tobias Hecking, Andreas Schreiber, Stefan Wagner

https://doi.org/10.7717/peerj-cs.866

February 9, 2022

Deep convolutional neural networks for regular texture recognition

Ni Liu, Mitchell Rogers, Hua Cui, Weiyu Liu, Xizhi Li, Patrice Delmas

https://doi.org/10.7717/peerj-cs.869

November 16, 2021

Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM)

Ahmed Bahaa Farid, Enas Mohamed Fathy, Ahmed Sharaf Eldin, Laila A. Abd-Elmegid

https://doi.org/10.7717/peerj-cs.739

October 29, 2021

Inheritance metrics feats in unsupervised learning to classify unlabeled datasets and clusters in fault prediction

Syed Rashid Aziz, Tamim Ahmed Khan, Aamer Nadeem

https://doi.org/10.7717/peerj-cs.722

September 29, 2021

IoT-based intrusion detection system using convolution neural networks

Abdullah Aljumah

https://doi.org/10.7717/peerj-cs.721

September 20, 2021

Determining the number of hidden layer and hidden neuron of neural network for wind speed prediction

Muhammad Ibnu Choldun Rachmatullah, Judhi Santoso, Kridanto Surendro

https://doi.org/10.7717/peerj-cs.724