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Dr. Moparthi Nageswara Rao

Chairperson, School of Computing, Amaravati | Professor, School of Computing, Amaravati

Qualification: Ph. D.
m_nageswara@av.amrita.edu
ORCID ID
Google Scholar Profile
Scopus Author ID
Research Interest: Software Engineering, Machine Learning, Data Science, Deep Learning

Bio

Dr. M. Nageswara Rao is currently serving as a Professor and Chairperson in the Department of Computer Science and Engineering. He holds a Ph.D. in Computer Science and Technology from Sri Krishnadevaraya University, Andhra Pradesh, India. He is a Senior Member of IEEE reflecting his active engagement with the global research community. His research interests lie in Machine Learning, Data Science, and Sentiment Analysis,Software Engineering with a special focus on applications in agricultural and cultivation contexts, aimed at improving outcomes for farmers and rural communities.

With over 12 years of experience in the software industry and an additional 12 years in academia, He brings a balanced blend of practical and theoretical expertise. He has authored multiple peer-reviewed journal and conference papers, and is an active reviewer for several reputed journals and conferences. He also contributes to the professional community through mentoring, technical training, and editorial roles, including editing a book published by Wiley.

He is a 4-star CodeChef programmer, known for his strong programming skills. He holds global certifications from AWS (Associate Developer) and Google Cloud, and actively serves as an AWS Educator, delivering certified courses such as Cloud Practitioner and Associate Developer for the AWS. He holds another global certificate from Oracle as Oracle Certified Professional.

Publications

Journal Article

Year : 2025

A Consensus Blockchain-Based Credit Risk Evaluation and Credit Data Storage Using Novel Deep Learning Approach

Cite this Research Publication : Vadipina Amarnadh, Moparthi Nageswara Rao, A Consensus Blockchain-Based Credit Risk Evaluation and Credit Data Storage Using Novel Deep Learning Approach, Computational Economics, Springer Science and Business Media LLC, 2025, https://doi.org/10.1007/s10614-025-10905-4

Publisher : Springer Science and Business Media LLC

Year : 2025

A Smart Healthcare System Using Consumer Electronics and Federated Learning to Automatically Diagnose Diabetic Foot Ulcers

Cite this Research Publication : Sujit Kumar Das, Nageswara Rao Moparth, Suyel Namasudra, Rubén González-Crespo, David Taniar, A Smart Healthcare System Using Consumer Electronics and Federated Learning to Automatically Diagnose Diabetic Foot Ulcers, International Journal of Interactive Multimedia and Artificial Intelligence, Universidad Internacional de La Rioja, 2025, https://doi.org/10.9781/ijimai.2024.10.04

Publisher : Universidad Internacional de La Rioja

Year : 2024

Reliable Federated Learning With GAN Model for Robust and Resilient Future Healthcare System

Cite this Research Publication : Anita Murmu, Piyush Kumar, Nageswara Rao Moparthi, Suyel Namasudra, Pascal Lorenz, Reliable Federated Learning With GAN Model for Robust and Resilient Future Healthcare System, IEEE Transactions on Network and Service Management, Institute of Electrical and Electronics Engineers (IEEE), 2024, https://doi.org/10.1109/tnsm.2024.3422376

Publisher : Institute of Electrical and Electronics Engineers (IEEE)

Year : 2024

MALEXNET-EUNET: MULTI-CLASS LIVER CANCER CLASSIFICATION AND SEGMENTATION USING A HYBRID DEEP LEARNING SYSTEM

Cite this Research Publication : NAGESWARA RAO MOPARTHI, BHUVAN UNHELKAR, PRASUN CHAKRABARTI, MALEXNET-EUNET: MULTI-CLASS LIVER CANCER CLASSIFICATION AND SEGMENTATION USING A HYBRID DEEP LEARNING SYSTEM, Journal of Mechanics in Medicine and Biology, World Scientific Pub Co Pte Ltd, 2024, https://doi.org/10.1142/s0219519424500349

Publisher : World Scientific Pub Co Pte Ltd

Year : 2024

MPCSAR-AHH: A hybrid deep learning model for real-time detection of cassava leaf diseases and fertilizer recommendation

Cite this Research Publication : J. Siva Prashanth, Nageswara Rao Moparthi, G. Bala Krishna, A.V. Krishna Prasad, B. Sravankumar, P. Ravinder Rao, MPCSAR-AHH: A hybrid deep learning model for real-time detection of cassava leaf diseases and fertilizer recommendation, Computers and Electrical Engineering, Elsevier BV, 2024, https://doi.org/10.1016/j.compeleceng.2024.109628

Publisher : Elsevier BV

Year : 2024

DrugBlock: An Advanced System to Secure Drug Supply Chain Using Internet of Things and Blockchain-Enabled Consumer Electronics

Cite this Research Publication : Suyel Namasudra, Sangjukta Das, Ruben Gonzalez Crespo, David Taniar, Nageswara Rao Moparthi, DrugBlock: An Advanced System to Secure Drug Supply Chain Using Internet of Things and Blockchain-Enabled Consumer Electronics, IEEE Transactions on Consumer Electronics, Institute of Electrical and Electronics Engineers (IEEE), 2024, https://doi.org/10.1109/tce.2024.3473739

Publisher : Institute of Electrical and Electronics Engineers (IEEE)

Year : 2024

An efficient IoT based crop disease prediction and crop recommendation for precision agriculture

Cite this Research Publication : Gunaganti Sravanthi, Nageswara Rao Moparthi, An efficient IoT based crop disease prediction and crop recommendation for precision agriculture, Cluster Computing, Springer Science and Business Media LLC, 2024, https://doi.org/10.1007/s10586-023-04246-w

Publisher : Springer Science and Business Media LLC

Year : 2024

Enhanced Neural Network-Based Univariate Time-Series Forecasting Model for Big Data

Cite this Research Publication : Suyel Namasudra, S. Dhamodharavadhani, R. Rathipriya, Ruben Gonzalez Crespo, Nageswara Rao Moparthi, Enhanced Neural Network-Based Univariate Time-Series Forecasting Model for Big Data, Big Data, Volume 12, Issue 2, Pages 83 – 99, Mary Ann Liebert Inc, 2024, https://doi.org/10.1089/big.2022.0155

Publisher : Mary Ann Liebert Inc

Year : 2023

Dual Interactive Wasserstein Generative Adversarial Network optimized with arithmetic optimization algorithm-based job scheduling in cloud-based IoT

Cite this Research Publication : Gunaganti Sravanthi, Nageswara Rao Moparthi, Dual Interactive Wasserstein Generative Adversarial Network optimized with arithmetic optimization algorithm-based job scheduling in cloud-based IoT, Cluster Computing, Springer Science and Business Media LLC, 2023, https://doi.org/10.1007/s10586-023-03994-z

Publisher : Springer Science and Business Media LLC

Year : 2023

Prediction and assessment of credit risk using an adaptive Binarized spiking marine predators’ neural network in financial sector

Cite this Research Publication : Vadipina Amarnadh, Nageswara Rao Moparthi, Prediction and assessment of credit risk using an adaptive Binarized spiking marine predators’ neural network in financial sector, Multimedia Tools and Applications, Springer Science and Business Media LLC, 2023, https://doi.org/10.1007/s11042-023-17467-3

Publisher : Springer Science and Business Media LLC

Year : 2023

AESPNet: Attention Enhanced Stacked Parallel Network to improve automatic Diabetic Foot Ulcer identification

Cite this Research Publication : Sujit Kumar Das, Suyel Namasudra, Awnish Kumar, Nageswara Rao Moparthi, AESPNet: Attention Enhanced Stacked Parallel Network to improve automatic Diabetic Foot Ulcer identification, Image and Vision Computing, Volume 138, Elsevier BV, 2023, https://doi.org/10.1016/j.imavis.2023.104809

Publisher : Elsevier BV

Global Certifications
  1. AWS Academy Educator
  2. AWS Certified Developer – Associate
  3. AWS Certified Cloud Practitioner
  4. Associate Cloud Engineer Certification (Google)
  5. Introduction to Programming Using Python (Microsoft TA)
FDP / Workshops
  • Attended: 10
Invited Talks
  • The 2nd International Conference on Big Data Computing and Modelling- Machine Learning Models
Membership
  • IEEE
  • IAENG
  • IACSIT
Awards
  1. One Team One Dream Award from IBM
  2. Spot Award from Mphasis an HP company
  3. Best Performer of the month from Sony India(P) ltd
  4. Award of Excellence in Research-2020 by Novel Research Academy
  5. Bentham Ambassador from Bentham family
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