M.SHUNMUGASUNDARAM

@srmvalliammai.ac.in

ASSOCIATE PROFESSOR AND DEPARTMENT OF MANAGEMENT STUDIES
SRM Valliammai Engineering College

M.SHUNMUGASUNDARAM


                     Download Compact PDF  
https://researchid.co/shunmugasundaram

RESEARCH, TEACHING, or OTHER INTERESTS

Organizational Behavior and Human Resource Management, Marketing, Strategy and Management, Business and International Management
18

Scopus Publications

401

Scholar Citations

10

Scholar h-index

10

Scholar i10-index

Scopus Publications

  • Sustainable waste-to-energy technologies: blending waste plastics as co-pyrolysis feed for fishery and agricultural wastes towards biofuel production and their characterization
    P. Madhu, Sujit Kumar, R. E. Ugandar, P. Harichandra Prasad, R. Vijayakumar, M. Shunmugasundaram, T. Vijay Muni, V. Porkodi
    Biomass Conversion and Biorefinery, 2026
  • Resilience and Adaptive Learning in Hybrid Education for Students with Disabilities: A Quantitative Analysis
    International Journal of Special Education, 2026
  • Sustainable Development in Education Using Quantum-Classical Synergistic Fibroblast Dense Nested Convolutional Attention Network
    K. Sankar Ganesh, M. Shunmugasundaram, V. Mohana Sundari, S. Gangadharan, G. Kannan
    International Journal of Computational Intelligence and Applications, 2025
    Sustainable development in education is crucial for advancing global educational standards and addressing disparities. Existing methods for predicting sustainable development in education often struggle with data quality and complexity, which can limit their accuracy and applicability. This study aims to overcome these limitations. This study presents a novel approach to predicting Sustainable Development in Education using the quantum-classical synergistic fibroblast dense nested convolutional attention network (Qua-CSFib-DNCANet). In this, input educational data is sourced from the Europe and Central Asia dataset. Then, these educational data are pre-processed using the preprocessing methods within new adjusted min–max with decimal scaling and statistical column normalization (NAMDSSCN) include normalization of statistical column, normalization of decimal scaling, normalization of adjusted decimal scaling, min–max normalization, normalization of adjusted 1-min–max, normalization of adjusted 2-min–max, normalization of adjusted 3-min–max, and normalization of adjusted 4-Min–Max. Multiple discrete orthonormal S-transforms extract features by providing an efficient method to represent complex educational metrics. The Qua-CSFib-DNCANet mechanism is applied to accurately predict indicators of sustainable development in education. The performance of the suggested system is assessed using academic information from the Europe and Central Asia databases, and it runs on a Python platform. With an astounding 99.9% correctness and 99.8% recall, the Qua-CSFib-DNCANet model outperforms current techniques in terms of efficiency and shows promise for future development in the sector. This approach aims to provide deeper insights and improved predictions, addressing the challenges associated with educational data analysis and supporting strategic initiatives for educational sustainability.
  • Fraud detection in the banking sector using Gated Green Anaconda Progressive Generative Axial Adversarial Attention Network
    K Prakash, M Franklin, M Shunmugasundaram, K Sankar Ganesh, S Gangadharan
    Intelligent Decision Technologies, 2025
    In the realm of digital banking, financial fraud has become an escalating concern due to the rapid adoption of online transaction systems. In the banking sector, fraud detection is critical, when deceptive practices outcome in large financial losses and can undermine trust in banking institutions. Traditional detection methods often struggle with false positives, high computational costs, and adaptability to evolving fraud patterns. This work is recommended to solve this problem. This work deals with effective identification of the various types of fraud that exist in the banking industry using a complex network known as the Gated Green Anaconda Progressive Generative Axial Adversarial Attention Network (2GAP-G3A-Net). The datasets used in this work include Financial-Fraud-Detection, and synthetic data that are derived from the financial payment system dataset that needs to be preprocessed for cleansing and normalization uses NLP based methods. Feature selection is carried out using the sea horse optimization algorithm to reduce model complexity and improve effectiveness of the model in predicting fraud cases while selecting the most important variables. The 2GAP-G3A-Net is then used to develop another state of the art and highly accurate fraud detection framework that integrates the PgAN and GAO with an additional GAAN to identify intricate transactional patterns. These techniques for using the 2GAP-G3A-Net model demonstrate a nearly perfect mean per-voxel Dice coefficient of 0.999 and show the efficiency of the model and higher potentiality compared with the current techniques. The approach enhances the accuracy of fraud prediction and minimizes false positives, can operate in a constantly changing environment and work with large data sets, which make it an effective tool in the banking industry.
  • Optimal Energy Management for Hybrid PV-Wind-Battery Microgrids through Markov Decision Processes Technique
    Nitin Chakole, Krishna Priya Remamany, G Mohan, P Sasirekha, NMG Kumar, et al.
    International Journal of Smart Grid, 2025
    Hybrid PV-Wind-Battery microgrids have emerged as sustainable solutions to meet growing energy demands while reducing reliance on fossil fuels. However, managing energy flow efficiently among multiple renewable sources and storage systems poses significant challenges due to the inherent variability of solar and wind power. This paper presents an advanced energy management framework for hybrid microgrids using Markov Decision Processes (MDP). The proposed approach optimizes energy distribution through stochastic decision-making based on real-time system states, such as power generation, load demand, and battery state of charge (SOC). The MDP-based model aims to minimize operational costs, enhance energy reliability, and maintain system stability by determining optimal actions for battery charging/discharging and energy source prioritization. A comparative analysis with conventional methods demonstrates the MDP framework’s superiority in adapting to dynamic conditions, reducing energy wastage, and maximizing renewable utilization. The proposed control strategy introduces a Markov Decision Process (MDP)-based energy management framework that dynamically adapts to the stochastic nature of renewable generation and load demand a distinct departure from traditional rule-based or deterministic approaches. Unlike previous methods that rely on fixed thresholds or predefined heuristics, our MDP model leverages real-time system states to make probabilistically optimal decisions regarding battery usage and source prioritization. This integration of stochastic optimization with hardware validation establishes a novel, scalable, and practical control solution for hybrid PV-Wind-Battery microgrids, marking a significant advancement in intelligent energy management systems.
  • Business Applications and Practical Implications of Cloud Computing
    Silas Sargunam, M. Shunmuga Sundaram, K. Sankar Ganesh
    Aip Conference Proceedings, 2025
  • A Federated Learning and Blockchain Framework for IoMT-Driven Healthcare 5.0
    Denis R, N. Venkateswaran, S. Gangadharan, M. Shunmugasundaram, Guduri Chitanya, Girija M. S, V. V. Satyanarayana Tallapragada, R. G. Vidhya
    International Journal of Basic and Applied Sciences, 2025
    This paper presents an innovative framework integrating federated learning, blockchain, and the Internet of Medical Things ‎‎(IoMT) to revolutionize healthcare systems in the context of Healthcare 5.0. By harnessing advanced sensors and leveraging ‎‎5G technology, the framework enables continuous, real-time data collection and intelligent analysis, facilitating highly ‎personalized and timely medical interventions. Federated learning enables decentralized model training across edge devices, ‎preserving data privacy and enhancing security. Simultaneously, blockchain ensures the integrity and transparency of healthcare ‎records through a decentralized and tamper-proof ledger. The synergy of these technologies fosters secure and efficient ‎communication across a network of interconnected medical devices. This framework significantly enhances healthcare delivery ‎by promoting proactive, patient-focused, and adaptive care models. Additionally, IoMT expands the capabilities of medical ‎equipment by enabling remote monitoring, automated data transmission, and comprehensive patient oversight. As the vision of ‎Healthcare 5.0 progresses, embracing such cutting-edge technological solutions is vital for improving patient outcomes, ‎streamlining operations, and accelerating medical innovation. Through the combined power of federated learning, blockchain, ‎and IoMT, the healthcare sector stands on the brink of a transformative shift toward secure, intelligent, and personalized care‎.
  • RELATION BETWEEN JOB PROFILE AND POLICE PERSONNEL'S PERCEPTION ABOUT CAUSES FOR STRESS
    Social Science Forum, 2025
  • Customer Experience Management in age of AI: Strategies for Personalization and Loyalty
    G. Saravana Kumar, Samminga Ashok Kumar, Suman Chintala, Noor Firdoos Jahan, M. Shunmugasundaram, Nikhil Polke
    2025 International Conference on Pervasive Computational Technologies Icpct 2025, 2025
    Since its birth, a great deal of study has focused on understanding the importance of AI in the business context. Given this, the goal of this study is to assess the effects of AI on client devotion and experiences and how personalisation mediates this relationship. This study had two goals in mind. After examining the various uses of AI in business, we use data from 900 companies worldwide to assess experimentally if these uses boost customer loyalty. The combined scores of four different AI traits make up the datasets: natural language processing integration, AI-powered customer service, predictive modelling, and ML-powered personalisation. The binary customer loyalty measure is the goal. Each component is measured using a 5-point Likert scale. Three different supervised machine learning (ML) techniques were employed: logistic regression, SVM, and decision trees. Confusion matrices were used to assess each algorithm's performance. With a test accuracy of 69.04%, the logistic classifiers outperformed the others. The accuracies of the decision tree and SVC were 64.39 and 58.96, respectively. The results of this study demonstrate how companies can utilise AI, ML, and NLP to analyse data and determine what's valuable. These insights can then be used to automate operations and inform company plans. Therefore, businesses should implement them if they want to stay competitive and boost client loyalty.
  • Hybrid Deep CNN-ELM Based Auto-Grading System for Reducing Educator Workload and Enhancing Student Performance in Higher Education
    Palak Keshwani, Venkata Kiran Kumar Ravi, M. Kanmani, Vusal Karimli Maharram, Sneha Kumari, M. Shunmugasundaram
    2025 3rd World Conference on Communication and Computing Wconf 2025, 2025
    The use of auto-grading systems has become commonplace in higher education, particularly in computer science degrees, due to the rising demands of managing larger class sizes and providing students with quick and efficient feedback. By delivering scalable, consistent assessments, these technologies are vital in improving student performance evaluation. To gain a better understanding of how people are currently using it, they polled teachers from different schools to find out what they like, what they find difficult, and how they grade. According to the findings, the most popular systems provide significant levels of customization and integration, and output-based grading is also quite popular. By utilising advanced text preparation techniques as stemming, information extraction, tokenisation, and CNN, this study also suggests a hybrid auto-grading method that mixes ELM with CNN. In order to find trends and increase grading precision, information extraction compares student replies to instructor-provided answers, which is a data mining process. Outperforming current state-of-the-art approaches, the suggested DCNN-ELM model attained a precision level of 95.73%. These results show how intelligent auto-grading systems can help make assessments more reliable and efficient, which in turn can lead to better results for students and teachers in higher education.
  • BiRNN and Dilated CNN-Driven Strategies for Vocabulary Development Among ESL/EFL Learners in Higher Education
    Ipsita Nayak, Khandavalli Ashok, B. Sridevi, G. Immanuel, Nigar Aliyarova Namig, M. Shunmugasundaram
    2025 3rd World Conference on Communication and Computing Wconf 2025, 2025
  • A study on impact of Green human resource management practice on its sector - Chennai
    M. Shunmuga Sundaram, R. V. Palanivel, K. Sankar Ganesh, V. John Paul Raj, K. P. Vidhya
    Aip Conference Proceedings, 2024
  • Advancing Women's Empowerment in the Technology Sector with a Concentration on the Internet of Things (IoT) and Artificial Intelligence (AI)
    B. T. Geetha, M. K. Sharma, M Shunmugasundaram, Jaksan D Patel, Melanie Lourens, Dr. Melanie Lourens
    Tqcebt 2024 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024, 2024
  • AN EFFECTIVE METHOD FOR MANAGING WASTE IN SMART CITIES BASED ON DEEP RESIDUAL NEURAL NETWORK APPROACH
    Journal of Environmental Protection and Ecology, 2024
  • An Improved Artificial Intelligence based Service Quality to Increase Customer Satisfaction and Customer Loyalty in Banking Sector
    M Shunmugasundaram, K.Sankar Ganesh, T. Joel Gnanapragash, John E P, John Paul Raj, V. Smitha
    2nd International Conference on Sustainable Computing and Data Communication Systems Icscds 2023 Proceedings, 2023
  • Application of BiLSTM-CRF Approach and its Application for Better Decisions in Human Resource Management Processes
    Umanesan R, M Shunmugasundaram, Pushpa Rani, K. Balasubramanian, K. Rakesh, Pankaj Singh Chandel
    International Conference on Sustainable Communication Networks and Application Icscna 2023 Proceedings, 2023
  • A study on police personnel’s perception about causes for stress and frequency of stress occurrence
    International Journal of Advanced Science and Technology, 2020
  • A study on sources of occupational stress among police constables
    International Journal of Applied Engineering Research, 2015

RECENT SCHOLAR PUBLICATIONS

  • Sustainable waste-to-energy technologies: blending waste plastics as co-pyrolysis feed for fishery and agricultural wastes towards biofuel production and their characterization
    PMSKREUPHPRVMSTVMV Porkodi8
    Biomass Conversion and Biorefinery 16 (235), 4-18 , 2026
    2026
  • Resilience and Adaptive Learning in Hybrid Education for Students with Disabilities: A Quantitative Analysis
    PV Shalini S, M. Shunmugasundaram, S. Gangadharan, Kaushik Samanta, Jaya ...
    International Journal of Special Education 41 (1), 611-625 , 2026
    2026
  • DIGITAL MARKETING MANAGEMENT PRACTICES INFLUENCING BRAND PERFORMANCE AND CONSUMER ENGAGEMENT IN TECHNOLOGY-DRIVEN MARKETS
    SG Darshana Bhagowati¹, K. Sathiyamurthi², M. Shunmugasundaram³, Karthick K ...
    SCIENTIFIC CULTURE 12 (2.1), 4689-4698 , 2026
    2026
  • Deep Learning-Based Time Series Analysis for Early Sepsis Prediction in Intensive Care Units
    SVK Anita Venugopal1*, M Shunmugasundaram2, S. Gangadharan3, Veena Janardhan ...
    National Journal of Antennas and Propagation 8 (2), 236-245 , 2026
    2026
  • Artificial Intelligence–Driven Design Thinking for User-Centric Product Development
    AD M Shunmugasundaram1*, S. Gangadharan2, Arul Selvan M3, J.Raja4, R ...
    National Journal of Antennas and Propagation 8 (2), 120-130 , 2026
    2026
  • Sustainable Development in Education Using Quantum-Classical Synergistic Fibroblast Dense Nested Convolutional Attention Network
    K Sankar Ganesh, M Shunmugasundaram, V Mohana Sundari, ...
    International Journal of Computational Intelligence and Applications 24 (04 … , 2025
    2025
  • BiRNN and Dilated CNN-Driven Strategies for Vocabulary Development Among ESL/EFL Learners in Higher Education
    Dr. Ipsita Nayak, Dr. G. Immanuel, Khandavalli Ashok, Nigar Aliyarova Namig ...
    2025 3rd World Conference on Communication & Computing (WCONF) 1 (1), 1-6 , 2025
    2025
  • Hybrid Deep CNN-ELM Based Auto-Grading System for Reducing Educator Workload and Enhancing Student Performance in Higher Education
    Palak Keshwani, Dr. Vusal Karimli Maharram, Vusal.karimli@unec.edu.az Dr ...
    IEEE XPLORE 1 (1), 1-6 , 2025
    2025
    Citations: 1
  • Optimal Energy Management for Hybrid PV-Wind-Battery Microgrids through Markov Decision Processes Technique
    BPG Nitin Chakole, Krishna Priya Remamany, G Mohan, P Sasirekha, NMG Kumar ...
    INTERNATIONAL JOURNAL of SMART GRID 9 (5), 127-145 , 2025
    2025
    Citations: 6
  • Fraud detection in the banking sector using Gated Green Anaconda Progressive Generative Axial Adversarial Attention Network
    K Prakash, M Franklin, M Shunmugasundaram, K Sankar Ganesh, ...
    Intelligent Decision Technologies 19 (5), 3281-3303 , 2025
    2025
    Citations: 1
  • Business applications and practical implications of cloud computing
    S Sargunam, MS Sundaram, KS Ganesh
    AIP Conference Proceedings 3137 (1), 020028 , 2025
    2025
  • Impact of Forecast Time-Step on PV Production Accuracy Using Machine Learning for Micro-Grid Efficiency
    MP P.R. Sudha Rani,S. Ajit,M. Shunmugasundaram,S. Gangadharan,Swetha Mareddy ...
    Metallurgical and Materials Engineering 31 (No. 1), 511-520 , 2025
    2025
  • Customer Experience Management in age of AI: Strategies for Personalization and Loyalty
    GS Kumar, SA Kumar, S Chintala, NF Jahan, M Shunmugasundaram, ...
    2025 International Conference on Pervasive Computational Technologies (ICPCT … , 2025
    2025
  • AI-Driven Sustainable Infrastructure: Smart Campus Automation, Energy Optimization, Security, and Intelligent Material Systems
    DJNRDMSDS KHARE
    BOOK 1, 457 , 2025
    2025
  • A Federated Learning and Blockchain Framework for ‎IoMT-Driven Healthcare 5.0
    DRNVSGMSGCGMSVVSTRG Vidhya
    International Journal of Basic and Applied Sciences 14 (1), 246-250 , 2025
    2025
    Citations: 10
  • Artificial Intelligence and its Influence on Call Center Performance Management
    A Singh, KS Ganesh, M Joshi, R Boorla, MS Sundaram
    Recent Technological Advances in Engineering and Management, 184-188 , 2024
    2024
  • Advancing Women’s Empowerment in the Technology Sector with a Concentration on the Internet of Things (IoT) and Artificial Intelligence (AI)
    DBTGMKSDMSJDPDMLDM Lourens
    IEEE Conference Proceedings, 17 , 2024
    2024
  • Enhancing Paper Cup Manufacturing Quality Using Six Sigma's DMAIC Methodology
    GN Harikrishna Bommala , Abullais Nehal Ahmed , M Shunmugasundaram , S. Ajit ...
    Nanotechnology Perceptions ISSN 1660-6795 20 (9), 710-725 , 2024
    2024
  • A study on impact of Green human resource management practice on its sector – Chennai
    MS Sundaram, RV Palanivel, KS Ganesh, VJP Raj, KP Vidhya
    INTERNATIONAL CONFERENCE ICMCCT2022: The Third International Conference on … , 2024
    2024
  • A study on impact of Green human resource management practice on its sector – Chennai
    KPV M. ShunmugaSundaram,R.V. Palanivel , K. Sankar Ganesh , V. John Paul Raj
    International Conference ICMCCT2022 100 (https://doi.org/10.1063/5.0212056), 1-7 , 2024
    2024

MOST CITED SCHOLAR PUBLICATIONS

  • Women empowerment: role of education
    A Subburaj
    International Journal in Management and Social Science 2 (12), 76-85 , 2014
    2014
    Citations: 179
  • AN EFFECTIVE METHOD FOR MANAGING WASTE IN SMART CITIES BASED ON DEEP RESIDUAL NEURAL NETWORK APPROACH
    AR M. SHUNMUGASUNDARAMa*, M. D. OQAIL AHMAD, T. SUBHA, S. SARUMATHI, SUJATHA ...
    Journal of Environmental Protection and Ecology 25 (2), 420-429 , 2024
    2024
    Citations: 31
  • A study on frequency of occupational stress among Grade 1 police constables
    MJ Kumaran, S Sanderam
    International Journal of Business Management and Economic Research 3 (4 … , 2012
    2012
    Citations: 24
  • Occupational stress and coping strategies among grade II police constables
    M Sundaram, M Kumaran
    International Journal of Business Management and Economic Research 3 (4 … , 2012
    2012
    Citations: 18
  • Application of BiLSTM-CRF Approach and its Application for Better Decisions in Human Resource Management Processes
    R Umanesan, M Shunmugasundaram, P Rani, K Balasubramanian, ...
    2023 International Conference on Sustainable Communication Networks and … , 2023
    2023
    Citations: 17
  • Policing the Most Stressful Occupation: A Study on Tamilnadu Head Constables.
    M Sekar, A Subburaj, MS Sundaram
    International Journal of Business Management & Economic Research 4 (5) , 2013
    2013
    Citations: 16
  • A study on Frequency of Stress among Female Police Constables Reference to Tamilnadu Police Department, India
    MSSMJ Kumaran
    International Research Journal of Social Sciences 1 (3), 15-20 , 2012
    2012
    Citations: 16
  • Occupational stress coping on policing reference to grade III police constables
    MS Sundaram, M Sekar, A Subburaj
    International Journal of Business Management & Research 4 (3), 9-50 , 2014
    2014
    Citations: 14
  • A Federated Learning and Blockchain Framework for ‎IoMT-Driven Healthcare 5.0
    DRNVSGMSGCGMSVVSTRG Vidhya
    International Journal of Basic and Applied Sciences 14 (1), 246-250 , 2025
    2025
    Citations: 10
  • Advancing women’s empowerment in the technology sector with a concentration on the internet of things (iot) and artificial intelligence (ai)
    BT Geetha, MK Sharma, M Shunmugasundaram, JD Patel, M Lourens
    2024 International Conference on Trends in Quantum Computing and Emerging … , 2024
    2024
    Citations: 10
  • Big five personality traits-a tool for managing stress
    A Subburaj, MS Sundaram, M Sekar, P Sumathi
    Ashok Yakkaldevi , 2012
    2012
    Citations: 8
  • A study on job satisfaction among the employees of state bank of India in Coimbatore city
    M Sekar, MS Sundaram, KS Ganesh, A Subburaj, NM Kumar
    International Journal of Business Economics and Management Research 2 (6to8 … , 2012
    2012
    Citations: 7
  • Optimal Energy Management for Hybrid PV-Wind-Battery Microgrids through Markov Decision Processes Technique
    BPG Nitin Chakole, Krishna Priya Remamany, G Mohan, P Sasirekha, NMG Kumar ...
    INTERNATIONAL JOURNAL of SMART GRID 9 (5), 127-145 , 2025
    2025
    Citations: 6
  • Application of BiLSTM-CRF Approach and its Application for Better Decisions in Human Resource Management Processes
    U Ramakrishnan, M Shunmugasundaram, P Rani, K Balasubramanian, ...
    2023
    Citations: 6
  • Innovations in Human Resource Management: Adapting to the Future of Work
    DSRB Priyanka Sharma1 , Dr. Bhaskara srinivas , Dr. M Shunmugasundaram ...
    Journal of Informatics Education and Research 3 (2 (2023)), 1698-1708 , 2023
    2023
    Citations: 6
  • Impact of job satisfaction and personal characteristics on employee absenteeism
    M Shunmuga, AA Sundram
    Indian Streams Research Journal 2 (10), 10 , 2012
    2012
    Citations: 6
  • A study on job demand stressors and coping strategies among police constables
    MS Sundaram, MJ Kumaran
    International Journal of Marketing and Management Research 3 (10), 30-46 , 2012
    2012
    Citations: 5
  • An Improved Artificial Intelligence based Service Quality to Increase Customer Satisfaction and Customer Loyalty in Banking Sector
    Dr M Shunmugasundaram
    Proceedings of the International Conference on Sustainable Computing and … , 2023
    2023
    Citations: 4
  • Sugar Quality: Process Options to Address Sustainability of Sugar Industry
    MS Sundaram, K Jagadeesh
    Sugar and Sugar Derivatives: Changing Consumer Preferences, 77-91 , 2020
    2020
    Citations: 4
  • A Study on Sources of Occupational Stress Among Police Constables
    MSM Sekar
    International Journal of Applied Engineering Research 10 (6), 14255-14266 … , 2015
    2015
    Citations: 4

Publications

57215826758