Dr. Sanjay Kumar Sinha

@piet.poornima.org

Professor, Computer Engineering
Poornima Institute of Engineering & Technology

Dr. Sanjay Kumar Sinha


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https://researchid.co/sanjay.sinha

EDUCATION

PhD. in Computer Science

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Science Applications, Information Systems, Computer Networks and Communications
18

Scopus Publications

40

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Empowering Elderly Care Through Artificial Intelligence
    Nikhil Kumar Goyal, Navin Kumar Goyal, Suneel Kumar, Ritam Dutta, Vishal Kothari, Sanjay Kumar Sinha
    AI for Geriatric Care in an Aging Society Ethical Clinical and Policy Challenges, 2025
    This section discusses how artificial intelligence (AI) can transform the elderly care sector and positively impact how aging populations live. As the world is becoming an aging society increased pressure to ensure patients receive personalised, effective and sustainable healthcare is being placed on traditional healthcare systems. These technologies (AI technologies) are finding innovative solutions to needs in remote health monitoring and wellness, disease prediction, companionship, and rehabilitation, as well as, fall detection. Other ways that AI helps in emotional well-being are besides clinical support by eliminating the feeling of social isolation with the help of virtual assistants and socially interactive robots. The chapter presents a technological overview of AI in elderly care application and indicates its potential advantages, but critically analyzes its ethical consequences, as well as psychological and societal effects.
  • Comparing Smote and Adasyn for Detection of Credit Card Fraud
    Mamta Sakpal, Sanjay Kumar Sinha
    Springer Proceedings in Earth and Environmental Sciences, 2025
  • A Model for Predicting Crime in Digital Forensics Using CNN
    Mamta Sakpal, Sanjay Kumar Sinha
    Springer Proceedings in Earth and Environmental Sciences, 2025
  • An Innovative Framework on Predicting House Price Using Machine Learning Approaches
    Debmitra Das, Ritam Dutta, Shilpa Singh, Shipra Sharma, Navin Kumar Goyal, Sanjay Kumar Sinha
    2025 IEEE 4th International Conference for Advancement in Technology Iconat 2025, 2025
    As house prices are increasing day by day therefore, it becomes a real necessity to create a smart mechanism to predict house prices around your area of choice. House Price Index (HPI) is mainly used to detect variations in house prices. House price is connected with some factors viz. the geographical location of the house, the population density around that area etc. Based on the specific location and population density, HPI detects the accurate price of the selected house. This technique can assist the buyer or seller in determining the accurate price of a house according to geographical location, and number of rooms availability. Our proposed machine learning (ML) approach i.e. Multiple Logistic Regression (LR) is applied to diagnose market trends and give more accurate result. In our proposed framework, we have collected two data sets from Kaggle. One is individual state dataset named “Bangalore house price dataset” and another one is “Dataset of India”. After an extensive literature survey on developing smart house price prediction framework, we have trained the existing model with Multiple LR, Decision Tree (DT) and Lasso Regression. Our simulator recorded the accuracy of 90.35 % for “Bangalore House Price Dataset” and whereas “Dataset of India” resulted the accuracy of 95.14% with Multiple LR model.
  • ML-enabled fault control and efficiency improvement in multi-cloud NFV
    K. Gopala Krishna, Kajal Chheda, Sahil Khurana, Prateek Aggarwal, Anamika Tiwari, Sanjay Kumar Sinha
    International Journal of System Assurance Engineering and Management, 2025
  • Multi-cloud storage augmentation: a novel secured framework for information sharing
    Jaimine Vaishnav, Damanjeet Aulakh, Bhawna Wadhwa, D. Ganesh, Jagtej Singh, Sanjay Kumar Sinha
    International Journal of System Assurance Engineering and Management, 2025
  • Elevating optical networks: Machine learning approach for optimal resource scheduling and performance boost
    Neetha Kala S.S., Aaditya Jain, Rahul Bhatt, Sanjay Kumar Sinha, Pankaj Saraswat, Prabhakaran
    International Journal of Communication Systems, 2024
    SummaryThe increasing demand for massaging networks that are stable and quick needs reevaluations of standard optical networking administration strategies. To improve the efficacy of optical networks by integrating machine learning (ML) approach for the best resource scheduling, this research presents an innovative dynamic block widow optimized random forest (DBWO‐RF) strategy. To implement the DBWO‐driven resource allocation method in accordance with the categorization and clustering findings, the RF method is incorporated with the software defined optical to achieve channel quality assessment after successfully clustering employs the RF approach to achieve channel quality assessment after successfully clustering traffic patterns using the fuzzy C‐means (FCM) algorithm. To lessen the likelihood of blocking, the fragmentation‐function‐fit (FFF) algorithm was provided and the findings indicate that this approach possesses a reduced blocking risk. Using multiple approaches to modulation for various channel quality, the suggested resource allocation system leverages the DBWO approach to distribute the necessary resources based on various “traffic flow (TF)” clustering findings. The examination's outcomes demonstrate that, compared to other techniques under various given load levels, the present study has a reduced blocking risk, a sufficient complexity degree and greater effectiveness in the utilization of spectrum resources.
  • Deep learning-based methodology for tracking cybersecurity in networked computers
    Dharmesh Dhabliya, N. R. Solomon Jebaraj, Sanjay Kumar Sinha, Asha Uchil, Anishkumar Dhablia, Jambi Ratna Raja Kumar, Sabyasachi Pramanik, Ankur Gupta
    Risk Assessment and Countermeasures for Cybersecurity, 2024
    Effective surveillance of cybersecurity is essential for safeguarding the security of computer networks. Nevertheless, due to the increasing scope, complexity, and amount of data created by computer networks, cybersecurity monitoring has become a more intricate issue. The difficulty of correctly and effectively monitoring computer network cybersecurity is a challenge faced by traditional approaches examining a greater quantity of data. Hence, using deep learning models to oversee computer network cybersecurity becomes necessary. This chapter introduces a technique for overseeing the cybersecurity of computer networks by using deep learning knowledge about models. The combination of CNN (convolutional neural networks) and LSTM (long short-term memory) models is used for monitoring the cybersecurity of computer networks. This combination enhances the accuracy of classifying network cybersecurity problems. The CICIDS2017 dataset is used for training and evaluating the suggested model.
  • Boundary stress distribution and elastic viscous of emerging pavement predicted using an innovative hybrid machine learning technique
    Intekab Alam, Sanjay Kumar Sinha, Karishma Desai, Honganur Raju Manjunath
    Multidisciplinary Science Journal, 2024
    Concrete's pumpability is significantly affected by the plastic viscosity of the mix and its surface yield stress. The long-term performance and durability of road infrastructure depend heavily on the capacity to predict the boundary stress distribution and elastic-viscous behavior of developing pavements. This study is concerned with predicting the elastic and viscous behavior of changing pavements using sophisticated predictive modeling approaches. Several techniques frequently need to capture the intricate interdependencies that are a feature of pavement behavior. To overcome this issue, we proposed the hybridization method of dynamic random forest combined with bilateral long short-term memory (DRF-BiLSTM). The purpose of DRF-BiLSTM is to predict the boundary stress distribution and elastic viscous of emerging pavement. Initially, asphalt binder (AB) datasets were collected. The collected dataset is preprocessed using the z-score normalization technique to reduce the effects of size discrepancies by standardizing the data. After preprocessing the data, the short-time fourier transform (STFT) method is used for feature extraction. Predictive results that are superior to those of benchmark models should obtained using experimental data supporting a hybridization of DRF-BLSTM in terms of.
  • Modernizations in wear-resistant materials: Development of aluminum and polyamide feedstock filaments for fused deposition modelling
    Naresh Kaushik, B. P. Singh, Sanjay Kumar Sinha, Naveen Kumar Rajendran
    Multidisciplinary Science Journal, 2024
    In the area of additive manufacturing (AM), the development of inside filaments has become an innovation in technological advancement as it pertains to fused deposition modelling (FDM). Without the use of traditional tools, this approach enables the creation of sophisticated 3D structures quickly. Although several uses have been investigated, there is a considerable research gap in the field of hybrid feedstock filament-based wear-resistant substances and frameworks development. In particular, this study explores the previously unexplored field of using a hybrid filament made of aluminum (Al2O3) powder and polyamide (Nylon 6) matrix. This study aims to explore the production capability of wear-resistant structures and materials by utilizing a hybrid feedstock filament in an innovative manner. The filament is made for FDM and consists of an aluminum powder and polyamide matrix. According to ASTM-D1238-73, the study is to ascertain the ideal ratios of filler, matrix. Through a detailed statistical study of wear findings, the procedure was established as an industry standard. To assess uniformity and monitor process parameters, modern statistical process control and quality improvement methodologies are employed. As critical indications in evaluating the feasibility and dependability of the created wear-resistant materials and FDM method, the findings comprise a histogram showing wear outcomes, an R-chart, and an X-chart for the achieved wear values. By leveraging FDM technology to produce wear-resistant materials that are both accessible and resilient, the complete approach seeks to set an industry standard.
  • Heat Stress in Dairy Cows: A Comprehensive Examination of Wellbeing, Milk Yield, Sexual Health
    Revista Electronica De Veterinaria, 2023
  • Wideband Technology Design with the Novel Based Technogy : An Antenna Systems
    Murugan R, Sanjay Kumar Sinha, Savita
    2023 International Conference on Power Energy Environment and Intelligent Control Peeic 2023, 2023
  • Blockchain empowerment: Investigating integration with software-defined networks and its impact on IoT privacy
    Sanjay Kumar Sinha, Sweta Kumari, Ansh Kataria, Narmadha Thangarasu, Girija Shankar Sahoo
    Multidisciplinary Reviews, 2023
  • Analyzing the Use of Machine Learning Models for Enhancing Big Data Retrieval Performance
    Saniya Khurana, P Balakumar, Nilesh P. Sable, Sanjay Kumar Sinha, Megha Pandey, V M Saravanan
    Proceedings 2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario Icpsitiags 2023, 2023
  • Implementing Machine Learning Techniques to Enhance Real-Time Data Analysis Services
    Jaisudha J, Dharmesh Dhabliya, Narasimhayya B E, Akhilendra Pratap Singh, Sanjay Kumar Sinha, Nitish Vashisht
    2023 3rd International Conference on Smart Generation Computing Communication and Networking Smart Gencon 2023, 2023
  • Retracted: Developing a Framework for Utilizing AI for Data Access Optimization (2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON) DOI: 10.1109/SMARTGENCON60755.2023.10441895)
    Nagaraju Bogiri, Sanjay Kumar Sinha, Ashmeet Kaur, Vaishali Singh, Dimple Bahri, X.Mercilin Raajini
    2023 3rd International Conference on Smart Generation Computing Communication and Networking Smart Gencon 2023, 2023
  • Retracted: Implementing Machine Learning Techniques to Enhance Real-Time Data Analysis Services (2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON) DOI: 10.1109/SMARTGENCON60755.2023.10442318)
    Jaisudha J, Dharmesh Dhabliya, Narasimhayya B E, Akhilendra Pratap Singh, Sanjay Kumar Sinha, Nitish Vashisht
    2023 3rd International Conference on Smart Generation Computing Communication and Networking Smart Gencon 2023, 2023
  • Developing a Framework for Utilizing AI for Data Access Optimization
    Nagaraju Bogiri, Sanjay Kumar Sinha, Ashmeet Kaur, Vaishali Singh, Dimple Bahri, X.Mercilin Raajini
    2023 3rd International Conference on Smart Generation Computing Communication and Networking Smart Gencon 2023, 2023

RECENT SCHOLAR PUBLICATIONS

  • DATA MINING AND KNOWLEDGE DISCOVERY IN LARGE-SCALE SYSTEMS
    DNKGPDSKSDPMADSBEDUD PRASAN
    ISBN: 978-81-685858-3-6 , 2026
    2026
  • AI-Driven Bharatiya Vanshavali and Heritage Analytics: Lev eraging Cloud Computing for Genealogical Research
    DSK Sinha
    Integrating Modern Technology with Ancient Knowledge for Developing a … , 2026
    2026
  • Fusion Technologies in Governance: From Algorithmic Intelligence to Augmented Reality
    NKG Kamini Pareek , Navin Kumar Goyal , Neetu Sharma, Sanjay Kumar Sinha
    AI-Powered Augmented Reality for Public Administration, 22 , 2026
    2026
  • An Innovative Framework on Predicting House Price Using Machine Learning Approaches
    D Das, R Dutta, S Singh, S Sharma, NK Goyal, SK Sinha
    2025 IEEE 4th International Conference for Advancement in Technology (ICONAT) , 2026
    2026
  • Empowering Elderly Care Through Artificial Intelligence
    NK Goyal, NK Goyal, S Kumar, R Dutta, V Kothari, SK Sinha
    AI for Geriatric Care in an Aging Society: Ethical, Clinical, and Policy … , 2026
    2026
    Citations: 5
  • Deep Learning Techniques for the Prediction of Heart Disease
    SK Sinha, S Prabha, NK Goyal, N Srivastava
    Intelligent Systems Using Semiconductors for Robotics and IoT, 371-374 , 2025
    2025
  • A New Approach for Identifying and Detecting Fake Reviews Using Ensemble Techniques with TF/IDF and Bi-Grams
    NK Goyal, S Sinha, D Bhatia
    Intelligent Systems Using Semiconductors for Robotics and IoT, 334-339 , 2025
    2025
  • Anthropomorphic AI: The Psychology of Human-Like Machines
    A Jain, S Gupta, M Choudhary, SK Sinha
    Intelligent Systems Using Semiconductors for Robotics and IoT, 303-309 , 2025
    2025
  • IoT-based optical sensor network for precision agriculture
    A Amit Sharma, Diksha Srivastava , Ramkumar Krishnamoorthy c , Sanjay Kumar ...
    Sustainable Computing: Informatics and Systems 46 , 2025
    2025
    Citations: 2
  • ML-enabled fault control and efficiency improvement in multi-cloud NFV
    SK Sinha
    International Journal of Systems Assurance Engineering and Management , 2025
    2025
  • Multi-cloud storage augmentation: a novel secured framework for information sharing
    SK Sanjay
    International Journal of Systems Assurance Engineering and Management , 2025
    2025
    Citations: 3
  • Enhancing Cybersecurity with Blockchain: A Decentralized Approach to Securing Digital Infrastructure
    CA Sinha Kumar Sanjay, Sandip Kumar Singh Modak,Praven Kumar Tyagi
    ICIMMI , 2024
    2024
  • Engineering Smart Systems for Early Breast Cancer Detection
    NR Sanjay Kumar Sinha, Abhijeet Nashte
    ICIMMI , 2024
    2024
  • Boundary stress distribution and elastic viscous of emerging pavement predicted using an innovative hybrid machine learning technique
    HRM Intekab Alama , Sanjay Kumar Sinha, Karishma Desai
    Multidisciplinary Science Journal , 2024
    2024
  • Sustainable Vertical Farming: Leveraging Machine Learning and IoT for Energy Efficiency and Productivity
    AD Sanjay Kumar Sinha, Shruti Gupta
    ICIMMI , 2024
    2024
  • Analyzing the Use of Machine Learning Models for Enhancing Big Data Retrieval Performance
    MP Saniya Khurana,Balakumar P,Sanjay Kumar Sinha
    2023 IEEE International Conference on Paradigm Shift in Information … , 2024
    2024
  • Elevating Optical Networks : Machine Learning approach for optimal resource scheduling and performance boost
    SK Sinha, P Saraswat, Prabhakaran
    International Journal of Communication Systems , 2024
    2024
    Citations: 2
  • Deep Learning based Methodology for tracking cyber security in networked computers
    N R.S., SK Sinha, Uchil
    Risk Assessment and countermeasures for cybersecurity , 2024
    2024
  • Modernizations in wear-resistant materials: Development of aluminum and polyamide feedstock filaments for fused deposition modelling
    NK Rajendran, Naresh Kaushik , B.P. Singh , Sanjay Kumar Sinha
    Emerging Trends in Engineering and Technology: Shaping the Future of … , 2024
    2024
  • Blockchain Empowerment: Investigating Integration with software defined networks and its impact on IoT privacy
    SK Sinha, S Kumari, A Kataria
    Multidisciplinary Reviews , 2024
    2024
    Citations: 20

MOST CITED SCHOLAR PUBLICATIONS

  • Blockchain Empowerment: Investigating Integration with software defined networks and its impact on IoT privacy
    SK Sinha, S Kumari, A Kataria
    Multidisciplinary Reviews , 2024
    2024
    Citations: 20
  • Empowering Elderly Care Through Artificial Intelligence
    NK Goyal, NK Goyal, S Kumar, R Dutta, V Kothari, SK Sinha
    AI for Geriatric Care in an Aging Society: Ethical, Clinical, and Policy … , 2026
    2026
    Citations: 5
  • Multi-cloud storage augmentation: a novel secured framework for information sharing
    SK Sanjay
    International Journal of Systems Assurance Engineering and Management , 2025
    2025
    Citations: 3
  • Analyzing the Use of Machine Learning Models for Enhancing Big Data Retrieval Performance
    S Khurana, P Balakumar, NP Sable, SK Sinha, M Pandey, VM Saravanan
    2023 IEEE International Conference on Paradigm Shift in Information … , 2023
    2023
    Citations: 3
  • IoT-based optical sensor network for precision agriculture
    A Amit Sharma, Diksha Srivastava , Ramkumar Krishnamoorthy c , Sanjay Kumar ...
    Sustainable Computing: Informatics and Systems 46 , 2025
    2025
    Citations: 2
  • Elevating Optical Networks : Machine Learning approach for optimal resource scheduling and performance boost
    SK Sinha, P Saraswat, Prabhakaran
    International Journal of Communication Systems , 2024
    2024
    Citations: 2
  • Role of Big Data and Analytics to Enhance the Higher Education in India
    SK Sinha
    International Journal of Computer Applications 975, 8887 , 2020
    2020
    Citations: 2
  • Comparing Smote and Adasyn for Detection of Credit Card Fraud
    M Sakpal, SK Sinha
    International Conference on “Recent Trends in Environment and Sustainable … , 2023
    2023
    Citations: 1
  • FTTX NETWORK DESIGN ARCHITECTURES
    SKS Fahim Khan
    International Research Journal of Modernization in Engineering Technology … , 2023
    2023
    Citations: 1
  • Wideband Technology Design with the Novel Based Technogy : An Antenna Systems
    DS Murugan R, Sanjay Kumar Sinha
    2023 International Conference on Power Energy, Environment & Intelligent … , 2023
    2023
    Citations: 1
  • DATA MINING AND KNOWLEDGE DISCOVERY IN LARGE-SCALE SYSTEMS
    DNKGPDSKSDPMADSBEDUD PRASAN
    ISBN: 978-81-685858-3-6 , 2026
    2026
  • AI-Driven Bharatiya Vanshavali and Heritage Analytics: Lev eraging Cloud Computing for Genealogical Research
    DSK Sinha
    Integrating Modern Technology with Ancient Knowledge for Developing a … , 2026
    2026
  • Fusion Technologies in Governance: From Algorithmic Intelligence to Augmented Reality
    NKG Kamini Pareek , Navin Kumar Goyal , Neetu Sharma, Sanjay Kumar Sinha
    AI-Powered Augmented Reality for Public Administration, 22 , 2026
    2026
  • An Innovative Framework on Predicting House Price Using Machine Learning Approaches
    D Das, R Dutta, S Singh, S Sharma, NK Goyal, SK Sinha
    2025 IEEE 4th International Conference for Advancement in Technology (ICONAT) , 2026
    2026
  • Deep Learning Techniques for the Prediction of Heart Disease
    SK Sinha, S Prabha, NK Goyal, N Srivastava
    Intelligent Systems Using Semiconductors for Robotics and IoT, 371-374 , 2025
    2025
  • A New Approach for Identifying and Detecting Fake Reviews Using Ensemble Techniques with TF/IDF and Bi-Grams
    NK Goyal, S Sinha, D Bhatia
    Intelligent Systems Using Semiconductors for Robotics and IoT, 334-339 , 2025
    2025
  • Anthropomorphic AI: The Psychology of Human-Like Machines
    A Jain, S Gupta, M Choudhary, SK Sinha
    Intelligent Systems Using Semiconductors for Robotics and IoT, 303-309 , 2025
    2025
  • ML-enabled fault control and efficiency improvement in multi-cloud NFV
    SK Sinha
    International Journal of Systems Assurance Engineering and Management , 2025
    2025
  • Enhancing Cybersecurity with Blockchain: A Decentralized Approach to Securing Digital Infrastructure
    CA Sinha Kumar Sanjay, Sandip Kumar Singh Modak,Praven Kumar Tyagi
    ICIMMI , 2024
    2024
  • Engineering Smart Systems for Early Breast Cancer Detection
    NR Sanjay Kumar Sinha, Abhijeet Nashte
    ICIMMI , 2024
    2024