Kapil Dev Raghuwanshi

@iujaipur.edu.in

Assistant Professor
IcfaiTech, The ICFAI University, Jaipur Rajasthan

Kapil Dev Raghuwanshi


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https://researchid.co/dev2988
Mr. Kapil Dev Raghuwanshi is an Assistant Professor at the
Department of Computer Science and Engineering, IcfaiTech, The
ICFAI University, Jaipur with over 14+ years of academic and
industry experience, he is a dedicated educator and researcher in the
domains of Cloud Computing, Machine Learning, Artificial
intelligence, Network Security and Computer networks. He holds a
B.E. in Computer Science and Engineering (2010) From RGPV
Bhopal, an MTech. in Computer Science and Engineering (2015) From
RGPV Bhopal, and is currently pursuing a Ph.D. in Computer
Engineering from Indus Institute of Technology and Engineering Ahmedabad, Indus
University, Ahmedabad (Gujarat).
Prof. Kapil Dev Raghuwanshi has published 11+ research papers in reputed journals and
International Conferences, including Springer Nature, IEEE Xplore, and Scopus-indexed
proceedings. His research focuses on artificial intelligence, Cloud Computing, Machine
Learning, and Network Security, addressing real-world challenges such

EDUCATION

Education Qualification Pursuing Ph.D. in Computer Engineering from Indus Institute of Technology and Engineering Ahmedabad, Indus University, Ahmedabad (Gujarat)
Examination Year of Passing University/ Board % of Marks
M. Tech. (C.S.E.) AUGUST – 2015 RGPV 77.9%
B.E. (C.S.E.) JUNE – 2010 RGPV 75.59%
XII MARCH – 2006 M.P. BOARD 70.88%
X MARCH – 2004 M.P. BOARD 57.4%

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Multidisciplinary, Computer Networks and Communications
9

Scopus Publications

51

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • GenoDense-Net: unraveling the genomic puzzle of the global pathogen
    Shivendra Dubey, Sakshi Dubey, Kapil Raghuwanshi, Pranshu Pranjal, Sudheer Kumar
    Tropical Diseases Travel Medicine and Vaccines, 2025
    The respiratory system of humans is impacted by infectious and deadly illnesses like COVID-19. Early identification and diagnosis of this type of illness is essential to stop the infection from spreading further. In the present research, we presented a technique for determining the condition using COVID-19's current genome sequences employing the DenseNet-16 framework. We operated a network of already trained neurons before using a transfer learning method to prepare it according to our dataset. Additionally, we preprocessed the collected information using the NearKbest interpolation approach; then, we utilized Adam Optimizer to optimize our findings. Compared with special deep learning models like ResNet-50, VGG-19, AlexNet, and VGG-16, our approach produced an accuracy of 99.18%. The model was deployed on a platform with GPU support, which greatly decreased training time. Dataset size and the requirement for further validation are two of the study's limitations, despite the encouraging results. The current research showed how a deep learning approach may be useful to categorize the genome sequence of infectious disease like COVID-19 using the suggested GenoDense-Net architecture. The next step in this research project is conducting investigations in the clinic.
  • Unlocking IoT and Machine Learning’s Potential for Water Quality Assessment: An Extensive Analysis and Future Directions
    Shivendra Dubey, Sakshi Dubey, Kapil Raghuwanshi
    Water Conservation Science and Engineering, 2025
  • Revolutionize Infectious Prevention Using Artificial Intelligence and Deep Learning
    Dinesh Kumar Verma, Shweta Singh, Shivendra Dubey, Kapil Raghuwanshi
    Communications in Computer and Information Science, 2025
  • A Survey: Detection of Heart-Related Disorders Using Machine Learning Approaches
    Kapil Dev Raghuwanshi, Shruti Yagnik
    Communications in Computer and Information Science, 2024
  • Generic Framework of New Era Artificial Intelligence and Its Applications
    Brij Mohan Sharma, Dinesh Kumar Verma, Kapil Dev Raghuwanshi, Shivendra Dubey, Rajit Nair, Sachin Malviya
    Communications in Computer and Information Science, 2024
  • Revealing a State-of-the-Art Machine Learning Architecture for Comprehensive Evaluation of Hepatitis disease
    Sachin Malviya, Shivendra Dubey, Sudheer Kumar Lodhi, Devendra Parmar, Kapil Raghuwanshi, Dinesh Kumar Verma
    2024 Parul International Conference on Engineering and Technology Picet 2024, 2024
    One of the most destructive illnesses in the world is hepatitis. On the basis of features, machine learning techniques can help with hepatitis disease diagnosis. The authors evaluated the effectiveness of various classification methods on the data set provided by UCI in order to create a methodical approach for diagnosing hepatitis disease. The random forests, support vector machines, K-nearest neighbor, and logistic regression (LR) are some of the classifiers that are employed. Both with and without class balancing, the classifiers were used in conjunction with the SMOTE strategy for class balancing. The two studies—one on class balancing and the other on classification with no class balancing—were contrasted based on various performance metrics. The effective performance of classification algorithms increased dramatically following class balancing was implemented. The highest accuracy was achieved with LR and SMOTE (93.19%).
  • Ordered Ensemble Classifier Chain for Image and Emotion Classification
    Puneet Himthani, Puneet Gurbani, Kapil Dev Raghuwanshi, Gopal Patidar, Nitin Kumar Mishra
    Lecture Notes on Data Engineering and Communications Technologies, 2022
  • Multi-tier Authentication for Cloud Security
    Kapil Dev Raghuwanshi, Puneet Himthani
    Lecture Notes in Networks and Systems, 2020
  • An effective access from cloud data using attribute based encryption
    Kapil Dev Raghuwanshi, Sitendra Tamrakar
    2015 1st International Conference on Futuristic Trends in Computational Analysis and Knowledge Management Ablaze 2015, 2015
    Cloud Computing is an important way of communicating and share data over Internet. Cloud Computing enables transmission of data over Internet and resource utilization at data centers. But during data sharing and resource utilization security plays a vital role since the chances of attacks increases. The data to be stored at data centers needs to be retrieved without any data loss and attack. Hence a multi key based data retrieved with encryption is proposed previously but the techniques require more computational time and hence increase the overall cost. Here in this paper a new and efficient is implemented which uses the concept of Cipher text policy attribute based encryption using elliptic curve based key generation. The implementation is based on the concept of generating a new attribute for each and every data to be send and encrypt the data using the generated attribute and forms a tupple and stored at the storage site. The receiver then authenticates himself and enters the attribute and hence decrypts the data. The proposed methodology implemented here provides efficient retrieval of data over cloud as well as reduces computational time and cost.

RECENT SCHOLAR PUBLICATIONS

  • GenoDense-Net: unraveling the genomic puzzle of the global pathogen
    PPSK Shivendra Dubey, Sakshi Dubey, Kapil Raghuwanshi
    Tropical Diseases, Travel Medicine and Vaccines 11 (32) , 2025
    2025.0
  • Unlocking IoT and machine learning’s potential for water quality assessment: an extensive analysis and future directions
    S Dubey, S Dubey, K Raghuwanshi
    Water Conservation Science and Engineering 10 (1), 18 , 2025
    2025.0
    Citations: 4
  • Revealing a State-of-the-Art Machine Learning Architecture for Comprehensive Evaluation of Hepatitis Disease
    S Malviya, S Dubey, SK Lodhi, D Parmar, K Raghuwanshi, DK Verma
    2024 Parul International Conference on Engineering and Technology (PICET) , 2024
    2024.0
  • Generic Framework of New Era Artificial Intelligence and Its Applications
    BM Sharma, DK Verma, KD Raghuwanshi, S Dubey, R Nair, S Malviya
    International Conference on Applied Technologies, 149-163 , 2024
    2024.0
    Citations: 34
  • A Survey: Detection of Heart-Related Disorders Using Machine Learning Approaches
    KD Raghuwanshi, S Yagnik
    International Conference on Applied Technologies, 178-188 , 2024
    2024.0
  • Revolutionize Infectious Prevention Using Artificial Intelligence and Deep Learning
    DK Verma, S Singh, S Dubey, K Raghuwanshi
    International Conference on Advances in Computing and Data Sciences, 334-345 , 2024
    2024.0
    Citations: 1
  • Ordered Ensemble Classifier Chain for Image and Emotion Classification
    P Himthani, P Gurbani, K Dev Raghuwanshi, G Patidar, N Kumar Mishra
    Congress on Intelligent Systems: Proceedings of CIS 2021, Volume 1, 395-406 , 2022
    2022.0
    Citations: 1
  • Multi-tier authentication for cloud security
    KD Raghuwanshi, P Himthani
    Social Networking and Computational Intelligence: Proceedings of SCI-2018, 67-75 , 2020
    2020.0
    Citations: 4
  • An Efficient Methodology for Cloud Computing to Retrieve Data
    KD Raghuwanshi, S Tamrakar
    2015.0
    Citations: 1
  • An effective access from cloud data using attribute based encryption
    KD Raghuwanshi, S Tamrakar
    2015 International Conference on Futuristic Trends on Computational Analysis … , 2015
    2015.0
    Citations: 3
  • An enhanced integrated solution for identification and elimination of wormhole attack in MANET
    K Raghuwanshi, A Saxena, M Manoria
    International Journal of Computer Applications 110 (7), 16-21 , 2015
    2015.0
    Citations: 3
  • Mutual Authentication in Cloud System using Two Level Security with One Time Password
    S Tamrakar, KD Raghuwanshi

MOST CITED SCHOLAR PUBLICATIONS

  • Generic Framework of New Era Artificial Intelligence and Its Applications
    BM Sharma, DK Verma, KD Raghuwanshi, S Dubey, R Nair, S Malviya
    International Conference on Applied Technologies, 149-163 , 2024
    2024.0
    Citations: 34
  • Unlocking IoT and machine learning’s potential for water quality assessment: an extensive analysis and future directions
    S Dubey, S Dubey, K Raghuwanshi
    Water Conservation Science and Engineering 10 (1), 18 , 2025
    2025.0
    Citations: 4
  • Multi-tier authentication for cloud security
    KD Raghuwanshi, P Himthani
    Social Networking and Computational Intelligence: Proceedings of SCI-2018, 67-75 , 2020
    2020.0
    Citations: 4
  • An effective access from cloud data using attribute based encryption
    KD Raghuwanshi, S Tamrakar
    2015 International Conference on Futuristic Trends on Computational Analysis … , 2015
    2015.0
    Citations: 3
  • An enhanced integrated solution for identification and elimination of wormhole attack in MANET
    K Raghuwanshi, A Saxena, M Manoria
    International Journal of Computer Applications 110 (7), 16-21 , 2015
    2015.0
    Citations: 3
  • Revolutionize Infectious Prevention Using Artificial Intelligence and Deep Learning
    DK Verma, S Singh, S Dubey, K Raghuwanshi
    International Conference on Advances in Computing and Data Sciences, 334-345 , 2024
    2024.0
    Citations: 1
  • Ordered Ensemble Classifier Chain for Image and Emotion Classification
    P Himthani, P Gurbani, K Dev Raghuwanshi, G Patidar, N Kumar Mishra
    Congress on Intelligent Systems: Proceedings of CIS 2021, Volume 1, 395-406 , 2022
    2022.0
    Citations: 1
  • An Efficient Methodology for Cloud Computing to Retrieve Data
    KD Raghuwanshi, S Tamrakar
    2015.0
    Citations: 1
  • GenoDense-Net: unraveling the genomic puzzle of the global pathogen
    PPSK Shivendra Dubey, Sakshi Dubey, Kapil Raghuwanshi
    Tropical Diseases, Travel Medicine and Vaccines 11 (32) , 2025
    2025.0
  • Revealing a State-of-the-Art Machine Learning Architecture for Comprehensive Evaluation of Hepatitis Disease
    S Malviya, S Dubey, SK Lodhi, D Parmar, K Raghuwanshi, DK Verma
    2024 Parul International Conference on Engineering and Technology (PICET) , 2024
    2024.0
  • A Survey: Detection of Heart-Related Disorders Using Machine Learning Approaches
    KD Raghuwanshi, S Yagnik
    International Conference on Applied Technologies, 178-188 , 2024
    2024.0
  • Mutual Authentication in Cloud System using Two Level Security with One Time Password
    S Tamrakar, KD Raghuwanshi