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STEPHEN DASS A View All

Assistant Professor

School of Technology

Mr. Stephen Dass is a graduate of Vellore Institute of Technology (VIT), Vellore campus, with an MS in Software Engineering and an M.Tech (By Research). He is currently pursuing his Ph.D. in Computer Science and Engineering from VIT University.

With over 4.8 years of teaching experience at VIT, Vellore, and Galgotias University, Greater Noida, Mr. Stephen Dass has supervised more than 15 student projects at the undergraduate and postgraduate levels.

He has published five articles in international and national journals and holds one patent. Additionally, he has authored a book titled Data Visualization Techniques for undergraduate students, published by Mercury Publications.

Mr. Stephen Dass has also served as a reviewer for international journals, including Transactions on Emerging Telecommunications Technologies (ETT) by Wiley & Sons, Inc. Furthermore, he was a reviewer for the International Conference on Electrical, Electronics, and Computing Technologies organized by Sharda School of Engineering and Technology, Sharda University, Greater Noida.

    • Graduation In :

      M S (Software Engineering)

    • Graduation From :

      Vellore Institute of Technology, Vellore Campus

    • Graduation Year :

      2013

    • Post Graduation In :

      M.tech (By Research)

    • Post Graduation From :

      Vellore Institute of Technology, Vellore Campus

    • Post Graduation Year :

      2020

    • Doctorate In :

      Ph.D (Thesis Submitted)

    • Doctorate From :

      Vellore Institute of Technology, Vellore Campus

    • Doctorate Year :

      2024

    • 4 yrs 8 months

  • Book Chapters

    • Stephen Dass A, Prabhu J. “Amelioration of Big Data Analytics by Employing Big Data Tools and Techniques”, IGI Global Applications of Security, Mobile, Analytic, and Cloud (SMAC) Technologies for Effective Information Processing and Management; 2018 Feb, 21.

    Publications in Journals

    • ArulDass, S. D., & Jayagopal, P. (2023). Classifying distinct emotions from parents of ASD child using EEG source data by combining Bernoulli–Laplace Prior and graph neural networks. Neural Computing and Applications, 1-19. with impact factor – 6.0. DOI : https://doi.org/10.1007/s00521-023-09171-y.
    • “ArulDass, S. D., & Jayagopal, P. (2022). Identifying Complex Emotions in Alexithymia Affected Adolescents Using Machine Learning Techniques. Diagnostics, 12(12), 3188. with impact factor – 3.6 . DOI: https://doi.org/10.3390/diagnostics12123188.
    • Kumar, M. S., Khan, M. Z., Rajendran, S., Noor, A., Dass, A. S., & Prabhu, J. (2022). Imbalanced classification in diabetics using ensembled machine learning. Computers, Materials and Continua, 72(3), 4397-4409.
    • Stephen Dass A, Prabhu J. “Ameliorating the Privacy on Large Scale Aviation Dataset by Implementing MapReduce Multi-Dimensional Hybrid k-Anonymization”,International Journal of Web portals (IJWP), IGI Global, 2019 May.
    • Stephen Dass A, Prabhu J. “Hybrid Coherent Encryption Scheme for Multimedia Big Data Management Using Cryptographic Encryption Methods”, International Journal of Grid and Utility Computing (IJGUC), Inderscience, 2018 may 02.

    Publications in Conferences

    • Stephen Dass A, Prabhu J. “Comparative Analysis of a Systematic Coherent Encryption Scheme for large-scale data management using Cryptographic Encryption Technique”, “2nd International Conference on Smart Computing and informatics. 2018 Jan 27.

  • Patents

    • “IoT-driven Automatic Rural Road Centerline Detection and Extraction from Aerial Images for Forest Fire Decision Support” published with Journal Number- 24/2023, Date: 16/06/2023. Patent no.202341036839.