Ms. Jyoti Shekhawat | Department of Computer Science and Engineering

Bio

Jyoti Shekhawat is an Assistant Professor in Computer Science and Engineering at Vivekananda Global University and a research scholar at Banasthali Vidyapith. She specializes in Artificial Intelligence and Machine Learning, with a strong focus on Deep Learning. Her research explores advanced models for applications such as brain tumor detection using MRI images, emphasizing accurate, interpretable, and real-world solutions. She has published in Scopus-indexed journals and conferences, contributing to healthcare, networking, and intelligent systems. Alongside research, she actively teaches Computer Science Engineering students, simplifying complex concepts into practical, engaging learning experiences while mentoring and supporting interdisciplinary research initiatives. And Circular Economy.

Additional Administrative Titles

Admission Head (Formar)

Training & Placement (T&P) Coordinator (Former)

Academic Degrees

PhD*

M.Tech (Computer Science and Engineering)
M.tech*(Artificial Intelligence and Data Science)

Academic Appointments

Assistant Professor, Vivekananda Global University, Jaipur (August 2022 – Present)
Assistant Professor & Admission Head, SITM Rewari (Aug 2015 – Dec. 2019)

Professional Experience

Over 8+ years of teaching experience in Computer Science & Engineering Experience in academic leadership, admissions management, and student mentoring Strong focus on curriculum development and outcome-based education Expertise in innovative teaching pedagogy and simplifying complex concepts Actively engaged in research, interdisciplinary learning, and student skill development

Courses Taught

BCA, MCA. B.Tech, B.Tech (AI&ML), M. TECH(CSE), M.Tech (AI &ML)

Teaching

Degree Courses:
C Programming
Java Programming
Data Structures
Design & Analysis of Algorithms
TOC
DBMS
ADBMS
Master Degree Courses:
Machine Learning
IOT
Data Mining & Data visualization
Image Processing

Research Interests

Artificial Intelligence Machine learning, Deep learning

Journal Articles

[1] D. Preethi, J. Shekhawat, B. Saraswat, H. Naik, K. Desai, “Self-Sustaining Energy Management Systems in Smart Microgrids Using Artificial Intelligence,” Int. J. Control, Automation, and Systems, pp. 1–23, 2026.
[2] J. Shekhawat, A. Kumar, “Optimized serverless cloud-based real-time processing architecture for sensor data analytics in healthcare,” in Smart Technologies and Intelligent Computing, pp. 196–204, 2026.
[3] A. J. M. Jantabo, J. Shekhawat, “Phishing Detection Using Convolutional Neural Network,” in Proc. IEEE Int. Conf. Computing, Communication and Networking, 2026.
[4] A. M. Jantabo, J. Shekhawat, “Phishing Detection Using Deep Learning: A Systematic Review,” Techno Review J. Technol. Manag., vol. 5, no. 4, pp. 20–33, 2025.
[5] S. Makkar, J. Sidhu, T. Zaidi, R. Batra, P. Garg, J. Shekhawat, “Advanced model for maximizing multi-cloud security through job scheduling,” Int. J. Syst. Assurance Eng. Manag., pp. 1–9, 2024.
[6] N. R. S. Jebaraj, J. Shekhawat, R. Gupta, “Retracted: An Overview of Clustering Algorithms for Credit Card Fraud Detection,” in Proc. Int. Conf. Optimization Computing and Wireless Communication, 2024.
[7] M. Sunil, J. Shekhawat, T. Vanaja, V. A. Mohammed, S. J. Thaware, V. Singh, “Deep Learning Techniques for Advanced Large-Scale Data Processing,” in Proc. 15th Int. Conf. Computing, Communication and Networking Technologies, 2024.
[8] K. Jain, P. Cajla, S. Yadav, M. G. N., S. Khurana, J. Shekhawat, “QoS improvement in multi-cloud system: Installation cost optimization strategy,” Int. J. Syst. Assurance Eng. Manag., pp. 1–10, 2024.
[9] J. Shekhawat, R. Kumar, N. R. S. Jebaraj, K. K. Brar, H. M. Al-Jawahry, G. Thakur, “Deep Learning Approach for Optimal Segmentation and Classification of Multi-Class Skin Cancer,” in Proc. Int. Conf. Reliability, Infocom Technologies and Optimization, 2024.
[10] V. Ravikumar, M. K. Kodmelwar, J. Shekhawat, N. N. Sakhare, et al., “Retracted: Unlocking the Power of Natural Language Processing to Automate Knowledge Discovery,” in Proc. 3rd Int. Conf. Smart Generation Computing, 2023.
[11] E. Sweety Bakyarani, N. P. Singh, J. Shekhawat, S. Bhardwaj, S. Chaku, et al., “A Novel Approach on Deep Reinforcement Learning for Improved Throughput in Power-Restricted IoT Networks,” in Proc. Int. Conf. Electrical and Electronics Engineering, pp. 63–76, 2023.
[12] J. Shekhawat, “A Multi-Objective Hyper-Heuristic Improved Configuration of SVM Based on Particle Swarm Optimization for Big Data Cyber Security,” in Proc. 3rd Int. Conf. Advance Computing and Innovative Technologies, 2023.
[13] M. Eti, J. Shekhawat, M. Nagpal, P. G. Chavhan, R. K. Yadav, “Implementing Long Short-Term Memory Network for Enhancing Hyperspectral Time Series Modeling,” in Proc. IEEE Int. Conf. Paradigm Shift in Information Technology, 2023.
[14] K. G. Krishna, J. Shekhawat, T. Agarwal, “Utilization of ECC in Smart Grids: A Review,” in Proc. Int. Conf. Power, Energy, Environment and Intelligent Control, 2023.
[15] M. J. Shekhawat, M. R. Khurana, “Time-stretching and genetic zooms in OutGene: Detecting Undefined Network Attacks,” in Proc. Int. Conf. Contemporary Computing and Informatics, 2022.
[16] D. Chhabra, J. Shekhawat, “A reliable security model that protects ultra-dense enterprise cloud networks from highly vulnerable cyber-attacks,” in Proc. Int. Interdisciplinary Humanitarian Conf., 2022.
[17] J. Shekhawat, “Special issue on the Internet of Things and its application,” Int. J. Eng. Manag. Res. (IJEMR), vol. 6, no. 5, pp. 552–556, 2016.

Conferences, Talks & Speaking Engagements

Served as a Session Chair at the International Conference on Progressive Trends in Engineering, Management & Science (PTEMS-2026) organized by Greater Noida Institute of Technology, demonstrating academic leadership and research contribution.
Also served as a Session Chair at the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI-2025) at Compuccom Institute of Technology and Management, Jaipur.