JIIT

Academic Experts

Mr. Megh Singhal

ASSISTANT PROFESSOR (GRADE-II)

megh.singhal@jiit.ac.in

Biography

Megh Singhal is an Assistant Professor (Grade-II) in the Department of Computer Science & Engineering and Information Technology (CSE/IT), Jaypee Institute of Information Technology (JIIT), Noida, India. He has joined the Institute in Aug 2024, since then he is associated with academics and research activities at the university level. He is pursuing his PhD in Computer Science and Engineering from Jaypee Institute of Information Technology (JIIT), Noida from Aug 2022. He has completed his M.Tech. in Computer Science and Engineering- Information Security from Jaypee Institute of Information Technology (JIIT), Noida in year 2017 and B.Tech. in Computer Science and Engineering from ABES Institute of Technology (ABESIT), Ghaziabad in year 2015. He has more than 7 years of teaching experience. He has mentored 15+ student projects at under-graduate level. He has published several research papers in various reputed indexed international journals and conferences. He is associated as a reviewer and TPC member for international conferences.

Educational Qualifications

Pursuing his PhD in Computer Science and Engineering from Jaypee Institute of Information Technology (JIIT), Noida from Aug 2022., M.Tech in Computer Science and Engineering- Information Security from Jaypee Institute of Information Technology (JIIT), Noida in year 2017., B.Tech in Computer Science and Engineering from ABES Institute of Technology (ABESIT), Ghaziabad in year 2015.

Research Highlights

He is interested about using data-driven methods to examine complex systems, with a particular emphasis on machine learning, data science and social network analysis. The structure, dynamics, and patterns of information flow in complex networks, such those in different types of social networks, are the subjects of his research. Through the application of multidisciplinary approaches, he addresses practical issues like as community detection, influence diffusion and influence maximization. Additionally, in order to facilitate efficient decision-making, he is interested in time series analysis and predictive analytics. My research has led to the development of novel methodologies that have advanced understanding in influence diffusion and influence maximization. My findings have been presented at major journal and international conferences, helping to disseminate knowledge and establish a strong professional network.

Areas Of Interest

Data Mining
Data Science
Network Security
Social Network Analysis

Publications

M. Singhal and B. Saxena, “Edge Sign And Strength Based Model for Influence Diffusion in Signed Social Networks,” Advances in Complex Systems, 2025, ISSN: 0219-5259, doi: 10.1142/s021952592540003x
M. Singhal and B. Saxena, “BO-CBoost: A Machine Learning Based Framework for Predicting the Influence Potential of Nodes in Complex Networks,” International Journal of Performability Engineering, 2024, Vol 20, Issue 11, p658, doi: 10.23940/ijpe.24.11.p2.658667
M. Singhal and B. Saxena, "Exploring the Performance of Diffusion Models in Weighted Social Networks," 2024 2nd International Conference on Disruptive Technologies (ICDT), Greater Noida, India, 2024, pp. 920-923, doi: 10.1109/ICDT61202.2024.10489068.
R. Chauhan et al., "An IoT-based Novel Framework for Early Prediction of Forest Fire," 2023 International Conference on Disruptive Technologies (ICDT), Greater Noida, India, 2023, pp. 727-732, doi: 10.1109/ICDT57929.2023.10151047.
M. Singhal, B. Saxena, A. P. Singh and A. Baranwal, "Study of the effectiveness of Generative Adversarial Networks towards Music Generation," 2023 Second International Conference on Informatics (ICI), Noida, India, 2023, pp. 1-5, doi: 10.1109/ICI60088.2023.10421735.