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Academic Experts

Anubhi Bansal

Biography

Ms. Anubhi Bansal is an academician and researcher in the field of Computer Science and Engineering with over 10 years of teaching experience. She is currently pursuing her Ph.D. in Computer Science & Engineering from Jaypee Institute of Information Technology (JIIT), Noida and holds an M.Tech. and B.Tech. in Computer Science and Information Technology from Uttar Pradesh Technical University, Lucknow. She is presently serving as an Assistant Professor (Grade-II) at JIIT Noida. 

Previously, she worked with JIMS Engineering Management Technical Campus, Greater Noida, GL Bajaj Institute of Technology & Management, HIMT Group of Institutions, and SB-BIT Meerut, contributing significantly to teaching, research, and student mentoring. She has also been an active member of organizing committees for conferences, Faculty Development Programs (FDPs), workshops, and academic events, contributing to the successful execution of professional and research-oriented activities. Her research interests include Social Network Analysis, Machine Learning, Data Analytics, Cloud Computing, and Blockchain. 

She has published several research papers in reputed IEEE, Springer, and Scopus-indexed journals and conferences, and has also served as a reviewer for international conferences. A GATE-qualified professional and NPTEL Silver Elite achiever in Deep Learning, she remains committed to academic excellence, innovation, and impactful research. 

Research Highlights

Ms. Anubhi Bansal's research focuses on Social Networks, Machine Learning, Data Analytics, and Healthcare Informatics. She has authored and co-authored several research papers published in reputed IEEE, Springer, and Scopus-indexed journals and conferences. 

Her work includes the application of deep learning for melanoma detection, machine learning-based cardiovascular disease prediction, mental health analytics. She has also explored secure cloud environments through virtual machine image verification techniques and contributed to scene identification systems using deep feature extraction methods.

Areas of Interest
  • Social Network Analysis
  • Machine Learning
  • Data Analytics
Patents

Title: ARTIFICIAL INTELLIGENCE BASED EMPLOYEE PERFORMANCE MONITORING DEVICE
ID: Design No. 465037-001 (Registered on 09/07/2025)
Specification: AI-based device for monitoring and evaluating employee performance through automated data collection, analytics, and intelligent decision-support mechanisms.