JIIT

Academic Experts

Dr. Himani Bansal

Associate Professor

himani.bansal@jiit.ac.in

Biography

Dr. Himani Bansal is an accomplished academician and researcher with over 19 years of professional experience, transitioning from a Software Engineer at Satyam Computer Services to an Associate Professor at Jaypee Institute of Information Technology, Noida. Her expertise spans Machine Learning, Data Science, Web Analytics, Trust Analysis, and Machine Unlearning, where she continues to contribute through research, teaching, and project leadership.

She is the Principal Investigator of a SERB-sponsored project on obscene image detection and exclusion, and holds three granted patents with several more filed in AI-driven innovations. Her scholarly contributions include authored and edited books with leading publishers (CRC Press, Wiley, IGI Global, BPB) and numerous research papers in Scopus and SCI/SCIE-indexed journals. She has guided one Ph.D. candidate to completion and is currently supervising three more in emerging areas like Machine Unlearning and Explainable AI.

A Senior Member of IEEE and active contributor to professional societies (ACM, CSI, ISTE, IFERP), Dr. Bansal has delivered keynote talks, chaired sessions at international conferences, and served as guest editor for reputed journals. She has also been actively engaged in academic leadership, curriculum design, and institutional committees, alongside mentoring young researchers.

Recognized for her academic excellence and innovative research, Dr. Bansal has received multiple awards, including the AICTE Vishwakarma Award finalist position and the Excellence in Research Journal Award by IGI Global. With her ongoing post-doctoral research in Machine Unlearning at the University of South Florida, she continues to push the boundaries of trustworthy and ethical AI.

Educational Qualifications

Ph.D. (Computer Science & Engineering) from Birla Institute of Technology, Mesra, Qualified UGC – NET in June’13, M. Tech. (Computer Science) from Birla Institute of Technology, Mesra (Attained CGPA of 9.07 (90.7%)), B.E. (Computer Engineering) from University of Rajasthan

Research Highlights

Dr. Himani Bansal’s research contributions lie at the intersection of Machine Learning, Data Science, Trust Analysis, and Machine Unlearning, with a focus on building reliable and ethical AI systems. She has authored and co-edited multiple books with leading publishers including CRC Press, Wiley, and IGI Global, covering domains such as cybersecurity, healthcare analytics, blockchain, and trust modeling.

Her recent work emphasizes Machine Unlearning, an emerging area that addresses data privacy and regulatory compliance by enabling AI models to selectively forget information. As a post-doctoral researcher at the University of South Florida, she is advancing frameworks and methodologies to enhance transparency, efficiency, and trust in AI-driven systems.

Dr. Bansal has published extensively in SCI/SCIE and Scopus-indexed journals, with impactful studies on trust evaluation of health websites, brain disorder segmentation, and AI-driven medical imaging. Her work on trust modeling in digital ecosystems earned the Excellence in Research Journal Award from IGI Global.

She is the Principal Investigator of a SERB-funded project on obscene image detection and exclusion in imaging devices, integrating deep learning for content safety. Additionally, she has been granted three patents in AI-based automation and human–computer interaction technologies, with several others under review.

With an ongoing record of Ph.D. supervision in Machine Unlearning and Explainable AI, Dr. Bansal’s research continues to push boundaries in developing AI that is responsible, interpretable, and socially impactful.

Areas Of Interest

Machine Learning & Deep Learning
Machine Unlearning
Data Science & Big Data Analytics
Trust Modeling & Web Analytics
Explainable AI (XAI) & Ethical AI
Medical Image Analysis & Healthcare Analytics
Cybersecurity & Blockchain Applications
Artificial Intelligence in Human–Computer Interaction
Content Safety & Obscene Image Detection
Cloud Computing & IoT-enabled Intelligent Systems

Publications

Gupta, S., & Bansal, H. (2023). Trust Evaluation of Health Websites by Eliminating Phishing Websites and Using Similarity Techniques. Concurrency and Computation: Practice and Experience.

Agarwal, S., & Bansal, H. (2024). eHTrust: Model for Trust Evaluation in Content-Driven Health Websites. Multimedia Tools and Applications, 1-31.

Bansal, H., & Kohli, S. (2019). Trust evaluation of websites: A comprehensive study. International Journal of Advanced Intelligence Paradigms, 13(1-2), 101-112.

Singal, H., & Kohli, S. (2016). Mitigating Information Trust: Taking the Edge off Health Websites. International Journal of Technoethics, 7(1), 16–33.

Bansal, H., Balusamy, B., Poongodi, T., & KP, F. K. (Eds.). (2021). Machine Learning and Analytics in Healthcare Systems: Principles and Applications. CRC Press, Taylor & Francis Group.