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Academic Experts
Dr. Jyoti Rani

Biography

Dr. Jyoti Rani joined the Department of Computer Science and Engineering at Jaypee Institute of Information Technology (JIIT), Noida on July 21, 2025, and is currently serving as an Assistant Professor(Senior Grade).She holds a Ph.D. in Computer Science and Engineering from Thapar Institute of Engineering & Technology, Patiala. She received her M.Tech. and B.Tech. degrees in Computer Science and Engineering through Maharshi Dayanand University, Rohtak.

Prior to joining JIIT, she served as an Assistant Professor at Manipal University Jaipur from July 26, 2024, to July 18, 2025. Before that, she was associated with the Department of Computer Science and Engineering at Motilal Nehru National Institute of Technology (MNNIT), Allahabad as a Guest Faculty from July 15, 2018, to March 31, 2021. She also worked as an Assistant Professor at Pt. L.R. College of Technology, Faridabad from January 1, 2017, to January 19, 2018.

Research Highlights

My research primarily focuses on enhancing information security through advanced watermarking techniques applied to medical signals and images. With the growing adoption of e-healthcare systems and IoT-enabled medical devices, securing sensitive patient data during transmission and storage has become a critical challenge. To address this, I have developed robust watermarking frameworks that ensure data confidentiality, authenticity, and integrity without compromising diagnostic quality. These methods integrate signal and image processing techniques with modern security approaches to embed imperceptible and reversible watermarks within medical data.

A major innovation in my work is the incorporation of deep learning models to optimize the watermark embedding and extraction process. This approach enables the watermark to adapt intelligently to various types of medical images, such as ECG signals and MRI scans, while preserving the region of interest (ROI) for accurate medical analysis. Additionally, the use of reversible data hiding ensures that the original image or signal can be perfectly recovered after watermark removal, which is crucial in clinical applications where data precision is non-negotiable. The integration of these methods not only supports data ownership and traceability but also builds trust in digital healthcare platforms. Overall, my research contributes to the development of secure, intelligent, and privacy-preserving solutions for medical data protection in modern digital environments.

Areas of Interest
  • Signal/Image Processing
  • Information Security
  • Deep Learning based Watermarking
  • Cyber Security
Publications
  • J. Rani, A. Anand, and S. Shivani, "VMD-based ECG signal watermarking using image fusion: a robust and versatile approach for secure telemedical services," Multimedia Tools and Applications, pp. 1–18, 2023.
  • J. Rani, A. Anand, and S. Shivani, "SecECG: secure data hiding approach for ECG signals in smart healthcare applications," Multimedia Tools and Applications, pp. 1–21, 2023.
  • J. Rani, A. Anand, and S. Shivani, “Denoising Convolutional Neural Network Assisted Electrocardiogram Signal Watermarking for Secure Transmission in E-Healthcare Applications,” IEEE MultiMedia, vol. 31, no. 2, pp. 1–8, 2025.
  • R. Sood, J. Rani, A. Anand, J. Bedi, Deep learning-based dual watermarking solution for securing medical images in e-healthcare, Knowledge-Based Systems (2025) 114750.
  • J. Rani, A. Anand, A review on advancement in watermarking techniques for biomedical data in e-healthcare applications, Biomedical Signal Processing and Control 112 (2026) 108521.
  • J. Rani, A. Anand, and S. Shivani, "A Novel Dual Watermarking for ECG Signals with Improved Payload," in Proc. 8th Int. Conf. on Computer Vision and Image Processing (CVIP 2023), IIT Jammu, India, Nov. 3–5, 2023. (Presented)
  • R. Sood, J. Rani, and A. Anand, "Improved Watermarking Approach Empowered by Deep Learning for Copyright Protection of Digital Images," in Proc. 9th Int. Conf. on Computer Vision and Image Processing (CVIP 2024), IIITDM Kancheepuram, Chennai, India, Dec. 19–21, 2024. (Presented)