Department of ECE

Dr.Mohebbanaaz

Associate Professor, Dept. of ECE
Dean – Research & Development (R&D), RCEW
Dean – Internal Quality Assurance Cell (IQAC), RCEW

Dr. Mohebbanaaz is an accomplished academician, researcher, and academic administrator with a Ph.D. in Signal and Image Processing using Machine Learning and Deep Learning from JNTU Hyderabad. With over 9 years of experience in teaching, research, and academic leadership, she is committed to promoting research excellence, innovation, and quality education. Her research focuses on Machine Learning, Deep Learning, Biomedical Signal Processing, Image Processing, Computer Vision, IoT, and Embedded Systems (FPGA & NVIDIA Platforms). She has published 50+ research papers in SCI, SCIE, and Scopus-indexed journals and has H-index of 17. She holds multiple granted and published patents in AI, healthcare, IoT, and smart technologies.

Dr. Mohebbanaaz has made significant contributions to research administration, accreditation (NBA & NAAC), faculty development, curriculum design, and institutional development. She is passionate about mentoring students and researchers while fostering interdisciplinary research and innovation to address real-world challenges.

Academic Profiles

    • Ph.D. in Signal and Image Processing using Machine Learning & Deep Learning, JNTUH, Hyderabad, jan-2024.
    • M.Tech. in Communication Systems and Signal Processing, G Pulla reddy Engineering College, JNTUA, Anantapur.
    • B.Tech. in Electronics and Communication Engineering, G Pullaiah College of Engineering and technology, JNTUA, Anantapur.

     

List of few SCI/Scopus High Impact Journals

  1. Mohebbanaaz, Shaik Khudsia Tabassum, Y Padma Sai, Lightweight structural CNN–LSTM model for early detection of diabetic retinopathy on edge platforms, Biomedical Signal Processing and Control, Volume 122,110300. (2026)
  2. Mohebbanaaz et.al, A novel inference system for detecting cardiac arrhythmia using deep learning framework. Neural Comput & Applic37, 9759–9775 (2025).
  3. Mohebbanaaz et.al Classification of ECG beats using optimized decision tree and adaptive boosted optimized decision tree. SIViP16, 695–703 (2022)
  4. Mohebbanaaz et.al “Cognitive assistant DeepNet model for detection of cardiac arrhythmia, Biomedical Signal Processing and Control”, Volume 71, Part B, 103221, ISSN 1746-8094. (2022)
  5. Mohebbanaaz et.al A new transfer learning approach to detect cardiac arrhythmia from ECG signals. SIViP16, 1945–1953 (2022).

For more Publications visit  https://scholar.google.com/citations?user=Hy7sFPsAAAAJ