Dr. Avatharam Ganivada
Associate Professor, SCIS, University of Hyderabad
Avatharam Ganivada

School of Computer & Information Sciences

Avatharam Ganivada

Researcher and teacher working in the area of Deep Neural Networks, Fuzzy & Rough Sets, Computer Vision, and Medical Image Analysis.

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About

Avatharam Ganivada has received Ph.D. from Calcutta University, 2016, where the research work has been carried out at CSCR, Inidian Statistical Institute, during 2010-2015. He newly joined as Associate Professor at SCIS, University of Hyderabad in January 2026. He intially joined as an Assistant Professor, SCIS, UoH, Mar., 2017. He worked in ProKarma Soft. Pvt. Ltd., Hyderabad from Sep., 2015 to Feb., 2017. His research areas inlcude Deep Neural Networks, Fuzzy Rough Sets, Medical Image Analysis, Computer Vision, and Bioinformatics.

Quick Profile

  • Current Position: Associate Professor, SCIS, University of Hyderabad
  • Education: Ph.D. in Computer Science and Engineering from University of Calcutta/ Indian Statistical Institute
  • Experience: Teaching & research experience in academia and industry
  • Keywords: Deep Learning, Fuzzy / Rough Sets, Computer Vision, Bioinformatics

Research Interests

Deep Neural Networks Fuzzy & Rough Sets Medical Image Analysis Computer Vision Pattern Recognition Bioinformatics

Research Highlights

Selected areas where current projects and student theses are focused.

Medical Image Segmentation

Deep learning–based models for detection, segmentation and classification of structures in ultrasound and other medical imaging modalities.

Fuzzy Rough Learning

Kernel and granular neural approaches combining fuzzy rough sets with modern neural network architectures for robust learning.

Projects

Externally funded projects in the areas of fuzzy rough learning and mineral prospectivity.

IoE

Fuzzy Rough Kernel Based Extreme Learning Machine

Project sponsored by Institution of Eminence (IoE).

Approx. Funding: 15 Lakhs

SERB

Classification of New Mineral Prospectivity for Gold Resources

Project on harnessing gold resources using machine learning and deep convolutional neural networks.

Approx. Funding: 18 Lakhs, sponsored by SERB

For project collaboration enquiries →

Publications

A selection of recent journal and conference publications. Use the filters below to explore.

  1. 2026
    M. F. Dar, and A. Ganivada*, “Fuzzy rough set loss for deep learning-based precise medical image segmentation,” Computerized Medical Imaging and Graphics, vol. 128, pp. 102716, Feb., 2026 (IF: 4.9, elsevier).
  2. 2026
    A. Ganivada*, P. V. S. Raju, V. S. Mudili, “Gold Anomaly Classification Using Supervised Machine Learning Algorithms including a Novel Fuzzy Kernel based Extreme Learning Machine,” Geodata and AI, pp. 100057, Feb., 2026 (elsevier).
  3. 2025
    P. V. S. Raju, V. S. Mudili, and A. Ganivada,“A Hybrid Framework for Detecting Mineralization Zones in the G.R.Halli, Dharwar craton, Karnataka, India,” Minerals, vol.15, pp.1125, 2025 (IF: 2.2), MDPI.
  4. 2024
    M. F. Dar, and A. Ganivada*, "Deep Learning and Genetic Algorithm-based Ensemble Model for Feature Selection and Classification of Breast Ultrasound Images", Image and Vision Computing, vol.146, pp. 105018, 2024 (IF:4.7, elsevier)
  5. 2025
    M. F. Dar, and A. Ganivada, "Adaptive Ensemble Loss and Multi-Scale Attention in Breast Ultrasound Segmentation with UMA-Net", Medical & Biological Engineering & Computing, vol.63, pp. 1697--1713, 2025 (IF: 2.6) Springer).
  6. 2025
    S. Yara and A. Ganivada*, "A Modified Inter-Frame Difference Method for Detection of Moving Objects in Videos", International Journal of Information Technology, 2025 (Springer).
  7. 2023
    A. Ganivada* and S. Yara, "A Novel Deep Convolutional Encoder-Decoder Network: Application to Moving Object Detection in Videos", Neural Computing and Applications, vol. 35, no. 39, pp. 22027-22041, 2023 (IF:6.0, Springer)
  8. 2023
    M. F. Dar, and A. Ganivada*, "EfficientU-Net: A Novel Deep Learning Method for Breast Tumor Segmentation and Classification in Ultrasound Images", Neural Processing Letters, vol. 55, pp. 10439-10462, 2023 (IF:3.1, Springer).
  9. 2022
    A. Ganivada*, S. Ramanna, "Self-organizing map with granular competitive learning: Application to microarray clustering", Intell. Decis. Technology, vol. 16(3), pp. 505-521, 2022 (IF:1.2, IOS Press).
  10. 2022
    S. Ahmad, R. Pal, A. Ganivada, "Rank level fusion of multimodal biometrics using genetic algorithm", Multim. Tools and Applications, vol. 81, no. 28, pp. 40931-40958, 2022 (IF:3.6, Springer).
  11. 2016
    S. S. Ray, A. Ganivada and S. K. Pal, "A Granular Self-Organizing Map for Clustering and Gene Selection in Microarray data", IEEE Trans. Neural Networks and Learning Systems , vol. 27, no. 9, pp. 1890--1906, 2016 (IF:11.45, IEEE).
  12. 2013
    A. Ganivada*, S. S. Ray and S. K. Pal, "Fuzzy Rough Sets, New Granular Neural Networks for Unsupervised Feature Selection", Neural Networks, vol. 48, pp. 91--108, 2013 (IF:5.75, elsevier).
  13. 2012
    A. Ganivada*, S. S. Ray and S. K. Pal, "Fuzzy Rough Granular Self-Organizing Map and Fuzzy Rough Entropy", Theoretical Computer Science, vol. 466, pp. 37--63, 2012 (IF:1.2, elsevier).
  14. 2011
    A. Ganivada*, S. Dutta, and S. K. Pal, "Fuzzy Rough Granular Neural Networks, Fuzzy granules and Classification", Theoretical Computer Science, vol. 412, pp.5834--5853, 2011 (IF:1.2, elsevier).
  15. 2011
    A. Ganivada* and S. K. Pal, "A Novel Fuzzy Rough Granular Neural Network for Classification", International Journal in Computational Intelligence Systems, vol. 4, no. 5, pp.1042--1051, 2011 (IP:1.3, Atlantis press).
  16. 2024
    A. Ganivada, A. Negi and A. Prasad, "Facial Expression Recognition Using Ensemble Learning Approach", in Proceedings of Int'l Conference on Advanced Communications and Machine Intelligence, MICA, vol 405, Springer, 2024.
  17. 2023
    S. Ahmad, R. Pal, A.Ganivada, "Identifying a Person in Mask: Fusion of Masked Face and Iris", in 10th International Conference on PReMI, LNCS, Springer, 2023.
  18. 2023
    A. Ganivada, S. Mukhtar, "Type-II Fuzzy Kernel-Based Multi-layer Extreme Learning Machine", in Proceddings of 7th Int'l conf. on Soft Computing: Theories and Applications, LNNS, vol. 627, pp. 601-609, 2023.
  19. 2022
    S. Yara, A. Ganivada, "Detection of Moving Objects and Enhancement Using Motion Features in Various Video Sequences", in Innovations in Computer Science and Engineering, LNNS, vol. 385, 2022.
  20. 2022
    S. Ahmad, R. Pal, A.Ganivada, "Matching Score-Based Biometric Quality Estimation for Score and Rank Level Fusion for Person Identification", in Proceddings of ICVGIP, 1-56, 2022.
  21. 2021
    A.Ganivada, "Fuzzy Methodologies for Forecasting Usage and Wet-Bulb Data Variables", IEEE International Conference on Intelligent Systems, Smart and Green Technologies, pp. 6–10, 2021.
  22. 2021
    S. Ahmad, R. Pal, A. Ganivada, "Score Level Fusion of Multimodal Biometrics Using Genetic Algorithm", IEEE Congress on Evolutionary Computation, pp. 2242–2250, 2021.
  23. 2019
    A. Ganivada, "Generalized Fuzzy Rough Sets Based on New Fuzzy Similarity Relation", in Proceddings of 7th Int'l Conf. of SoCPaR, 1-9, 2019.

Students

Current and past supervision of Ph.D., M.Tech, and MCA students.

Doctoral Students (Ph.D.)

  • Shadab Ahamad: Degree awarded, 2024
  • Yara Srinivas: Degree awarded, 2025
  • Mohsin F. Dar: Thesis submitted, 2025

M.Tech Dissertations

  • Avinas Paidi (2019)
  • Venkatesh Chalumuri (2019)
  • Rachana Uniyal (2020)
  • Ashutosh Rane (2020)
  • Abilash Dash (2020)
  • Sushmitha Lakma (2021)
  • Krishna Shah (2021)
  • Ankit Prasad (2021)
  • V. Anvesh Raju (2022)
  • Ponagani Satish Kumar (2023)
  • Tawab Shinwari (2023)
  • Vishnu V. Reddy (2025)

MCA Students

  • Vishwajeet Verman(2026): Ongoing
  • Animikh Das(2026): Ongoing
  • Ujagare Budhabhushan Bhimrao(2026): Ongoing
  • Suraj Kr Mahto(2026): Ongoing
  • Saurabh Soni(2026): Ongoing

Teaching

Courses taught at SCIS, UoH in recent years.

Core Courses

  • Computer Based Numerical Methods and Statistics, and IT course for CIS students (July-Dec 2018)
  • Computer Based Numerical Methods and Statistics, (July-Dec 2019)
  • Data Structures and Programming, (Aug-Dec 2023)
  • Data and File Structures (Theory & Lab)

Advanced & Electives

  • Neural Networks, (Jan-May 2019)
  • Neural Networks and Object Oriented Analysis and Design (Theory & Lab), (Jan-May 2020 )
  • Computer Vision & Image Processing
  • Computer Graphics (shared with Dr. Anupama) and Pattern Recognition, (July- Dec 2020)
  • IT101 course for CIS students, (Jan-May 2021)

Recent Offerings

  • Image Processing, (2021, 2022)
  • IT Lab for CIS, (Jan-May 2024)
  • RMCS and RPE, (July-Dec2024)
  • Internet Technology & RPE, (Jan-Jun 2025)

Contact

For research collaboration, student supervision or academic queries.

Office

EB-201, New Building
School of Computer & Information Sciences
University of Hyderabad, Gachibowli
Hyderabad – 500 046, India

Reach

  • Phone: +91-40-2313 4105
  • Email (official): avatharg@uohyd.ac.in
  • Email (alt): avatharg@yahoo.co.in
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