Institute Professor (Superannuated), DA-IICT • Dhirubhai Ambani University
40+ years in Computer Vision, Machine Learning & Signal Processing • IIT Bombay PhD
Four decades at the forefront of visual intelligence
Prof. Manjunath V. Joshi is a distinguished researcher and educator with over four decades of contributions to computer vision, machine learning, and signal processing. He served at DA-IICT (now Dhirubhai Ambani University, Gandhinagar) from 2005, where he was Professor since 2008 and Dean of Research & Development from 2020 to 2023, before superannuation on September 30, 2026.
His foundational work in learning-based super-resolution, multi-resolution image fusion, and hyperspectral unmixing has been widely cited. His current research frontiers include Quantum Machine Learning for Computer Vision, Generative AI and Diffusion Models, Adversarial Robustness, and AI for Remote Sensing and Plasma Physics.
Prof. Joshi began his academic career in 1985 at Gogte Institute of Technology, Belgaum, and subsequently joined IIT Bombay where his doctoral dissertation on Motion-Free Super-resolution Imaging earned the Infineon India Best PhD Thesis Award (2005) and the Outstanding Researcher Award (2004). He is the recipient of the Dr. Vikram Sarabhai Award in Information Technology from the Government of Gujarat (2006–07).
He has supervised 9 PhD scholars and 35+ MTech theses, co-authored 6 monographs, and has trained scientists at ISRO. He has held visiting research positions in Trento (Italy), Strasbourg (France), and Erlangen (Germany), and has taught at IIT Gandhinagar and IIIT Vadodara.
Bridging classical vision and quantum-era intelligence
Visiting research stays and international collaborations
Six books with leading international publishers
Motion-Free Super-Resolution
Springer, 2005
Multi-resolution Image Fusion in Remote Sensing
Cambridge University Press, 2019
Regularization in Hyperspectral Unmixing
SPIE Press, 2016
Digital Heritage Reconstruction Using Super-resolution and Inpainting
Morgan & Claypool, 2016
Unmixing Approaches in Hyperspectral Remote Sensing
CRC Press (Accepted)
Spectrum Sensing for Cognitive Radio: Fundamentals and Applications
CRC Press, 2021
Metrics as of October 2026
Full publication list available on Google Scholar. Funded projects include grants from DST, ISRO, BRNS, and NVIDIA hardware grants.
Recent and representative works — full list on Google Scholar
Not All Is Lost: Repairing Lossy User Preference States of Personalization Encoders
Advances in Neural Information Processing Systems (NeurIPS 2026) • Sydney, Australia, Dec 6–12, 2026
arXiv: 2610.01270
Bloch-Wasserstein Generative Adversarial Network for Quantum State Learning
IEEE International Conference on Quantum Computing & Engineering (QCE 2026) • Toronto, Canada, September 2026
Quantum Reservoir Computing with Temporal Convolutional Readout for Optical Equalization and Forecasting
IEEE International Conference on Quantum Computing & Engineering (QCE 2026) • Toronto, Canada, September 2026
Soft-QUBO Based Global Optimization of Non-Maximum Suppression via QAOA for Crowded Pedestrian Detection
Conference on Computer Vision and Image Processing (CVIP 2026) • NIT Calicut, Dec 9–12, 2026 • Springer LNCS
Quantum Single-Image Super Resolution
Quantum Information Processing, Springer Nature, vol. 25, 2026
A Data-Driven Reduced-Order Model for Plasma Density Estimation in a High-Power RF Ion Source
Journal of Instrumentation, Apr. 2026
Transformer-Based Framework Using In-House Sensors and Lightweight Images for Accurate Plant Disease Classification
IEEE Sensors Journal, vol. 26, no. 7, Apr. 2026
Hybrid and Parallel GAN Architecture with Non-IID Noise Input
The Journal of Supercomputing, Springer Nature, Jun. 2025
Data-Driven Soft Sensor for Optical Intensity Estimation in High-Power Plasma Source
IEEE Sensors Journal, vol. 25, Jul. 2025
Assessment of Autoencoders for Signal Reconstruction in High-Power Negative Ion-Based Plasma Sources
Journal of Instrumentation, vol. 10, pp. 5359–5368, Oct. 2025
Multimodal Data Fusion by Integrating IoT-Enabled Sensors and Images for Jamun Crop Disease Detection With Machine Learning
IEEE Transactions on AgriFood Electronics, vol. 3, no. 2, Sep.–Oct. 2025
Matching Parameter Estimation for High-Power Inductively Coupled Plasma Sources Using Machine Learning Techniques
Fusion Engineering and Design, vol. 208, Elsevier, Nov. 2024
New Learning Based Super-Resolution: Use of DWT and IGMRF Prior
IEEE Transactions on Image Processing, vol. 19, no. 5, pp. 1201–1213, 2010
An Edge Preserving Multiresolution Fusion: Use of Contourlet Transform and MRF Prior
IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 6, pp. 3210–3220, 2014
Auto-Inpainting Heritage Scenes: A Complete Framework for Detecting and Infilling Cracks in Images and Videos
Machine Vision and Applications, vol. 26, no. 2–3, pp. 317–337, 2015
A Model-Based Approach to Multiresolution Fusion in Remotely Sensed Images
IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 9, pp. 2549–2562, 2006
Multi-Objective Super-resolution: Concepts and Examples
IEEE Signal Processing Magazine, vol. 20, no. 3, pp. 49–61, 2003
🔗 Complete list of 36+ journal and 82+ conference papers: Google Scholar Profile
Supervised 9 PhD scholars; 5 currently guiding
Recognition for research excellence and teaching
Courses taught across undergraduate, postgraduate, and industry programmes
Open to research collaboration, PhD guidance, and academic engagement
Prof. Joshi welcomes collaboration in quantum machine learning, generative AI for vision, adversarial robustness, and remote sensing. Prospective PhD students with strong backgrounds in mathematics, signal processing, or quantum computing are encouraged to reach out.