Aditya Panda

I am currently a final year doctoral student at Indian Statistical Institute. During the last few years, I mainly worked on data efficient deep learning approaches. Specifically I explored the different aspects of the problem Compositional Zero-Shot Learning (CZSL). Compositional Zero-Shot Learning, focusses on recognizing new state-object compositions from limited training data. We worked on approaches using graph convolutional networks, and transformer networks to tackle challenges in the closed-world, open-world, and partially supervised CZSL problems. Before my PhD, I completed my M. Tech degree in Computer Science from ISI, Kolkata. Prior to that I pursued my undergraduate studies in Electronics and Tele-Communication Engineering from Jadavpur University, Kolkata.

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Publication List

b3do Compositional Zero-Shot Learning using Multi-Branch Graph Convolution and Cross-layer Knowledge Sharing
Aditya Panda, Dipti Prasad Mukherjee
Pattern Recognition, 2024
Link/ bibtex
Isolating Features of Object and Its State for Compositional Zero-Shot Learning
Aditya Panda, Bikash Santra, Dipti Prasad Mukherjee
IEEE Transactions on Emerging Topics in Computational Intelligence, 2023
Link/ bibtex
Bi-Modal Compositional Network for Feature Disentanglement
Aditya Panda, Bikash Santra, Dipti Prasad Mukherjee
IEEE International Conference on Image Processing (ICIP), 2022
Link/ bibtex
Monocular 3D human pose estimation by multiple hypothesis prediction and joint angle supervision
Aditya Panda, Dipti Prasad Mukherjee
IEEE International Conference on Image Processing (ICIP), 2021
Link/ bibtex
Particle swarm optimization with a modified learning strategy and blending crossover
Aditya Panda, Rammohan Mallipeddi, Swagatam Das,
IEEE Symposium Series on Computational Intelligence (SSCI), 2017
Link/ bibtex
Static learning particle swarm optimization with enhanced exploration and exploitation using adaptive swarm size
Aditya Panda, Srijan Ghoshal, Amit Konar, Bonny Banerjee, Atulya K Nagar,
IEEE Congress on Evolutionary Computation (CEC), 2016
Link/ bibtex

Under Review Manuscripts

Partially Supervised Compositional Zero-Shot Learning by Locality Preserving Neighbourhood Aggregation
Aditya Panda, Dipti Prasad Mukherjee
communicated to an IEEE Transaction
Prompt-Driven Multi-Branch Disentanglement Network for Compositional Zero-Shot Learning
Aditya Panda, Dipti Prasad Mukherjee
communicated to an IEEE Transaction

Academic Services


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