I am a PhD student in Computer Science at UT Austin working with Prof. Kristen Grauman. Before this, I received my MS in Computer Science at UT. I am broadly interested in computer vision and machine learning. Currently, I am working on the application of embodied and active audio-visual learning to open problems in service robotics and AR/VR.

Previously, I have worked with Prof. Visvanathan Ramesh at Goethe University on continual and meta Learning for image recognition tasks. I have also had the pleasure of collaborating with Prof. Christoph Malsburg at the Frankfurt Institute for Advanced Studies for investigating visual models that draw motivation from Neuroscience.

Earlier, I graduated from BITS Pilani .

CV | E-Mail | Google Scholar | Github | Twitter

Active Audio-Visual Separation of Dynamic Sound Sources
Sagnik Majumder, Ziad Al-Halah, Kristen Grauman
arXiv 2022
paper | project

Move2Hear: Active Audio-Visual Source Separation
Sagnik Majumder, Ziad Al-Halah, Kristen Grauman
ICCV 2021
paper | project | code and data

Learning to Set Waypoints for Audio-Visual Navigation
Changan Chen, Sagnik Majumder, Ziad Al-Halah, Ruohan Gao, Santhosh K. Ramakrishnan, Kristen Grauman
ICLR 2021
paper | project | code

Model Agnostic Answer Reranking System for Adversarial Question Answering
Sagnik Majumder, Chinmoy Samant, Greg Durrett
EACL SRW 2021
paper

Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset
Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh
CVPR 2021
paper | code and data

Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh
arXiv 2019
paper | code

Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh
ICCV SDLCV Workshop 2019
paper | code

Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures
Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh
NeurIPS CRACT Workshop 2018
paper | code

Handwritten Digit Recognition by Elastic Matching
Sagnik Majumder, Christoph von der Malsburg, Aashish Richhariya, Surekha Bhanot
JCP 2018
paper | code

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