I am a PhD student in Computer Science at UT Austin, advised by Prof. Kristen Grauman. Before this, I received my MS in Computer Science at UT. I am broadly interested in computer vision and machine learning. My current line of research is embodied audio-visual understanding of 3D scenes with applications in mobile 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.
Industrial research internships: I am looking for industrial research internships in audio-visual/multi-modal learning for Summer 2025. Kindly reach out if you think I would be a good fit.
Research collaborations: I am open to collaborating on research projects, and also mentoring Master's and final (senior) year students on their thesis. Shoot me an email to discuss more.
CV | E-Mail | Google Scholar | Github | Twitter
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BITS Pilani 2014-2018 |
FIAS Summer 2017 |
Goethe University 2018-2019 |
Meta AI 2022-present |
UT Austin 2019-present |
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ActiveRIR: Active Audio-Visual Exploration for Acoustic Environment Modeling
Arjun Somayazulu, Sagnik Majumder, Changan Chen, Kristen Grauman
IROS 2024 (Oral)
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Media coverage: TechXplore
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Learning Spatial Features from Audio-Visual Correspondence in Egocentric Videos
Sagnik Majumder, Ziad Al-Halah, Kristen Grauman
CVPR 2024
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Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani, ..., Sagnik Majumder, ..., Mike Zheng Shou, Michael Wray
CVPR 2024 (Oral)
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Chat2Map: Efficient Scene Mapping from Multi-Ego Conversations
Sagnik Majumder, Hao Jiang, Pierre Moulon, Ethan Henderson, Paul Calamia, Kristen Grauman*, Vamsi Krishna Ithapu*
*Equal contribution
CVPR 2023
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Retrospectives on the Embodied AI Workshop
Matt Deitke, Dhruv Batra, Yonatan Bisk, ..., Sagnik Majumder, ..., Luca Weihs, Jiajun Wu
arXiv
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Few-Shot Audio-Visual Learning of Environment Acoustics
Sagnik Majumder, Changan Chen*, Ziad Al-Halah*, Kristen Grauman
*Equal contribution
NeurIPS 2022
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Active Audio-Visual Separation of Dynamic Sound Sources
Sagnik Majumder, Kristen Grauman
ECCV 2022
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Move2Hear: Active Audio-Visual Source Separation
Sagnik Majumder, Ziad Al-Halah, Kristen Grauman
ICCV 2021
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Learning to Set Waypoints for Audio-Visual Navigation
Changan Chen, Sagnik Majumder, Ziad Al-Halah, Ruohan Gao, Santhosh K. Ramakrishnan, Kristen Grauman
ICLR 2021
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Model Agnostic Answer Reranking System for Adversarial Question Answering
Sagnik Majumder, Chinmoy Samant, Greg Durrett
EACL SRW 2021
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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
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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh
arXiv 2019
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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
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Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures
Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh
NeurIPS CRACT Workshop 2018
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Handwritten Digit Recognition by Elastic Matching
Sagnik Majumder, Christoph von der Malsburg, Aashish Richhariya, Surekha Bhanot
JCP 2018
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