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Abhra Chaudhuri

PhD Student in Computer Science


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Short Bio:

I am supervised by Anjan Dutta and Zeynep Akata. I am also an Intern at the Fujitsu Research of Europe, working in the Autonomous Learning group on making vision transformers robust to distribution shifts for image segmentation problems.

The general area of my research is representation learning from multiple views. Although I primarily deal with problems from computer vision, I am open to collaboration in other domains as well. I aim to design algorithms that are interpretable, and preferably, theoretically sound.

My interests lie in the mathematical foundations of computer science - information theory, linear algebra, graph theory and combinatorics to name a few. I also picked up a curiosity for functional programming and distributed systems during my stint as a software engineer at Informatica.

  1. Abhra Chaudhuri, Ayan Kumar Bhunia, Yi-Zhe Song and Anjan Dutta. "Data-Free Sketch-Based Image Retrieval". In the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, June, 2023.
  2. Abhra Chaudhuri, Massimiliano Mancini, Zeynep Akata and Anjan Dutta. "Relational Proxies: Emergent Relationships as Fine-Grained Discriminators". In the Proceedings of Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2022 (Spotlight).
  3. Abhra Chaudhuri, Massimiliano Mancini, Yanbei Chen, Zeynep Akata and Anjan Dutta. "Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image Retrieval". In the Proceedings of British Machine Vision Conference (BMVC), London, UK, 2022.
  4. Abhra Chaudhuri, Palaiahnakote Shivakumara, Pinaki Nath Chowdhury, Umapada Pal, Tong Lu, Daniel Lopresti, G Hemantha Kumar. “A deep action-oriented video image classification system for text detection and recognition”. In Springer Nature Applied Sciences, 2021.