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Assistant professor |
I am an Assistant Professor in the Department of Computational and Data Sciences (CDS), Indian Institute of Science, Bangalore and the convenor of the Visual Computing Lab (VCL). From December’16 to June’17, I worked as a researcher at Robert Bosch Research and Technology Centre, India. Prior to that, I was a research fellow in the Rapid-Rich Object Search (ROSE) Lab at Nanyang Technological University, Singapore working on large scale, deployable video surveillance systems. From October’14 to November’15, I worked as a post-doctoral fellow in the A*STAR-NUS Clinical Imaging Research Centre at National University of Singapore. I completed my Ph.D. in Electrical Engineering from University of California, Riverside under the supervision of Dr. Amit K. Roy-Chowdhury in August, 2014. I obtained my M.S. from the same institute in 2010 and prior to that, my bachelors in Electrical Engineering from Jadavpur University, Kolkata, India.
[Google Scholar] [LinkedIn] [CV (available upon request)]
I am interested in developing novel computer vision and machine learning algorithms to solve visual analysis problems arising from diverse real-world applications. Majority of my current research can be categorized into three major thematic areas -
Data-efficient Deep Learning: zero-shot/few-shot knowledge distillation, continual learning, source-free/unsupervised domain adaptation, data-free adversarial defense, privacy-preserving ML etc.
Cross-modal Computer Vision: text-based image retrieval, sketch-guided localization, scene-graph generation, visual question answering etc.
Video Surveillance: robust and scalable person-reidentification, anomaly detection, human gait and pose analysis etc.
In the past, I have extensively worked on biological and medical image analysis problems (e.g., registration, cell segmentation, spatio-temporal cell tracking, cell and tissue resolution 3D reconstruction of confocal image stacks, analysis of clinical MR and CT images etc.). I am also interested in data-association problems on graphs and their applications to visual analytics tasks.
G. K. Nayak, M. K. Reddy, V. Shaj, R. Venkatesh Babu, A. Chakraborty, “Zero Shot Knowledge Distillation in Deep Networks”, International Conference on Machine Learning (ICML), 2019.
G. K. Nayak, M. K. Reddy, S. Jain, A. Chakraborty, “Mining Data Impressions from Deep Models as Substitute for the Unavailable Training Data”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021.
J. N. Kundu, S. Seth, V. Jampani, R. Mugalodi, R. V. Babu, A. Chakraborty, “Self- Supervised 3D Human Pose Estimation Via Part Guided Novel Image Synthesis”, Computer Vision and Pattern Recognition (CVPR), 2020.
A. Tripathi, R. R. Dani, A. Mishra, A. Chakraborty, “Sketch-Guided Object Localization in Natural Images”, European Conference on Computer Vision (ECCV), 2020.
A. Aggarwal, R. V. Babu, A. Chakraborty, “Text-based person search via attribute-aided matching”, Winter Conference on Applications of Computer Vision (WACV), 2020.
A. K. Singh, A. Mishra, S. Shekhar, A. Chakraborty, “From Strings to Things: Knowledge- enabled VQA Model that can Read and Reason”, International Conference on Computer Vision (ICCV), 2019.
A. Chakraborty, A. Das, A. K. Roy-Chowdhury, “Network Consistent Data Association”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2016.
A. Chakraborty, A. K. Roy-Chowdhury, “Context Aware Spatio-temporal Cell Tracking In Densely Packed Multilayer Tissues”, Medical Image Analysis, 2015.
A. Das, A. Chakraborty, A. K. Roy-Chowdhury,“Consistent Re-identification in a Camera Network”, European Conference on Computer Vision (ECCV), 2014.
For the complete list of publications, please see the Publication page.
Introduction to Data Science [DS 215] : Aug 2022
Data Analysis and Visualization [DS 294] : Jan 2022, Jan 2020, Jan 2018
Video Analytics [DS 263] : Aug 2021, Aug 2019 (co-taught with Prof. R. Venkatesh Babu)
Deep Learning for Computer Vision [DS 265] : Jan 2020 (co-taught with Prof. R. Venkatesh Babu)