I am a Machine Learning Researcher, a native of Assam (অসম), India. A few of my professional links:
Google Scholar LinkedIn dblp CSAuthorsNet GitHub Other Website (not actively maintained)
My ERDOS PATH reads as:
Ujjal Kr Dutta -> Mehrtash Harandi -> Richard Hartley -> Marc Kilgour -> Peter C. Fishburn -> Paul Erdos.
" Research is to see what everybody else has seen, and to think what nobody else has thought".
You and Your Research ( - by Richard Hamming, 1986)
Word-cloud generated from my PhD paper abstracts.
List of my research publications can be found here.
Broad Research Agenda:
Advance efficient and generalizable machine learning methods that require less human supervision, adapt incrementally, and transfer knowledge across domains.
Focus area: Fundamental/basic and applied ML research (for solving real-world problems).
Research Topics I have worked on:
Representation & Metric Learning: Advanced methods for learning robust, transferable representations, including manifold learning, graph-based learning, adversarial learning, and Riemannian optimization.
Domain Generalization & Transfer Learning: Developed domain-invariant models for vision tasks, enabling robust performance across unseen data distributions.
Semi-/Unsupervised & Continual Learning: Pioneered techniques for learning from limited labels, and for incremental adaptation—crucial for lifelong AI agents.
Applied Computer Vision and Machine Learning: Led projects on object detection, segmentation, pose estimation, 3D vision, virtual try-on, satellite imagery based Earth Observation (EO), time-series and sequential modeling for sensor data, recommender systems, multi-armed and contextual bandits.
Generative Models & Diffusion: Explored GAN, VAE, Stable Diffusion, and neural fields for content generation and augmentation.
Model Compression & Knowledge Distillation: Designed efficient, low-latency models for edge deployment.
Physics-Informed ML: Integrated domain knowledge into neural models for scientific and industrial applications.
Program Committee Member / Reviewer for
International Conferences:
International Conference on Learning Representations (ICLR) 2025
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022, 2023
International Conference on Computer Vision (ICCV) 2023
European Conference on Computer Vision (ECCV) 2022, 2024
Neural Information Processing Systems (NeurIPS) 2024
AAAI Conference on Artificial Intelligence (AAAI) 2021 , 2022
Winter Conference on Applications of Computer Vision (WACV) 2021
Manifold Learning from Euclid to Riemann (Manlearn) workshop at International Conference on Pattern Recognition ( ICPR ) 2020/21
AISTATS 2021 (invited), 2023, 2024
International Journals: ( publons profile )
Apart from research, I am an athlete in the following sports: Olympic-style Weightlifting, Powerlifting and Mixed Martial Arts (MMA)/ Muay Thai. Till my undergrad, I also used to play soccer (mid-field), which I discontinued eventually to focus on strength and combat sports. During undergrad, I competed in my first set of Weightlifting and Powerlifting competitions where I got bronze and silver medals.
During my stay in the PhD programme, I got a lot of opportunities to participate, and win, in many of the competitions involving these sports. In particular, I was 4 times Strongman (2015, 2017, 2018, 2019) in IITM Powerlifting (for lifting the highest weight per pound of body weight. I have lifted 190kg deadlift, as my personal best), 1 time silver medalist representing IITM at Chennai district level Olympic-style Weightlifting competition (2015), and 1 time silver medalist at the national level Inter-IIT Tournament in Olympic-style Weightlifting (2017).
Have a look here.