RESEARCH INTERESTS

My research interests span the areas of deep learning, generative AI, computer vision, machine learning, medical image analysis and artificial intelligence.

In essence, my goal is to design efficient, scalable, and mathematically principled algorithms capable of analyzing, extracting, and generating information from diverse types of data, including natural images, video, and medical imaging.



EDITORIAL BOARD MEMBER

International Journal of Computer Vision
Computer Vision and Image Understanding Journal
Computational Intelligence Journal (Wiley)



LATEST NEWS

4 Papers Accepted at NeurIPS 2025
Boosting Generative Image Modeling via Joint Image-Feature Synthesis
X thread arXiv
DINO-Foresight: Looking into the Future with DINO
X thread arXiv
Multi-Token Prediction Needs Registers
X thread arXiv
ReplaceMe: Network Simplification via Depth Pruning and Transformer Block Linearization
GitHub arXiv
NeurIPS 2025 Spotlight Acceptance

Our work on Representation Diffusion (ReDi) has been accepted as a NeurIPS spotlight

ICML 2025 Acceptance
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
X thread arXiv
MICCAI 2025 Acceptance
Diffusing Boundaries: CBCT-to-CT Translation with Extended Field of View
Paper
CVPR 2025 Acceptance
Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers
X thread arXiv
Featured in Medical Image Analysis Journal (May 2025)
Our work on deep learning for detecting acute & sub-acute MS lesion activity from a single brain MRI - eliminating the need for follow-ups.
paper