I am a PhD candidate at Stony Brook University, advised by
Dimitris Samaras.
My research revolves around the image priors encoded in deep generative denoising models, and their applications
to the digital histopathology and satellite image domains.
I also interned at Microsoft Research where with my mentor
Nebojsa Jojic
we worked on generative prior problems.
Fast constrained sampling in pre-trained diffusion models
NeurIPS 2025
Speeding up training-free inference with a simple approximation. We made a game that uses this algorithm to generate images with constraints in real-time [Gameplay 1 / Gameplay 2].
PixCell: A generative foundation model for digital histopathology images
Preprint
The first generative foundation model for digital histopathology images.
ZoomLDM: Latent Diffusion Model for multi-scale image generation
CVPR 2025
A multi-scale diffusion model to generate very large coherent histopathology images.
Learned representation-guided diffusion models for large-image generation
CVPR 2024
Self-supervised models provide patch annotations for diffusion models. We extrapolate from patches to synthesize large images.
Diffusion models as plug-and-play priors
NeurIPS 2022
Any inference task can use a diffusion model as an image prior. You can even solve the traveling salesman problem!
Eyes of the beholder: attention-guided metamers reveal divergent scene representations
Ritik Raina, Abe Leite, Alexandros Graikos, Seoyoung Ahn, Gregory J Zelinsky
CCN 2026
Poppy: Polarization-based Plug-and-Play Guidance for Enhancing Monocular Normal Estimation
Irene Kim, Sai Tanmay Reddy Chakkera, Alexandros Graikos, Dimitris Samaras, Akshat Dave
ECCV 2026 · Best paper honorable mention
Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning
Varun Belagali*, Srikar Yellapragada*, Alexandros Graikos,
Saarthak Kapse, Zilinghan Li, Tarak Nath Nandi, Ravi K Madduri,
Prateek Prasanna, Joel Saltz, Dimitris Samaras
DataCV Workshop @ CVPR 2026 · Best paper award
GriDiT: Factorized Grid-Based Diffusion for Efficient Long Image Sequence Generation
Snehal Singh Tomar, Alexandros Graikos, Arjun Krishna, Dimitris Samaras, Klaus Mueller
TMLR 2026
Structured image representation learning for flow-matching models
Alexandros Graikos, Kostas Triaridis, Esmeralda S. Whitammer, Dimitris Samaras
ICLR 2026 2nd Workshop on Deep Generative Model in Machine Learning: Theory, Principle and Efficacy
Generating metamers of human scene understanding
Ritik Raina, Abe Leite, Alexandros Graikos, Seoyoung Ahn,
Dimitris Samaras, Greg Zelinsky
ICLR 2026
Fast constrained sampling in pre-trained diffusion models
Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras
NeurIPS 2025
PixCell: A generative foundation model for digital histopathology images
Srikar Yellapragada*, Alexandros Graikos*, Zilinghan Li, Kostas Triaridis,
Varun Belagali, Tarak Nath Nandi, Karen Bai, Beatrice S. Knudsen, Tahsin Kurc,
Rajarsi R. Gupta, Prateek Prasanna, Ravi K Madduri, Joel Saltz, Dimitris Samaras
Preprint
Pathology Image Compression with Pre-trained Autoencoders
Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis, Zilinghan Li, Tarak Nath Nandi,
Ravi K Madduri, Prateek Prasanna, Joel Saltz, Dimitris Samaras
MICCAI 2025
PathSegDiff: Pathology Segmentation using Diffusion model representations
Sachin Kumar Danisetty, Alexandros Graikos, Srikar Yellapragada, Dimitris Samaras
5th Deep Generative Models Workshop @ MICCAI 2025
Seen2Scene: a generative model of fixation-by-fixation scene understanding
Ritik Raina, Abe Leite, Alexandros Graikos, Seoyoung Ahn, Greg Zelinsky
CCN 2025
ZoomLDM: Latent Diffusion Model for multi-scale image generation
Alexandros Graikos*, Srikar Yellapragada*, Kostas Triaridis,
Prateek Prasanna, Rajarsi R. Gupta, Joel Saltz, Dimitris Samaras
CVPR 2025