Neel Dey

  • Ph.D. Candidate


A picture of Neel Dey

I’m a Ph.D. candidate at New York University, advised by Guido Gerig. I’m part of the multi-disciplinary Visualization, Imaging, and Data Analysis (VIDA) Center at NYU which provides a wonderful environment for both research and not losing your mind in gradschool.

My research primarily focuses on geometric machine learning and computer vision applied to medical and biological images - a field that fortunately offers both fun technicality and real-world relevance.

Research Interests
Geometric Deep Learning, Computer Vision, Medical Image Analysis, Machine Learning, and Tensor Algebra

(please see for an updated list)

Dey, et al. "Generative Adversarial Registration for Improved Conditional Deformable Templates", ICCV 2021 (to appear).

Dey, et al. “Group Equivariant Generative Adversarial Networks", ICLR 2021.

Elaldi*, Dey*, et al. “Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data", IPMI, 2021 (* co-first authors).

Ren*, Dey*, et al. “Segmentation-Renormalized Deep Feature Modulation for Unpaired Image Harmonization", IEEE Transactions on Medical Imaging, 2021 (* co-first authors; Impact Factor: 6.68).

Ren, Kim, Dey, Gerig. "Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI", MICCAI 2021 (to appear).

Li, Dey, et al. “Point-supervised Segmentation of Microscopy Images and Volumes via Objectness Regularization", IEEE ISBI, 2021 (best paper award - 3rd place).

Dey, et al. “Robust Non-negative Tensor Factorization, Diffeomorphic Motion Correction, and Functional Statistics to Understand Fixation in Fluorescence Microscopy", MICCAI, 2019. (Early accept)

Dey, et al. "Tensor Decompositions for Hyperspectral Images of Autofluorescent Retinal Tissue", Medical Image Analysis, 2019. (Impact Factor: 11.15)

Gisbert, Dey, et al. “Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography", MICCAI OMIA Workshop, 2020.

Dey, et al. "Multi-modal Image Fusion for Multispectral Super-resolution in Microscopy", SPIE Medical Imaging, 2019. (Oral Presentation)


New York University 2017

Master of Science, Electrical Engineering

Research Centers, Labs, and Groups