Shayan Shekarforoush

I am a final year Computer Science PhD student at University of Toronto, supervised by David Fleet and Marcus Brubaker. I am also affiliated with Vector Institute and closely collaborate with David Lindell. Currently, I am a research intern at Ubisoft La Forge, Toronto working on relightable and controllable head avatar, supervised by Abdallah Dib.

I was a research intern at Samsung AI Center Toronto supervised by Alex Levinshtein, working on dual-camera image enhancement. I was also research intern at Technical University of Munich led by Nassir Navab, working on Geometric Deep Learning. I received my B.Sc. in Computer Engineering from Sharif University of Technology, Iran.

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Research Interest

In my thesis, I studied 3D Reconstruction of biomolecules using cryo-EM, a transformational scientific imaging technique. Specifially, I've worked on Neural Fields and Gaussian Splatting to model biological structures and their dynamics. Also, I've worked on 3D Pose Estimation for cryo-EM.

Selected Publications
cryospire Reconstructing Heterogeneous Biomolecules via Hierarchical Gaussian Mixtures and Part Discovery
Shayan Shekarforoush, David Lindell, Marcus Brubaker, David Fleet
arXiv / project page
semi-amortized CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
Shayan Shekarforoush, David Lindell, Marcus Brubaker, David Fleet
NeurIPS 2024
arXiv / project page / code / Oral (MLSB Workshop)
dual-camera Dual-Camera Joint Deblurring-Denoising
Shayan Shekarforoush, Aman Walia, Marcus Brubaker, Kosta Derpanis, Alex Levinshtein
arXiv / project page
resMFN Residual Multiplicative Filter Networks for Multiscale Reconstruction
Shayan Shekarforoush, David Lindell, David Fleet, Marcus Brubaker
NeurIPS 2022
arXiv / project page / code
physics_cryoem Physics aware inference for the cryo-EM inverse problem
Geoffrey Woollard, Shayan Shekarforoush, Frank Wood, Marcus Brubaker, Khanh Dao Duc
NeurIPS MLSB Workshop 2022
paper
miccai2019 Graph Convolution Based Attention Model for Personalized Disease Prediction
Anees Kazi, Shayan Shekarforoush, S.Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Benedict Wiestler, Karsten Kortum, Seyed-Ahmad Ahmadi, Shadi Albarqouni, Nassir Navab
MICCAI 2019
paper
incpetion InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
Anees Kazi, Shayan Shekarforoush, S.Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Karsten Kortuem, Seyed-Ahmad Ahmadi, Shadi Albarqouni, Nassir Navab
IPMI 2019 (Oral Presentation)
arXiv / code
Teaching Assistant

  • Intro to Machine Learning (Head TA) - Winter 2024
  • Introduction to Image Understanding - Fall and Winter 2023
  • Computational Imaging - Fall 2022, 2024, 2025
  • Academic Service

  • Reviewer: NeurIPS, ICLR, ICML, ICCV, WACV

  • Template adapted from Jon Barron.