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.

Email / CV / Google Scholar / Twitter / Github / LinkedIn

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
	Reconstructing Heterogeneous Biomolecules via Hierarchical Gaussian Mixtures and Part Discovery Shayan Shekarforoush, David Lindell, Marcus Brubaker, David Fleet arXiv / project page
	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 Joint Deblurring-Denoising Shayan Shekarforoush, Aman Walia, Marcus Brubaker, Kosta Derpanis, Alex Levinshtein arXiv / project page
	Residual Multiplicative Filter Networks for Multiscale Reconstruction Shayan Shekarforoush, David Lindell, David Fleet, Marcus Brubaker NeurIPS 2022 arXiv / project page / code
	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
	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
	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.