Mengwei Ren
I am a Ph.D. candidate at the NYU Visualization and Data Analytics Research (VIDA) Center ,
supervised by Prof. Guido Gerig. I have been fortunate to intern at Adobe,
Google Research, and Siemens Healthineers.
My research broadly lies at the intersection of computer vision , deep learning, and biomedical image analysis.
Particularly, I am interested in generative models, representation learning and spatiotemporal analysis.
I will graduate in Spring 2024 and I am actively seeking a full-time opportunity in the field of generative AI. Happy to connect :-)
Email  / 
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09-2023 |
Our work on keypoint augmented self-supervised learning has been accepted to NeurIPS2023. |
07-2023 |
Our work on structure guided diffusion model for deblurring has been accepted to ICCV2023. |
07-2023 |
Our work on data synthesis for microscopy segmentation has been accepted to MICCAI DALI. |
05-2023 |
Starting my internship at Adobe. |
10-2022 |
I received a Scholar Award from NeurIPS2022. |
09-2022 |
Our work on spatiotemporal representation learning has been accepted to NeurIPS2022 (oral). |
08-2022 |
I gave a talk on my PhD research on image-to-image translation at Luma seminar, Google Research. |
07-2022 |
I gave an invited presentation on longitudinal neuroimage analysis at Stanford Research Institute & Computational Neuroimage Science Laboratory. Milestone: my first in-person talk :p |
06-2022 |
Starting my internship at Computational Imaging (LUMA) Team, Google Research.
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04-2022 |
Guest lecture on "Deep Learning for Computer Vision" for NYU Tandon CS-GY 6643 Computer Vision.
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07-2021 |
Our work on spatiotemporal brain atlas synthesis has been accepted to ICCV2021.
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06-2021 |
Our work on diffusion-weighted brain image synthesis has been accepted to MICCAI2021 (oral). |
05-2021 |
Starting a Machine Learning research internship @Siemens Healthineer.
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04-2021 |
Guest lecture on "Deep generative models (w/ a focus on VAE/GANs)" for NYU Tandon CS-GY 6643 Computer Vision. |
02-2021 |
My first journal paper was accepted by IEEE Transactions on Medical Imaging! |
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Multiscale Structure Guided Diffusion for Image Deblurring
Mengwei Ren, Mauricio Delbracio, Hossein Talebi, Guido Gerig, Peyman Milanfar.
ICCV, 2023
arXiv,
bibtex
Image-conditioned Diffusion Probablistic Models (icDPMs) for restoration work well on benchmarks but not real images. We introduce a simple yet effective structure guidance that leads to significantly better visual quality on unseen images.
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