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Bio: I am a co-founder and research scientist at a stealth startup. I can hopefully share more details soon. Previously, I was a Research Scientist at Adobe. Before that, I was a PhD student at MIT CSAIL, where I had the chance to work under the supervision of Prof. Frédo Durand. My research interests include computational photography, computer vision and machine learning. Prior to joining MIT, I completed my undergraduate studies in France, at École Polytechnique, with a focus on Applied Mathematics.

I have had the great privilege of mentoring and collaborating with wonderful students: Julien Philip, Dmitriy Smirnov, Utkarsh Singhal, Tamar Rott Shaham, Zhihao Xia, Spandan Madan, Ishit Mehta, Mustafa Işık, Pradyumna Reddy, James Hong, Karima Ma, Thibaut Ehret, Holly Jackson, Lucy Chai, Sai Praveen Bangaru, Difan Liu, Yash Belhe, Yotam Nitzan, Lucas Valença, Caroline Chan, Goutam Bhat, Prafull Sharma, Yinbo Chen, Ke Wang, Jiteng Mu, Tianwei Yin, Hadi AlZayer.

If you are looking for the economist, that would be my sister Sarah.



  • Improved Distribution Matching Distillation for Fast Image Synthesis
    Tianwei Yin, Michaël Gharbi, Taesung Park Richard Zhang, Eli Shechtman, Frédo Durand, William T. Freeman,
    arXiv 2024

  • One-step Diffusion with Distribution Matching Distillation
    Tianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Frédo Durand, William T. Freeman, Taesung Park
    CVPR 2024

  • Magic Fixup: Streamlining Photo Editing by Watching Dynamic Videos
    Hadi Alzayer, Zhihao Xia, Xuaner (Cecilia) Zhang, Eli Shechtman, Jia-Bin Huang, Michaël Gharbi
    arXiv 2024

  • Lazy Diffusion Transformer for Interactive Image Editing
    Yotam Nitzan, Zongze Wu, Richard Zhang, Eli Shechtman, Daniel Cohen-Or, Taesung Park, Michaël Gharbi
    arXiv 2024

  • Editable Image Elements for Controllable Synthesis
    Jiteng Mu, Michaël Gharbi, Richard Zhang, Eli Shechtman, Nuno Vasconcelos, Xiaolong Wang, Taesung Park
    arXiv 2024

  • Image Neural Field Diffusion Models
    Yinbo Chen, Oliver Wang, Richard Zhang, Eli Shechtman, Xiaolong Wang, Michaël Gharbi
    CVPR 2024

  • VecFusion: Vector Font Generation with Diffusion
    Vikas Thamizharasan, Difan Liu, Shantanu Agarwal, Matthew Fisher, Michaël Gharbi Oliver Wang, Alec Jacobson, Evangelos Kalogerakis
    CVPR 2024

  • Learning Subject-Aware Cropping by Outpainting Professional Photos
    James Hong, Lu Yuan, Michaël Gharbi, Matthew Fisher, Kayvon Fatahalian
    AAAI 2024

  • Discontinuity-Aware 2D Neural Fields
    Yash Belhe, Michaël Gharbi, Matthew Fisher, Iliyan Georgiev, Ravi Ramamoorthi, Tzu-Mao Li
    Siggraph Asia 2023

  • Shadow Harmonization for Realistic Compositing
    Luca Valença, Jinsong Zhang, Michaël Gharbi, Yannick Hold-Geoffroy, Jean-François Lalonde
    Siggraph Asia 2023

  • Self-Supervised Burst Super-Resolution
    Goutam Bhat, Michaël Gharbi, Jiawen Chen, Luc Van Gool, Zhihao Xia
    ICCV 2023

  • Materialistic: Selecting Similar Materials in Images
    Prafull Sharma, Julien Philip, Michaël Gharbi, William T. Freeman, Frédo Durand, Valentin Deschaintre
    Siggraph 2023

  • Domain Expansion of Image Generators
    Yotam Nitzan, Michaël Gharbi, Richard Zhang, Taesung Park, Jun-Yan Zhu, Daniel Cohen-Or, Eli Shechtman
    CVPR 2023

  • Semi-supervised Parametric Real-world Image Harmonization
    Ke Wang, Michaël Gharbi, He Zhang, Zhihao Xia, Eli Shechtman
    CVPR 2023

  • Differentiable Rendering of Neural SDFs through Reparameterization
    Sai Praveen Bangaru, Michaël Gharbi, Tzu-Mao Li, Fujun Luan, Kalyan Sunkavalli, Milos Hasan, Sai Bi, Zexiang Xu, Gilbert Bernstein, Frédo Durand
    Siggraph Asia 2022

  • Any-resolution Training for High-resolution Image Synthesis
    Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang
    ECCV 2022

  • Spotting Temporally Precise, Fine-Grained Events in Video
    James Hong, Haotian Zhang, Michaël Gharbi, Matthew Fisher, Kayvon Fatahalian
    ECCV 2022

  • Searching for Fast Demosaicking Algorithms
    Karima Ma, Michaël Gharbi, Andrew Adams, Shoaib Kamil, Tzu-Mao Li, Connelly Barnes, Jonathan Ragan-Kelley
    ToG (Siggraph 2022)

  • Free-viewpoint Indoor Neural Relighting from Multi-view Stereo
    Julien Philip, Sébastien Morgenthaler, Michaël Gharbi, George Drettakis
    ToG (Siggraph 2022)

  • Interactive Monte Carlo Denoising using Affinity of Neural Features
    Mustafa Işık, Krishna Mullia, Matthew Fisher, Jonathan Eisenmann, Michaël Gharbi
    Siggraph 2021

  • MarioNette: Self-Supervised Sprite Learning
    Dmitriy Smirnov, Michaël Gharbi, Matthew Fisher, Vitor Guizilini, Alexei A. Efros, Justin Solomon
    NeurIPS 2021

  • Modulated Periodic Activations for Generalizable Local Functional Representations
    Ishit Mehta, Michaël Gharbi, Connelly Barnes, Eli Shechtman, Ravi Ramamoorthi, Manmohan Chandraker
    ICCV 2021

  • Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
    James Hong, Matthew Fisher, Michaël Gharbi, Kayvon Fatahalian
    ICCV 2021

  • Im2Vec: Synthesizing Vector Graphics without Vector Supervision
    Pradyumna Reddy, Michaël Gharbi, Michal Lukáč, Niloy J. Mitra
    CVPR 2021

  • Spatially-Adaptive Pixelwise Networks for Fast Image Translation
    Tamar Rott Shaham, Michaël Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli
    CVPR 2021

  • Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments
    Zhihao Xia, Michaël Gharbi, Federico Perazzi, Kalyan Sunkavalli, Ayan Chakrabarti
    CVPR 2021

  • Differentiable Vector Graphics Rasterization for Editing and Learning
    Tzu-Mao Li, Michal Lukáč, Michaël Gharbi, Jonathan Ragan-Kelley
    Siggraph Asia 2020

  • Basis Prediction Networks for Effective Burst Denoising with Large Kernels
    Zhihao Xia, Federico Perazzi, Michaël Gharbi, Kalyan Sunkavalli, Ayan Chakrabarti
    CVPR 2020

  • A Dataset of Multi-Illumination Images in the Wild
    Lukas Murmann, Michaël Gharbi, Miika Aittala, Frédo Durand
    ICCV 2019

  • Sample-based Monte Carlo Denoising using a Kernel-Splatting Network
    Michaël Gharbi, Tzu-Mao Li, Miika Aittala, Jaakko Lehtinen, Frédo Durand
    Siggraph 2019

  • Multi-view Relighting using a Geometry-Aware Network
    Julien Philip, Michaël Gharbi, Tinghui Zhou, Alexei A. Efros, George Drettakis
    Siggraph 2019

  • Learning to Optimize Halide with Tree Search and Random Programs
    Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michaël Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Frédo Durand, Jonathan Ragan-Kelley
    Siggraph 2019

  • Learning Efficient Image Processing Pipelines
    Michaël Gharbi
    MIT PhD Thesis

  • Differentiable Programming for Image Processing and Deep Learning in Halide
    Tzu-Mao Li, Michaël Gharbi, Andrew Adams, Frédo Durand. Jonathan Ragan-Kelley,
    Siggraph 2018

  • Convolutional Neural Network for Earthquake Detection and Location
    Thibaut Perol, Michaël Gharbi, Marine Denolle
    Science Advances 2018

  • Deep Bilateral Learning for Real-Time Image Enhancement
    Michaël Gharbi, Jiawen Chen, Jonathan T. Barron, Samuel W. Hasinoff, Frédo Durand
    Siggraph 2017

  • Deep Joint Demosaicking and Denoising
    Michaël Gharbi, Gaurav Chaurasia, Sylvain Paris, Frédo Durand
    Siggraph Asia 2016

  • Transform Recipes for Efficient Cloud Photo Enhancement
    Michaël Gharbi, YiChang Shih, Gaurav Chaurasia, Jonathan Ragan-Kelley, Sylvain Paris, Frédo Durand
    Siggraph Asia 2015

  • A Gaussian Approximation of Feature Space for Fast Image Similarity
    Michaël Gharbi, Tomasz Malisiewicz, Sylvain Paris, Frédo Durand
    MIT Technical Report 2012