Chenyu You
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Chenyu You
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Introduction
I am a fourth year Ph.D. candidate in the Department of Electrical Engineering, Yale University, where I am very fortunately advised by Prof. James S. Duncan. I obtained a Master degree in Electrical Engineering from Stanford University in 2019, specializing in Artificial Intelligence (AI). While at Stanford, I have been fortunate to work with Prof. Daniel Rubin over various projects in Laboratory of Quantitative Imaging and Artificial Intelligence. Prior to that, I received my bachelor degree (with honors) in Electrical Engineering and Mathematics from Rensselaer Polytechnic Institute (RPI) in 2017. In RPI, I have worked on signal processing and machine learning under the supervision of Prof. Ge Wang. Previously, I was a Research Intern at Facebook AI Research (FAIR), New York, in summer 2022. I was a Student Researcher at Google Research, Mountain View.
My research interests are broadly in the area of machine learning theory and algorithms intersecting the fields of computer & medical vision, natural language processing, signal processing, and distributed systems.
News
[2023.02] Our paper “Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation” has been accepted at IPMI 2023.
[2023.02] One paper accepted at IPMI 2023.
[2023.01] One paper accepted at Medical Physics.
[2022.10] One paper accepted at WACV 2023.
[2022.09] Our new preprint “Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels” is online on Arxiv.
[2022.09] Our paper “Class-Aware Generative Adversarial Transformers for Medical Image Segmentation” has been accepted at NeurIPS 2022!
[2022.09] Two papers accepted at NeurIPS 2022!
[2022.09] Our new preprint “Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation” is online on Arxiv.
[2022.08] Gave a talk at Meta AI Research (FAIR) Eestcoast Vision Group about Contrastive Learning.
[2022.08] Very honored to be recognized as IEEE Transactions on Medical Imaging (TMI) Platinum Distinguished Reviewer.
[2022.08] One paper accepted at WACV 2023.
[2022.07] One paper accepted at MICCAI-STACOM 2022.
[2022.07] One paper accepted at MICCAI-DeCaF 2022.
[2022.07] One paper accepted at MICCAI-DGM4MICCAI 2022.
[2022.06] Two papers accepted at MICCAI 2022.
[2022.05] One paper accepted at KDD 2022 (Oral).
[2022.05] One paper early accepted at MICCAI 2022!
[2022.04] One paper accepted at NAACL 2022.
[2022.03] Our paper “SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation” has been formally accepted by IEEE Transactions on Medical Imaging (IEEE-TMI) (Impact Factor: 10.048).
[2022.03] I will be interning at Facebook AI Research (FAIR), New York, starting from June 2022.
[2022.03] One paper accepted at ICLR-PAIR2Struct 2022.
[2022.02] Very proud to be recognized as a Distinguished Referee for Medical Physics.
[2022.01] Our new preprint “Class-Aware Generative Adversarial Transformers for Medical Image Segmentation” is online on Arxiv.
[2021.12] Awarded 2021 - 2022 Yale Fellowship.
[2021.12] One paper accepted at AAAI 2022.
[2021.11] One paper has been formally accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI) (Impact Factor 17.861).
[2021.10] One paper accepted at WACV 2022.
[2021.09] One paper accepted at NeurIPS 2021.
[2021.08] One paper accepted at EMNLP 2021.
[2021.06] Three papers accepted at Interspeech 2021.
[2021.05] Glad to be recognized as CVPR 2021 outstanding reviewer.
[2021.04] One paper accepted at IJCAI 2021 (Acceptance Rate: 13.9%).
[2021.03] Very proud to be recognized as Medical Physics Journal Distinguished Reviewer.
[2021.02] Very honored to be recognized as IEEE Transactions on Medical Imaging (TMI) Distinguished Reviewer.
[2021.01] Two papers accepted at IEEE-ICASSP 2021.
[2021.01] One paper accepted at ICLR 2021 (Spotlight).
[2020.11] Awarded 2020 - 2021 Yale Fellowship.
[2020.10] Proud to be an Outstanding Reviewer for MICCAI 2020.
[2020.09] We have released all the training/testing code and pretrained models for NuSeT, a high quality Tool box for Cell Segmentation and Analysis.
[2020.08] One paper accepted at MICCAI-MIL3ID 2020.
[2020.07] One paper accepted at PLOS Computational Biology.
[2019.10] Awarded 2019 - 2020 Yale Fellowship.
[2019.09] Three full papers accepted at Proceedings of SPIE.
[2019.07] We have released all the training/testing code for GAN-CIRCLE (IEEE-TMI 2020) at Github.
[2019.06] Our paper “Recovery of Latent Vectors and Exploration of Latent Space from StyleGAN” received the Stanford CS230 Final Project Prize, mentored by Prof. Andrew Ng.
[2019.06] Our paper “CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)” has been formally accepted by IEEE Transactions on Medical Imaging (IEEE-TMI) (Impact Factor: 10.048).
[2019.01] One papers accepted at Medical Physics.
Contact
Email: chenyu.you [AT] yale [DOT] edu
Address: 300 Cedar Street, New Haven, CT 06520-8042