About Me

I am a Ph.D. student in the Department of Electrical and Electronic Engineering at Imperial College London, supervised by Professor Pier Luigi Dragotti. My research focuses on computer vision, signal processing, and deep learning for inverse problems, with an emphasis on image restoration, diffusion models, and compressive sensing.

I received my bachelor's degree in electronic and information engineering from Dalian University of Technology in 2019 and my master's degree in computer applications technology from Peking University, Shenzhen, in 2022. During my master's studies, I was supervised by Professor Jian Zhang. I was awarded the President's Ph.D. Scholarship by Imperial College London.

News

Publications

You can also find my publications on Google Scholar.

  1. SING: Semantic Image Communications using Null-Space and INN-Guided Diffusion Models

    J. Chen*, S. F. Yilmaz*, D. You*, P. L. Dragotti, and D. Gündüz

    * Equal contribution (co-first authors).

    IEEE Transactions on Communications (Early Access), 2026.

    PaperarXiv Citation

  2. Frequency-Aware Perceptual Optimization for Low-Complexity Implicit Image Compression

    H. Wu, G. Li, D. You, P. L. Dragotti, and D. Gündüz

    International Conference on Machine Learning (ICML), 2026.

    PaperPDF Citation

  3. Lottery Prior: Randomized Neural Compression for Zero-Shot Inverse Problems

    H. Wu, D. You, P. L. Dragotti, and D. Gündüz

    International Conference on Machine Learning (ICML), 2026.

    PaperPDF Citation

  4. Realism and Fidelity: Two Sides of a Coin in Deep Joint Source-Channel Coding

    H. Wu, W. Wang, D. You, P. L. Dragotti, and D. Gündüz

    NeurIPS Workshop on AI and ML for Next-Generation Wireless Communications and Networking (AI4NextG), 2025.

    PaperPDF Citation

  5. INDIGO+: A Unified INN-Guided Probabilistic Diffusion Algorithm for Blind and Non-Blind Image Restoration

    D. You and P. L. Dragotti

    IEEE Journal of Selected Topics in Signal Processing, 2024.

    PaperCode Citation

  6. A Hallucination Metric and Correction Scheme for Diffusion-Based Image Restoration

    D. Siromani, D. You, and P. L. Dragotti

    IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2024.

    Paper Citation

  7. WiMANS: A Benchmark Dataset for WiFi-Based Multi-User Activity Sensing

    S. Huang, K. Li, D. You, Y. Chen, A. Lin, S. Liu, X. Li, and J. A. McCann

    European Conference on Computer Vision (ECCV), 2024.

    PaperPDFCode Citation

  8. CommIN: Semantic Image Communications as an Inverse Problem with INN-Guided Diffusion Models

    J. Chen*, D. You*, D. Gündüz, and P. L. Dragotti

    * Equal contribution (co-first authors).

    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

    Paper Citation

  9. INDigo: An INN-Guided Probabilistic Diffusion Algorithm for Inverse Problems

    D. You, A. Floros, and P. L. Dragotti

    IEEE International Workshop on Multimedia Signal Processing (MMSP), 2023.

    Best Paper Award

    PaperarXiv Citation

  10. ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

    D. You, J. Xie, and J. Zhang

    IEEE International Conference on Multimedia and Expo (ICME), 2021.

    PaperCode Citation

  11. COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

    D. You, J. Zhang, J. Xie, B. Chen, and S. Ma

    IEEE Transactions on Image Processing, 2021.

    PaperCode Citation

  12. AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

    D. You, F. Liu, S. Ge, X. Xie, J. Zhang, and X. Wu

    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021.

    Paper Citation