Liyue Shen
Assistant Professor, EECS – Electrical and Computer Engineering
Studies biomedical AI, including deep learning for medical image reconstruction and analysis and AI for precision health.
Liyue Shen's lab at Michigan works on medical imaging & healthcare AI, medical image analysis and 3D vision & neural rendering. 25 papers since 2023, 15 at top venues, mostly ICLR and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 60%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 4 papers2026 · T1 4 · collecting
- 8 papers2025 · T1 3
- 10 papers2024 · T1 7
- 3 papers2023 · T1 1
T1 venuesOtherVenues: ICLR, NeurIPS, ECCV, MICCAI, WACV
Research focuspaper titles that use each topic's words
- Medical image analysis9 papers
- 3D vision & neural rendering7 papers
- Medical imaging & healthcare AI5 papers
- image reconstruction1 paper
- precision health0 papers
Paper list
From DBLP.
20264 papers
- ICLR (T1)Antithetic Noise in Diffusion Models (opens in a new tab)
- KDD (T1)Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning (opens in a new tab)
- ECCV (T1)Evaluating and Understanding Model Editing for Medical Vision Language Models (opens in a new tab)
- CVPR (T1)Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement (opens in a new tab)
20258 papers
- NeurIPS (T1)CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation (opens in a new tab)
- Trans. Mach. Learn. Res.Distributionally Robust Alignment for Medical Federated Vision-Language Pre-training Under Data Heterogeneity (opens in a new tab)
- ICLR (T1)Dynamic Modeling of Patients, Modalities and Tasks via Multi-modal Multi-task Mixture of Experts (opens in a new tab)
- Trans. Mach. Learn. Res.Part-aware Prompted Segment Anything Model for Adaptive Segmentation (opens in a new tab)
- MICCAI (T1)Single-Spoke Motion-Compensated Dynamic 3D MRI Reconstruction via Neural Representation (opens in a new tab)
- Comput. Biol. MedicineST-NeRP: Spatial-temporal neural representation learning with prior embedding for patient-specific imaging study (opens in a new tab)
- WACVTempA-VLP: Temporal-Aware Vision-Language Pretraining for Longitudinal Exploration in Chest X-Ray Image (opens in a new tab)
- IEEE Trans. Computational ImagingTest-Time Adaptation Improves Inverse Problem Solving With Patch-Based Diffusion Models (opens in a new tab)
202410 papers
- IEEE Trans. Computational ImagingAccelerated Wirtinger Flow With Score-Based Image Priors for Holographic Phase Retrieval in Poisson-Gaussian Noise Conditions (opens in a new tab)
- IEEE Trans. Inf. Forensics Secur.AgrAmplifier: Defending Federated Learning Against Poisoning Attacks Through Local Update Amplification (opens in a new tab)
- ECCV (T1)CoSIGN: Few-Step Guidance of ConSIstency Model to Solve General INverse Problems (opens in a new tab)
- NeurIPS (T1)DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction (opens in a new tab)
- MICCAI (T1)Efficient In-Context Medical Segmentation with Meta-Driven Visual Prompt Selection (opens in a new tab)
- NeurIPS (T1)Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.NeRP: Implicit Neural Representation Learning With Prior Embedding for Sparsely Sampled Image Reconstruction (opens in a new tab)
- WWW (T1)Privacy-Preserving and Fairness-Aware Federated Learning for Critical Infrastructure Protection and Resilience (opens in a new tab)
- ICLR (T1)Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency (opens in a new tab)
- ICML (T1)The Emergence of Reproducibility and Consistency in Diffusion Models (opens in a new tab)
20233 papers
- WWW (T1)AgrEvader: Poisoning Membership Inference against Byzantine-robust Federated Learning (opens in a new tab)
- IEEE Trans. Medical ImagingLabel-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging (opens in a new tab)
- WACVPINER: Prior-informed Implicit Neural Representation Learning for Test-time Adaptation in Sparse-view CT Reconstruction (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to MichiganFall 2027
Michigan CSE Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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