Ya Zhang
教授
Works on AI and its applications in healthcare.
Ya Zhang's lab at SJTU works on medical imaging & healthcare AI. 109 papers since 2023, 78 at top venues, mostly CVPR and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 28/ year
- at T1 venues
- 72%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 18 papers2026 · T1 11 · collecting
- 18 papers2025 · T1 12
- 41 papers2024 · T1 32
- 32 papers2023 · T1 23
T1 venuesOtherVenues: CVPR, NeurIPS, ICLR, ICML, ICCV
Research focuspaper titles that use each topic's words
- Medical imaging & healthcare AI15 papers
- applications1 paper
- healthcare0 papers
- artificial intelligence0 papers
- artificial0 papers
Paper list
From the lab homepage.
202618 papers
- Nature Machine Intelligence (T1)A knowledge-driven framework for predicting single-cell responses for unprofiled drugs
- Communications MedicineAdvancing radiology foundation models with reasoning through step-by-step verification from daily reports
- Nature (T1)An agentic system for rare disease diagnosis with traceable reasoning (opens in a new tab)
- Nature Communications (T1)Boosting pathology foundation models via few-shot prompt-tuning for rare cancer subtyping
- Findings of ACLEliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach
- Cell Reports Medicine, 7Enhancing diagnosis of mild cognitive impairment through brain-heart-gut metabolic networks in whole-body PET imaging
- CVPR (T1)GenMask: Adapting DiT for Segmentation via Direct Mask Generation
- ICLR (Oral), acceptedImproving Diffusion Models for Class-imbalanced Training Data via Capacity Manipulation
- Cancer CellKnowledge-enhanced pretraining for vision-language pathology foundation model on cancer diagnosis
- TPAMI (T1)Lorkd: low-rank knowledge decomposition for medical foundation models
- AAAI (T1)MedS^3: Towards Medical Slow Thinking with Self-Evolved Soft Dual-sided Process Supervision
- ACL (T1)Miner: Mining Intrinsic Mastery for Data-Efficient RL in Large Reasoning Models
202518 papers
- ICLR (T1)Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection (opens in a new tab)
- ICML (T1)ConText: Driving In-context Learning for Text Removal and Segmentation
- Scientific Data 12 (1), 1636Development of a large-scale grounded vision language dataset for chest CT analysis (opens in a new tab)
- ICCV (T1)Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning
- IEEE Transactions on Neural Network and Learning Systems (TNNLS), 36(7):13527-13541Few-Shot Anomaly Detection via Category-Agnostic Registration Learning (opens in a new tab)
- ICLR (T1)Fine-tuning with Reserved Majority for Noise Reduction (opens in a new tab)
- NPJ Digital Medicine 8 (1), 566Large-vocabulary segmentation for medical images with text prompts (opens in a new tab)
- NeurIPS (T1)Learning to Instruct for Visual Instruction Tuning
- ICML (T1)MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
- ICCV (T1)MRGen: Segmentation Data Engine For Underrepresented MRI Modalities
- ACM MMMulti-agent system for comprehensive soccer understanding
- CVPR (T1)Multi-modal Medical Diagnosis via Large-small Model Collaboration
202441 papers
- CVPR (T1)Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical Images (opens in a new tab)
- WACVAnnotation-free Audio-Visual Segmentation (opens in a new tab)
- CVPR (T1)Audio-Visual Segmentation via Unlabeled Frame Exploitation (opens in a new tab)
- IEEE Transactions on Image Processing (TIP), 33: 4966-4981Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental Learning (opens in a new tab)
- Radiology: Artificial IntelligenceBoosting Deep Learning for Interpretable Brain MRI Lesion Detection through the Integration of Radiology Report Information (opens in a new tab)
- EMNLP (T1)CliMedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models in Clinical Scenarios
- Communications Medicine, 4, Article number: 277Development of a large-scale medical visual question-answering dataset (opens in a new tab)
- ACL (T1)DictLLM: Harnessing Key-Value Data Structures with Large Language Models for Enhanced Medical Diagnostics (opens in a new tab)
- ICML (T1)Diversified Batch Selection for Training Acceleration (opens in a new tab)
- ICLR (T1)Domain-Inspired Sharpness Aware Minimization Under Domain Shifts (opens in a new tab)
- ICML (T1)Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters (opens in a new tab)
- TMMFederated Adversarial Domain Hallucination for Privacy-preserving Domain Generalization (opens in a new tab)
202332 papers
- TMMAdaptive Mutual Supervision for Weakly-Supervised Temporal Action Localization (opens in a new tab)
- NeurIPS (T1)Asynchrony-Robust Collaborative Perception via Bird’s Eye View Flow (opens in a new tab)
- European Radiology, 33(7):5060-5068Benign vs malignant vertebral compression fractures with MRI: a comparison between automatic deep learning network and radiologist’s assessment (opens in a new tab)
- BMVCBoost Video Frame Interpolation via Motion Adaptation (opens in a new tab)
- CVPR (T1)Class-Balancing Diffusion Models (opens in a new tab)
- TPAMI (T1)Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting (opens in a new tab)
- NeurIPS (T1)Combating Representation Learning Disparity with Geometric Harmonization (opens in a new tab)
- TMLR (T1)Contrastive Attraction and Contrastive Repulsion for Representation Learning (opens in a new tab)
- CVPR (T1)Controllable Mesh Generation Through Sparse Latent Point Diffusion Models (opens in a new tab)
- CVPR (T1)Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization (opens in a new tab)
- CVPR (T1)DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration (opens in a new tab)
- CVPR (T1)Enhanced Multimodal Representation Learning with Cross-modal KD (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to SJTUFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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