About Me

I am a Ph.D. candidate in Control Science and Engineering at the Department of Automation, University of Science and Technology of China (USTC), advised by Prof. Tianzhu Zhang. I received my bachelor's degree from the Department of Electronic Engineering and Information Science at USTC in 2022 as a member of the Talent Program in Artificial Intelligence. I expect to graduate in 2027.

My research focuses on robust and trustworthy visual understanding across natural images, 3D point clouds, medical images, and vision-language models. I develop methods for fine-grained perception and multimodal reasoning under distribution shifts, with particular interests in domain adaptation and generalization, confidence calibration, semi-supervised learning, and efficient and reliable multimodal inference.

I am currently a research intern at Tencent Youtu Lab, working on fine-grained visual understanding and image-to-code capabilities for multimodal large language models.

Research Experience

Fine-Grained Visual Understanding Across Multiple Modalities (Natural Images / 3D Point Clouds / Medical Images)

Natural Images

  1. Towards Robust Pseudo-Label Learning in Semantic Segmentation: An Encoding PerspectiveNeurIPS 2025 · CCF A · Top-tier machine learning conference · First author · Domain adaptation
  2. Towards Unsupervised Domain Bridging via Image Degradation in Semantic SegmentationNeurIPS 2025 · CCF A · Top-tier machine learning conference · First author · Domain adaptation · Semi-supervised learning
  3. Balanced Learning for Domain Adaptive Semantic SegmentationICML 2025 · CCF A · Top-tier machine learning conference · First author · Domain adaptation
  4. DA-Cal: Towards Cross-Domain Calibration in Semantic SegmentationTIP 2026 · SCI Q1 · CCF A · Top-tier computer vision journal · First author · Cross-domain calibration
  5. Exploring Weather-Aware Aggregation and Adaptation for Semantic Segmentation Under Adverse ConditionsICCV 2025 · CCF A · Top-tier computer vision conference · Domain adaptation
  6. Towards Unbiased Learning in Semi-Supervised Semantic SegmentationICLR 2025 · CCF A · Top-tier machine learning conference · Semi-supervised learning
  7. Beyond Confidence: Exploiting Homogeneous Patterns for Semi-Supervised Semantic SegmentationICML 2025 · CCF A · Top-tier machine learning conference · Semi-supervised learning
  8. Two Losses, One Goal: Balancing Conflict Gradients for Semi-Supervised Semantic SegmentationICCV 2025 · CCF A · Highlight · Top-tier computer vision conference · Semi-supervised learning
  9. From Softmax to Dirichlet: Evidential Learning for Semi-Supervised Semantic SegmentationCVPR 2026 · CCF A · Top-tier computer vision conference · Semi-supervised learning
  10. Dual-Agent Optimization Framework for Cross-Domain Few-Shot SegmentationCVPR 2025 · CCF A · Top-tier computer vision conference · Few-shot learning

3D Point Clouds

  1. Adaptive Augmentation-Aware Latent Learning for Robust LiDAR Semantic SegmentationICLR 2026 · CCF A · Top-tier machine learning conference · First author · Domain generalization
  2. BeyondMix: Leveraging Structural Priors and Long-Range Dependencies for Domain-Invariant LiDAR SegmentationNeurIPS 2025 · CCF A · Top-tier machine learning conference · Domain adaptation
  3. DA2-LiDAR: A Generic Density-Adaptive Framework for Unsupervised Domain Adaptation in LiDAR SegmentationTIP · SCI Q1 · CCF A · Top-tier computer vision journal · Domain adaptation
  4. Localization and Expansion: A Decoupled Framework for Point Cloud Few-Shot Semantic SegmentationECCV 2024 · Top-tier computer vision conference · Few-shot learning
  5. Generalized Few-Shot Point Cloud Segmentation via LLM-Assisted Hyper-Relation MatchingICCV 2025 · CCF A · Top-tier computer vision conference · Few-shot learning

Medical and Biological Images

  1. MAUNet: Modality-Aware Anti-Ambiguity U-Net for Multi-Modality Cell SegmentationNeurIPS Competition Track 2022 · CCF A Workshop · First author · Domain generalization · Semi-supervised learning
  2. Enhancing Cell Detection in Histopathology Images: A ViT-Based U-Net ApproachMICCAI Workshop 2023 · Top-tier medical imaging conference workshop · Cell detection
  3. SAM-Glomeruli: Enhanced Segment Anything Model for Precise Glomeruli SegmentationMICCAI Workshop 2024 · Top-tier medical imaging conference workshop · Glomeruli segmentation
  4. Alleviate and Mining: Rethinking Unsupervised Domain Adaptation for Mitochondria Segmentation from a Pseudo-Label PerspectiveAAAI 2025 · CCF A · Top-tier artificial intelligence conference · Domain adaptation

Multimodal Understanding, Alignment, and Efficient Inference for Vision-Language Models

  1. Cycle-Consistent Test-Time Adaptation for Reasoning SegmentationEMNLP 2026 · Under review · Top-tier natural language processing conference · First author · Reasoning segmentation · Multimodal adaptation
  2. Principled Semantic Representation Optimization for Text-Assisted Image ClusteringNeurIPS 2026 · CCF A · Under review · Top-tier machine learning conference · Co-first author · Multimodal alignment · Image clustering
  3. Spectral Heat Flow for Conservative Token Condensation in Vision-Language ModelsICML 2026 · CCF A · Top-tier machine learning conference · Visual token condensation · Efficient inference
  4. Beyond Logits: Coherent Hallucination Mitigation via Attention Contrastive DecodingICML 2026 · CCF A · Top-tier machine learning conference · Hallucination mitigation · Contrastive decoding
  5. Beyond Blind Noising: Disentangled Visual Rectification for Hallucination Mitigation in MLLMsICML 2026 · CCF A · Top-tier machine learning conference · Hallucination mitigation · Visual rectification

Selected Publications

  • Wangkai Li, Rui Sun, Zhaoyang Li, Yujia Chen, Tianzhu Zhang. “DA-Cal: Towards Cross-Domain Calibration in Semantic Segmentation.” IEEE Transactions on Image Processing (TIP), 2026.
    Jun. 2026
  • Wangkai Li, Zhaoyang Li, Yuwen Pan, Rui Sun, Yujia Chen, Tianzhu Zhang. “Adaptive Augmentation-Aware Latent Learning for Robust LiDAR Semantic Segmentation.” International Conference on Learning Representations (ICLR), 2026.
  • Wangkai Li, Rui Sun, Zhaoyang Li, Tianzhu Zhang. “Towards Robust Pseudo-Label Learning in Semantic Segmentation: An Encoding Perspective.” Conference on Neural Information Processing Systems (NeurIPS), 2025.
  • Wangkai Li, Rui Sun, Huayu Mai, Tianzhu Zhang. “Towards Unsupervised Domain Bridging via Image Degradation in Semantic Segmentation.” Conference on Neural Information Processing Systems (NeurIPS), 2025.
  • Wangkai Li, Rui Sun, Bohao Liao, Zhaoyang Li, Tianzhu Zhang. “Balanced Learning for Domain Adaptive Semantic Segmentation.” International Conference on Machine Learning (ICML), 2025.

Academic Competitions

  • 1st Place, WSI-Level Glomeruli Detection in Kidney Pathology Image Segmentation Challenge (MICCAI 2024)
  • 2nd Place, NTIRE Efficient Super-Resolution Challenge (CVPR 2024)
    Jun. 2024
  • Second Prize (3rd Place; CNY 200,000), Video Interpolation in Fast-Motion Scenes, 2nd Guangdong-Hong Kong-Macao Greater Bay Area Algorithm Case Competition
  • 1st Place, Cell Detection from Cell-Tissue Interaction Challenge (MICCAI 2023)
  • Spotlight Tracker, Best Robustness, Visual Object Tracking and Segmentation Challenge (ICCV 2023)
    Oct. 2023
  • Meritorious Winner, Rank: 4/102, Weakly Supervised Cell Segmentation in Multimodal High-Resolution Microscopy Images Challenge (NeurIPS 2022)
  • 1st Place, Visual Object Tracking Short-Term Bounding-Box Challenge (ECCV 2022)

Awards

  • Jianghuai NIO Scholarship, USTC 2025
  • First-Class Graduate Scholarship, USTC (awarded five times) 2022–2026
  • First-Class Scholarship, Talent Program in Artificial Intelligence, USTC 2021
  • First Prize, 12th Chinese Mathematics Competition (Non-Mathematics Major) Oct. 2020
  • Outstanding Undergraduate Scholarship, Silver Award, USTC (awarded three times) 2019–2021

Professional Service

Reviewer for TPAMI, TMM, CVPR (2024–2026), AAAI (2025–2026), ICLR (2025–2026), ICCV 2025, ICML 2026, ECCV 2026, and NeurIPS 2026.

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