Yawei Li
Nanyang Assistant Professor
Works on AI efficiency, TinyML and hardware-software co-design for vision models.
Yawei Li's lab at NTU works on accelerators, chips & architecture. 34 papers since 2023, 18 at top venues, mostly CVPR and NeurIPS.
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 53%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 3 papers2026 · T1 3 · collecting
- 16 papers2025 · T1 8
- 8 papers2024 · T1 4
- 7 papers2023 · T1 3
T1 venuesOtherVenues: CVPR, NeurIPS, ICLR, ICML, ACCV
Research focuspaper titles that use each topic's words
- Accelerators, chips & architecture1 paper
- efficiency0 papers
- vision models0 papers
- hardware-software0 papers
- hardware-software co-design0 papers
Paper list
From the lab homepage.
20263 papers
- TMLR (T1)Any Image Restoration via Efficient Spatial-Frequency Degradation Adaptation (opens in a new tab)
- ICLR (T1)Efficient Degradation-agnostic Image Restoration via Channel-Wise Functional Decomposition and Manifold Regularization (opens in a new tab)
- ICLR (T1)Optimal Brain Restoration for Joint Quantization and Sparsification of LLMs (opens in a new tab)
202516 papers
- GLOBECOMA Compute&Memory Efficient Model-Driven Neural 5G Receiver for Edge AI-assisted RAN (opens in a new tab)
- CASESDesign and Optimization for AI/ML Acceleration on Resource-constrained and Edge Systems (opens in a new tab)
- ICCV (T1)FastVAR: Linear Visual Autoregressive Modeling via Cached Token Pruning (opens in a new tab)
- EMBCFEMBA: Efficient and Scalable EEG Analysis with a Bidirectional Mamba Foundation Model (opens in a new tab)
- EMBCFinetuning and Quantization of EEG-Based Foundational BioSignal Models on ECG and PPG Data for Blood Pressure Estimation (opens in a new tab)
- IEEE Computer Society Annual Symposium on VLSIFlatAttention: Dataflow and Fabric Collectives Co-Optimization for Efficient Multi-Head Attention on Tile-Based Many-PE Accelerators (opens in a new tab)
- Proceedings the of European Conference on Artificial IntelligenceHow Many Does It Take to Prune a Network: Comparing One-Shot vs. Iterative Pruning Regimes (opens in a new tab)
- ICML (T1)IntLoRA: Integral Low-rank Adaptation of Quantized Diffusion Models (opens in a new tab)
- NeurIPS (T1)LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis (opens in a new tab)
- CVPR (T1)MambaIRv2: Attentive State Space Restoration (opens in a new tab)
- CVPR (T1)MarkushGrapher: Joint Visual and Textual Recognition of Markush Structures (opens in a new tab)
- NeurIPS (T1)PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation (opens in a new tab)
20248 papers
- ACCVBringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised Learning (opens in a new tab)
- AICASQ-Segment: Segmenting Images In-Sensor for Vessel-Based Medical Diagnosis (opens in a new tab)
- CVPR WorkshopRetina: Low-Power Eye Tracking with Event Camera and Spiking Hardware (opens in a new tab)
- NeurIPS (T1)Sharing Key Semantics in Transformer Makes Efficient Image Restoration (opens in a new tab)
- CVPR (T1)Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary (opens in a new tab)
- ECCV WorkshopUltra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO (opens in a new tab)
- ECCV (T1)Unified Embedding Alignment for Open-Vocabulary Video Instance Segmentation (opens in a new tab)
- TIP (T1)VRT: A Video Restoration Transformer (opens in a new tab)
20237 papers
- CVPR (T1)CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution (opens in a new tab)
- CVPR (T1)Efficient and Explicit Modelling of Image Hierarchies for Image Restoration (opens in a new tab)
- ICMELearning Continuous Piecewise Non-Linear Activation Functions for Deep Neural Networks (opens in a new tab)
- IROS (T1)LocalViT: Analyzing Locality in Vision Transformers (opens in a new tab)
- CVPR WorkshopLSDIR: A large Scale Dataset for Image Restoration (opens in a new tab)
- Machine Intelligence ResearchPractical Blind Denoising via Swin-Conv-UNet and Data Synthesis (opens in a new tab)
- SensorsTinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision for In-Sensor Gaze Estimation (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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