Weichen Liu
Associate Professor
Works on embedded and real-time systems, network-on-chip design and machine learning acceleration for edge intelligence.
Weichen Liu's lab at NTU works on accelerators, chips & architecture, distributed, cloud & edge systems and rendering & appearance. 48 papers since 2023, 8 at top venues, mostly DAC and EMNLP. 3 PhD students. 10 alumni, most often to Huawei and Alibaba.
At a glance
- papers, 2023–2026
- 13/ year
- at T1 venues
- 17%
- PhD students
- 3
- MS students
- 0
- alumni listed
- 10
Papers by yearfrom the lab homepage, 2023–2026
- 7 papers2026 · T1 3 · collecting
- 11 papers2025 · T1 1
- 10 papers2024 · T1 2
- 20 papers2023 · T1 2
T1 venuesOtherVenues: DAC, EMNLP, ICCAD, TPAMI
Research focuspaper titles that use each topic's words
- Distributed, cloud & edge systems11 papers
- Accelerators, chips & architecture5 papers
- edge intelligence2 papers
- Rendering & appearance0 papers
- learning acceleration0 papers
Paper list
From the lab homepage.
20267 papers
- IEEE TCADCoherence in Control: Bridging Many-Core Mapping and Routing through Cost Unification
- JSACXL Shared Coherent Memory Simulation and Cross-Host Synchronization Mechanisms Design for Data Sharing
- DAC (T1)Hierarchical Pareto-Prompted Optimization for Probabilistic DAG Scheduling on Real-Time Systems
- ICCAD (T1)Mapping Without Graphs: Learning Coherence Traffic for Task Placement
- RTCSAOnline Failure Detection for Robot Manipulation with Time-Aware Metrics and Efficient Models
- ACM TECSRetention-Based Energy-Efficient and High-Core-Utilization Scheduling for Arbitrary-Deadline DAGs
- EMNLP (T1)SlimKV: Joint Token-Feature KV Cache Compression with Reconstruction-Free Beacon Attention
202511 papers
- IEEE TCADA Novel MDM-based Optical Networks-on-Chip with Reliability Analysis
- MEMOCODECoherence-Aware Task Graph Modeling for Realistic Application
- OLTCPDM-PCNN: A Compact and Power Efficient Photonic CNN Accelerator Based on Dual-function Microring Resonators
- IEEE TCADExploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems
- ACM TECSFT-DAG: An Efficient Full-Topology DAG Generator with Controllable Parameters
- GLSVLSILearning Cache Coherence Traffic for NoC Routing Design
- OLTNonvolatile Optical Phase Shifter-Based Coherent Neural Network Accelerator for Efficient Matrix Computations and Inference Tasks
- JSAOptimizing the Performance of In-Memory File System by Thread Scheduling and File Migration Under NUMA Multiprocessor Systems
- RACSReliability Architectures for High-Performance Processors: A Survey and Outlook
- ISEDASimulating CXL Shared Coherent Memory Using Shared Memory Among Virtual Machines
- DAC (T1)STREAM: Spatiotemporal Similarity-based Efficient Approximate Median with Tunable Granularity
202410 papers
- IEEE TCA Context-Awareness and Hardware-Friendly Sparse Matrix Multiplication Kernel for CNN Inference Acceleration
- IEEE JSTQEA Formal Scheme of Fault Injection on Coherent Integrated Photonic Neural Networks
- IEEE JLTA Multi-Objective Particle Swarm Optimization Pruning on Photonic Neural Networks
- IEEE TCADDomino-Pro-Max: Towards Efficient Network Simplification and Reparameterization for Embedded Hardware Systems
- DAC (T1)Double-Win NAS: Towards Deep-to-Shallow Transformable Neural Architecture Search for Intelligent Embedded Systems
- ACM TECSEfficient Deep Learning Infrastructures for Embedded Computing Systems: A Comprehensive Survey and Future Envision
- TPAMI (T1)Enabling Energy-Efficient Deployment of Large Language Models on Memristor Crossbar: A Synergy of Large and Small
- GLSVLSIFedTR: Federated Learning Framework with Transfer Learning for Industrial Visual Inspection
- IEEE TGCNMSONoC: A Metasurface-assisted Hybrid Waveguide/FSO Network-on-Chip Architecture
- ASP-DACPearls Hide Behind Linearity: Simplifying Deep Convolutional Networks for Embedded Hardware Systems via Linearity Grafting
202320 papers
- DATEAccelerating Gustavson-based SpMM on Embedded FPGAs with Element-wise Parallelism and Access Pattern-aware Caches
- IEEE TCADAn Efficient Gustavson-based Sparse Matrix-matrix Multiplication Accelerator on Embedded FPGAs
- IEEE FPLAn Efficient Sparse LSTM Accelerator on Embedded FPGAs with Bandwidth-oriented Pruning
- IEEE TCADAutomated Optical Accelerator Search Toward Superior Acceleration Efficiency, Inference Robustness and Development Speed
- IEEE D&TAutomated Optical Accelerator Search: Expediting Green and Ubiquitous DNN-Powered Intelligence
- IEEE TCADCRIMP: Compact & Reliable DNNs Inference for In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation
- ASP-DACCrossbar-Aligned & Integer-Only Neural Network Compression for Efficient In-Memory Acceleration
- ACM TACODAG-Order: An Order-Based Dynamic DAG Scheduling for Real-Time Networks-on-Chip
- IEEE TCADEdgeCompress: Coupling Multi-Dimensional Model Compression and Dynamic Inference for EdgeAI
- IEEE TCADEfficient FPGA-based Sparse Matrix-Vector Multiplication with Data Reuse-aware Compression
- DATEEMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI
- SRF@ASP-DACEnabling Efficient Edge Intelligence: A Hardware-Software Co-design Approach
Where alumni went10 listed, 33% to industry
Industry 3Academia 6
Most often to
- Huawei
- Alibaba
Also to
- Chongqing University of Posts and Telecommunications
- ETH Zurich
- George Mason University
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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