Xiang Chen
Tenure-Track Associated Professor
Researches mobile and distributed computing systems and high-performance intelligent computing for efficient on-device AI.
Xiang Chen's lab at Peking works on distributed, cloud & edge systems and efficient training & inference. 19 papers since 2023, 9 at top venues, mostly DAC and ICML. 4 alumni. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 47%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 4
Papers by yearfrom the lab homepage, 2023–2026
- 9 papers2026 · T1 5 · collecting
- 1 papers2025 · T1 0
- 6 papers2024 · T1 1
- 3 papers2023 · T1 3
T1 venuesOtherVenues: DAC, ICML, ICLR, IJCNN, TNNLS
Research focuspaper titles that use each topic's words
- Efficient training & inference3 papers
- Distributed, cloud & edge systems2 papers
- distributed computing0 papers
- intelligent computing0 papers
- on-device0 papers
Paper list
From the lab homepage.
20269 papers
- DAC (T1)CODA: A Computation-Data Decoupled Dataflow Paradigm for DNN Computing on NPUs
- Proceedings of the Design Automation and Test in Europe Conference, to appearDolphium: Co-Optimizing Quantization Dataflowand Paradigms on Poly-Hierarchical NPUs
- DAC (T1)HeRo: Adaptive Orchestration of Agentic RAG on Heterogeneous Mobile SoC
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsHST-MoE: Hierarchical Soft-training for Multi-Expert Federated Learning
- DAC (T1)KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models
- Proceedings of the Design Automation and Test in Europe Conference, to appearLATIAS: A General Architecture-Operator Model for Spatial Accelerators with Complex Topology and Memory Hierarchy
- DAC (T1)MIRAGE: Runtime Scheduling for Multi-Vector Image Retrieval with Hierarchical Decomposition
- IJCNNRoboECC: Multi-Factor-Aware Edge-Cloud Collaborative Deployment for VLA Models
- ICLR (T1)ToProVAR: Efficient Visual Autoregressive Modeling via Tri-Dimensional Entropy-Aware Semantic Analysis and Sparsity Optimization
20251 paper
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsFedMT: Multi-Task Federated Learning with Competitive GPU Resource Sharing
20246 papers
- IEEE Transactions on Cognitive Communications and NetworkingCollaborative Learning based Spectrum Sensing under Partial Observations
- Proceedings of the International Conference on Acoustics, Speech, and Signal ProcessingCommunication-Efficient Decentralized Dynamic Kernel Learning
- Proceedings of the Design Automation and Test in Europe Conference, to appear, . [WACV ‘26] C. Xu, F. Yu, J. Xiong, and X. Chen. “Quadranet v2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptation,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer VisionDynaMo: Runtime Switchable Quantization for MoE with Cross-Dataset Adaptation
- ICML (T1)Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
- Proceedings of the Asia and South Pacific Design Automation ConferenceQuadraNet: Improving High-Order Neural Interaction Efficiency with Hardware-Aware Quadratic Neural Networks
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsRethinking Latency-Aware DNN Design With GPU Tail Effect Analysis
20233 papers
- DAC (T1)EagleRec: Edge-Scale Recommendation System Acceleration with Inter-Stage Parallelism Optimization on GPUs
- ICML (T1)Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction
- TNNLS (T1)QC-ODKLA: Quantized and Communication-Censored Online Decentralized Kernel Learning via Linearized ADMM
Where alumni went4 listed
Apply to PekingFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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