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Cheng DENG (Daven)

Research Fellow
Bayes Centre, CSE
University of Edinburgh
cdeng (at) ed.ac.uk
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About Me

Currently, I am a Research Fellow at the Bayes Centre, the University of Edinburgh, working in collaboration with Prof. Luo Mai, Prof. Jeff Pan, and Prof. Jun Wang. I served as the visiting research fellow at Li Auto. Prior to joining the University of Edinburgh, I was a Research Assistant at the Hong Kong University of Science and Technology (Guangzhou), where I worked with Prof. Lei Chen and Prof. Lionel M. Ni. I obtained my Ph.D. in Computer Science from the Acemap IIOT Lab at Shanghai Jiao Tong University, where I had the privilege of being supervised by Prof. Weinan Zhang, Prof. Luoyi Fu, and Prof. Xinbing Wang. During my early research career, I interned with the Data Team at TikTok and as an Applied Scientist at Amazon Shanghai AI Lab. In 2021, I was also selected for the Wenjun Wu Honored Ph.D. Class.

Research Interests

Highlight

We release the Hardware Co-Design Scaling Law for edge deployment, introducing a principled framework for selecting the most suitable LLM for specific hardware and application constraints. By explicitly linking model architecture, training loss, and inference latency through roofline modelling, this work identifies the Pareto frontier between model accuracy and inference latency.

News

Selected Publications [Google Citation]

  1. Preprint Hardware Co-Design Scaling Laws via Roofline Modelling for On-Device LLMs
    Luoyang Sun, Jiwen Jiang, Yifeng Ding, Fengfa Li, Yan Song, Haifeng Zhang, Jian Ying, Lei Ren, Kun Zhan, Wei Chen, Yan Xie, Cheng Deng
    PDF
  2. MLSys 2026 RAGBoost: Efficient Retrieval-Augmented Generation with Accuracy-Preserving Context Reuse
    Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai
    International Conference on Machine Learning Systems, 2026.
    PDF
  3. ICLR 2026 SpatialViz-Bench: A Cognitively-Grounded Benchmark for Diagnosing Spatial Visualization in MLLMs
    Siting Wang, Minnan Pei, Luoyang Sun, Cheng Deng, Kun Shao, Zheng Tian, Haifeng Zhang, Jun Wang
    International Conference on Learning Representations, 2026.
    PDF
  4. Preprint PLM: Efficient Peripheral Language Models Hardware-Co-Designed for Ubiquitous Computing
    Cheng Deng, Luoyang Sun, Jiwen Jiang, Yongcheng Zeng, Xinjian Wu, Wenxin Zhao, Qingfa Xiao, Jiachuan Wang, Haoyang Li, Lei Chen, Lionel M. Ni, Haifeng Zhang, Jun Wang
    PDF Code
  5. ICML2024 DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
    Siyuan Guo, Cheng Deng, Ying Wen, Hechang Chen, Yi Chang, Jun Wang
    International Conference on Machine Learning
    PDF Code
  6. EMNLP2023 Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus
    Tianhang Zhang, Lin Qiu, Qipeng Guo, Cheng Deng, Yue Zhang, Zheng Zhang, Chenghu Zhou, Xinbing Wang, Luoyi Fu
    EMNLP, 2024
  7. Preprint GeoGalactica: A Scientific Large Language Model in Geoscience
    Zhouhan Lin, Cheng Deng, Le Zhou, Tianhang Zhang, Yi Xu, Luoyi Fu, Weinan Zhang, Junxian He, Chao Ma, Yunqiang Zhu, Xinbing Wang, Chenghu Zhou, et al.
    PDF Code
  8. WSDM2024 K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization
    Cheng Deng, Tianhang Zhang, Zhongmou He, Yi Xu, Qiyuan Chen, Yuanyuan Shi, Luoyi Fu, Weinan Zhang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin, Junxian He
    WSDM, 2024
    PDF Code
  9. CIKM2021 GAKG: A Multimodal GeoScience Academic Knowledge Graph
    Cheng Deng, Yuting Jia, Weinan Zhang, Luoyi Fu, Xinbing Wang, Chenghu Zhou, et al.
    CIKM, 2021
    PDF Code

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