Cheng DENG

About Me

I build efficient AI systems that make foundation models and agents practical for real-world products, edge devices, and intelligent infrastructure.

Currently, I am a Research Fellow at the Bayes Centre, University of Edinburgh, working in collaboration with Prof. Luo Mai, Prof. Jeff Pan, and Prof. Jun Wang. I also serve as a 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 was fortunate to be 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 worked as an Applied Scientist Intern at Amazon Shanghai AI Lab. In 2021, I was selected for the Wenjun Wu Honored Ph.D. Class.

My research focuses on efficient machine learning algorithms and deployable AI systems. My work sits at the intersection of efficient machine learning, AI agents, hardware–software co-design, and edge intelligence, with a particular focus on making AI systems usable under practical constraints such as latency, memory, energy, and hardware availability. My publications can be found on Google Scholar.

News

[2026-04] 2 papers accepted by ACL Main Conference 2026, 2 papers accepted by ICLR 2026, 1 paper accepted by MLSys 2026!
[2026-04] I hosted an academic workshop at the Bayes Centre, University of Edinburgh, titled “Edge AI Agent Workshop”, where I also delivered a talk on “Efficient AI Agent on the Edge”.
[2026-03] Invited show on NiklasOPF Prodcast, sharing “PLM: Peripheral Language Model” and “Hardware co-Design Scaling Law”!
[2026-02] Invited talk on “Efficient LLM on the Edge” at the Cardiff NLP Group seminar in Cardiff University!
[2025-12] Invited talk on “Efficient Physical AI and Beyond” at Li Auto AI Sharing seminar!