Artificer AI Lab

To build is to know, to know is to learn, the constructs still turn.

Artificer AI Lab pursues AI that learns, adapts, and improves – building systems that are reliable, efficient, and capable in an open-ended world.

Our research focuses on continual learning, foundation model adaptation (including post-training and test-time learning), generative modeling, and neural architecture design covering memory mechanisms and mixture-of-experts, with emphasis on real-world deployment applications.

  • Dong Gong (Faculty)
  • Haodong Lu (PhD, UNSW, Google PhD Fellowship), Term 3 2022 –
  • Huiyi Wang (PhD, UNSW), Term 1 2023 –
  • Ruilin Tong (PhD, UNSW), Term 3 2023 –
  • Chongyang Zhao (PhD, UNSW), Term 1 2024 –
  • Taylor (Zishan) Qin (PhD, UNSW), Term 2 2024 –
  • Xin Xie (PhD, UNSW), Term 3 2024 –
  • Daijiao Liu (PhD, UNSW), Term 3 2024 –
  • Max Eastwood (PhD, UNSW), Term 2 2025 –
  • Mingsong Li (PhD, UNSW), Term 3 2025 –
  • Zeyu Zhang (RA, UNSW), 2025 –
  • Zhenhong Sun (PhD ANU, RA, UNSW), 2024/2022 –
  • Yuhang Liu (Postdoc, visiting PhD, with Javen Shi at AIML), 2018, 2020 –

Alumni (partial list)