About me

Hello! My name is Arthur Chen (陳皓楠). I’m a master’s student at the R2L Lab of the University of Waterloo, advised by Victor Zhong. I am also a researcher at the Vector Institute. During my undergraduate studies, I had the privilege of working with Jimmy Lin and Wenhu Chen building retrievers.

I’m sitting at the intersection of Machine Learning (ML) and Natural Language Processing (NLP).

My primary interest is using natural languages to enable ML systems to automatically adapt onto new environments. I’m particularly interested in:

• Language Grounding: using language to establish a shared context between the ML model and the environment
• Test-time Adaptation: adapting ML models at deployment/test time
• Automatic Evaluation: evaluating ML model performance automatically with minimal human effort (e.g., labeling, human evaluation)

Experience

• Research Intern at Salesforce AI Research (2025)
  • Worked on test-time adaptation for LLM-based agents
  • Hosted by Caiming Xiong
• Research Intern at Cerebras Systems (2022)
  • Worked on dynamic sparse training for model compression (i.e., using a fraction of the model’s parameters during training to achieve competitive performance)
• Research Intern at Huawei Noah’s Ark Lab (2021)
  • Worked on image signal processing (ISP) for low vision applications
  • Hosted by Vahid Partovi Nia