Zhuang Li

Dr. Zhuang Li

Lecturer, Data Science and Artificial Intelligence

Details

Open to

  • Masters Research or PhD student supervision
  • Collaborative projects
  • Join a web conference as a panellist or speaker
  • Career advice
  • Membership of an advisory committee
  • Mentoring (long-term)
  • Mentoring (short-term)

About

Dr. Zhuang Li is a lecturer at RMIT University with research expertise in natural language processing, machine learning, and data-efficient AI. He received his PhD from Monash University, where he focused on semantic parsing and generalization in low-resource and multilingual settings. Prior to his PhD, he worked at Microsoft on Bing and Cortana, gaining hands-on experience with large-scale, real-world AI systems.

 

His current research focuses on building culturally-aligned and safe language models, developing efficient data curation and fine-tuning methods, and advancing robust alignment techniques for large language models. His work lies at the intersection of NLP, computational social science, and trustworthy AI. Dr. Li actively supervises PhD students and welcomes applicants with strong motivation and interest in topics such as data-efficient training, language model alignment, synthetic data generation, and culturally-grounded AI.

Research fields

  • 460208 Natural language processing
  • 4611 Machine learning
  • 441007 Sociology and social studies of science and technology
  • 500103 Ethical use of new technology

UN sustainable development goals

  • 16 Peace, Justice and Strong Institutions
  • 9 Industry, Innovation and Infrastructure
  • 10 Reduced Inequalities

Academic positions

  • Lecturer
  • RMIT University
  • Melbourne, Australia
  • 1 Dec 2024 – Present
  • Research Fellow
  • Monash University
  • Melbourne, Australia
  • 1 Feb 2023 – 1 Dec 2024

Non-academic positions

  • Research Scientist
  • Openstream.AI
  • Melbourne, Australia
  • 1 Feb 2023 – 1 Dec 2024
  • Software Developer
  • Microsoft
  • , China
  • 1 Jul 2017 – 18 Dec 2018

Research interests

  • Natural Language Processing (NLP)
  • Data-efficient Learning
  • Large Language Models
  • Trustworthy and Responsible AI
  • Computational Social Science 
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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.