Xinlei Wang

🔔 I will join INSAIT as a postdoctoral researcher working on AI sustainability, aligning the growth of AI with environmental considerations. My work asks how we can build AI systems that meet real-world engineering needs, and how we can build them responsibly:

• Life-cycle carbon footprint across data centers, training, and inference
• Attribution and pricing of compute and emissions
• Energy–computation co-design (data-center efficiency and grid readiness)
• LLM agents for real-world engineering in scheduling, planning, and forecasting, where solutions must be feasible and verifiable under real domain constraints, not merely convincing

Currently, I am about to complete my Ph.D. in Electrical Engineering at the University of Sydney under the supervision of Dr. Jing Qiu, and I had an M.Sc. in Data Science from the Chinese University of Hong Kong, Shenzhen under the supervision of Prof. Junhua Zhao, and a B.B.A. with Honors in Finance and Global Business Management from the Chinese University of Hong Kong, Shenzhen.

My work has been published at ICML, NeurIPS, ACL, Cell Patterns, Cell Nexus and Nature Reviews Electrical Engineering. I also have extensive project experience with power grid operators and research institutes, spanning carbon accounting and energy market analysis. Over the past few years, I have led carbon rating reports for 100+ listed companies in Australia and China and served on the editorial board of the AI and Sustainable Development Outlook.