Ziming Liu

Hi! I’m Ziming, currently a postdoc at Stanford & Enigma, working with Prof. Andreas Tolias. I obtained my PhD from Massachusetts Institute of Technology, advised by Prof. Max Tegmark. Before that, I obtained my B.S. from Peking University. My research interests lie in the intersection of AI and Science:

• Science of AI: Understanding AI using science. I’m interested in understanding intriguing network phenomena (e.g., grokking, neural scaling laws).
• Science for AI: Advancing AI using science. When the scaling of the current paradigm plateaus, it is time to focus back on fundamental science (for AI).
• AI for Science: Advancing science using AI. I’m excited about inventing accurate/interpretable AI4Science models and curiosity-driven AI scientists.

I am grateful to the Quanta magazine (among other media outlets) which has covered all three branches of my research. Consider reading if you want to get some taste:

• Science of AI (Grokking): How Do Machines ‘Grok’ Data?
• Science for AI (Poisson Flow): The Physical Process That Powers a New Type of Generative AI
• AI for Science (KAN): Novel Architecture Makes Neural Networks More Understandable

My research philosophy is best described by John Hopfield’s inspiring words in his Nobel lecture:

[About physics] Physics is not defined by subject matter, but is a point of view that the world around us (with effort, ingenuity and adequete resources) is understandable in a predictive and reasonably quantitative fashion.

[About choosing problems] I am now looking for a big problem whose resolution and understanding will be of significance far beyond its normal disciplinary boundaries and will reorganize the fields from which they came.