Johnny (Jingze) Li
Ph.D.
Johnny (Jingze) Li
Ph.D.
University of California, San Diego
University of California, San Diego
Carnegie Mellon University
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Ph.D.
University of California, San Diego
About me
About me
I'm a postdoc at Carnegie Mellon University. I recently obtained Ph.D. from the University of California, San Diego, Department of Mathematics and the Center for Engineered Natural Intelligence. I'm very fortunate to be advised by Prof. Gabriel Silva and Prof. Bo Li.
You can reach out to me at johnnyl2@andrew.cmu.edu.
News: Two of my recent work is on Arxiv:
Paper 1: measure of emergence on networks: https://arxiv.org/abs/2609.38037
Paper 2: Emergence - related behavior of language models (activation pattern change in serial tasks): https://arxiv.org/abs/2609.36221
News: I'm attending COLT 2026 in San Diego, CA. See you there!
News: I defended my Ph.d. thesis!
News: I got awarded the Barbara and Paul Saltman Excellent Teaching Award for Graduate Students at UCSD. link
News: I won the Outstanding Teaching Scholar Award for the UCSD Summer Graduate Teaching Scholars (SGTS) program! I was one of six recipients university wide for the contribution to undergraduate education. link
My research interest lies in the emergent phenomenon of artificial and biological neural networks. My research applies a range of mathematical tools to machine learning, data science and neuroscience. I study emergence and emergent abilities in machine learning and neural systems using mathematics. My collaborators and I are developing emergence-promoting architecture/algorithm design for machine learning and large language models, as well as the design principles of biological neural systems. I study these through the tools of homological algebra, network theory, statistical physics, geometry and information theory.
My research interest lies in the emergent phenomenon of artificial and biological neural networks. My research applies a range of mathematical tools to machine learning, data science and neuroscience. I study emergence and emergent abilities in machine learning and neural systems using mathematics. My collaborators and I are developing emergence-promoting architecture/algorithm design for machine learning and large language models, as well as the design principles of biological neural systems. I study these through the tools of homological algebra, network theory, statistical physics, geometry and information theory.
What is emergence: https://en.wikipedia.org/wiki/Emergence https://arxiv.org/abs/2206.07682
cv: here
You can find my Ph.d. dissertation here
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