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CS Ph.D.

• A GenAI and Explainable ML fanatic.
  • Diffusion Models (interpretability & alignment)
  • Information Theory
  • Density Estimation

CS B.S.

• Excellent student graduated from the Honors College.
  • Matrix Decomposition

Research Intern -- GenAI

• I'm working on a project to redefine diffusion models.

Research Intern -- GenAI

• I worked with Vikash Sehwag to accelerate the training of Diffusion Models from scratch on 8 H100 GPUs. It costs less than $2000 in only 3 days!

Graduate Student Researcher

• I am studying Generative AI and Explainable ML based on information theory and density estimation.

Graduate Student Researcher

• Experienced in Big Streaming Data Mining, focusing on online anomaly detection and high-dimensional time series analysis.

Undergraduate Student Researcher

• Experienced in Machine Learning of matrix or tensor decomposition and sparse representation.

Info-Decomp

• Interpretable Diffusion Via Information Decomposition - Illuminating the fine-grained relationships learned by diffusion models by noticing a precise relationship between diffusion and information decomposition.

ITDiffusion

• Information-Theoretic Diffusion - A brand new diffusion model or density estimator based on information theory.

Brain-Computer-Interface

• Task-Independent EEG-Identification via Low-Rank Matrix Decomposition

• Dean’s Distinguished Fellowship Award from University of California, Riverside.

• Chinese Government Scholarship from China Scholarship Council (CSC).
• The Meritorious Winner in Interdisciplinary Contest in Modeling. (top 9.74% in over 20,000 teams all over the world)
• Zhejiang Province Government Scholarship.

• 1st Prize University Scholarship from Hangzhou Dianzi University.

• Zhejiang Province Government Scholarship.
• 1st Prize University Scholarship from Hangzhou Dianzi University.