Yang Meng is currently pursuing a Ph.D. in Statistics at the University of California, Irvine, expected to complete by 2026, co-advised by Dr. Babak Shahbaba and Dr. Stephan Mandt. With three years of full-time professional experience in Data Science, he brings a wealth of practical knowledge to his academic pursuits. Prior to his doctoral studies, Yang earned his M.A. in Statistics from Columbia University in 2020, advised by Dr. Tian Zheng, following his B.S. in Statistics from Zhejiang University in 2018.

Research Interests

His research focuses on artificial intelligence:

Multimodal Learning: audio and text-to-image generation, latent representation analysis, and multimodal variational autoencoders

Generative Models: particularly diffusion models, diffusion-VAE hybrids, and video generation

AI for Science: applying AI to neuroscience, specifically through FMRI studies and hippocampal neuron activities, to climate science, and to public health analysis

Uncertainty Quantification: employing Bayesian neural networks and modern statistical inference to address uncertainties in AI models.