Richard Feynman blackboard quote
What I cannot create, I do not understand. — Richard Feynman

I am a Senior Research Scientist at Futurewei Technology. I received my PhD and MS in Computer Science from Stevens Institute of Technology, and my BS in Computer Science from Harbin Institute of Technology. My research interests are broadly in artificial intelligence, with a primary focus on probabilistic generative models that can understand the world. I have also completed internships as a Research Scientist at Toyota Research Institute and Futurewei Technology.

Publications

COSMIO examples of galaxy observations and cross-survey imputation
NeurIPS 2026
COSMIO: A Benchmark for Cross-Survey Modality Imputation
Dichang Zhang, Yixuan Shao, Jiaqi Deng, Jiali Cui, Haotian Yin, Yuanpeng Liu, Xiang Gao, Zhiqiang Lao, Heather Yu, Simon Birrer, Dimitris Samaras
VLM-teacher framework for galaxy morphology classification
KDD 2026
A General-Purpose VLM Can Teach an Astronomy Foundation Model to Better Recognize Galaxy Morphology
Dichang Zhang, Jiaqi Deng, Yixuan Shao, Yuanpeng Liu, Jiali Cui, Zhiqiang Lao, Heather Yu, Liang Peng, Simon Birrer, Dimitris Samaras
Reconstruction error and geometry-aware saliency heatmaps on a 3D frame-shaped model
SIGGRAPH Posters 2026
Where to Learn Matters: Feature-Aware Sampling for Neural SDF Reconstruction
Haotian Yin, Jiaxing Zhang, Zhiqiang Lao, Yu Guo, Yuanpeng Liu, Jiali Cui, Heather Yu, Przemyslaw Musialski
TMLR 2026
TMLR 2026
Learning Multimodal Energy-based Model with MultimodalVariational Auto-Encoder via MCMC Revision
Jiali Cui, Zhiqiang Lao, Heather Yu
TMLR 2026
TMLR 2026
Learning Multi-stage Energy-based Prior for Hierarchical Generative Models
Jiali Cui, Tian Han
AAAI 2026
AAAI 2026
ShaLa: Multimodal Shared Latent Space Modelling
Jiali Cui, Yan-Ying Chen, Yanxia Zhang, Matthew Klenk
ECCV 2024
ECCV 2024
Learning Multimodal Latent Generative Models with Energy-Based Prior
Shiyu Yuan, Jiali Cui, Hanao Li, Tian Han
ICML 2024
ICML 2024
Learning Latent Space Hierarchical EBM Diffusion Models
Jiali Cui, Tian Han
NeurIPS 2023
NeurIPS 2023
Learning Energy-based Model via Dual-MCMC Teaching
Jiali Cui, Tian Han
ICCV 2023
ICCV 2023
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior
Jiali Cui, Ying Nian Wu, Tian Han
CVPR 2023
CVPR 2023
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator
Jiali Cui, Ying Nian Wu, Tian Han
NeurIPS 2020 Workshop
NeurIPS 2020 Workshop
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling
Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu