Zhengfeng (Jeff) Lai’s Homepage
I am a ML Research Scientist @ Apple AI/ML, contributing to Apple Intelligence and Vision Foundation Models. Prior to that, I received my Ph.D. honored with Best PhD Dissertation Award from the University of California, Davis in 2023, advised by Prof. Chen-Nee Chuah, Prof. Sen-Ching Cheung, and Prof. Brittany N. Dugger. I received my bachelor’s degree from Zhejiang University in 2019.
My research interests include Large Language Model, Multimodal Pre-Training, Video Foundation Model, label/data-efficient learning, and AI healthcare.
In my free time, I like to play tennis, hiking and outdoor adventures. I also like to talk to people from various backgrounds and learn different life styles. Feel free to chat with me.
Recent News
- We release our first streaming video understanding work: StreamBridge.
- SlowFast-LLaVA-1.5 is accepted by COLM 2025.
- Our video generation model STIV and benchmark ETVA are accepted by ICCV 2025.
- Our next-gen vision encoder CLOC: Contrastive Localized Language-Image Pre-Training is accepted by ICML 2025.
- First-authored paper in large-scale multimodal pre-training Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models is accepted by ICLR 2025.
- Two first-authored papers (VeCLIP and PathCLIP) are accepted by ECCV 2024.
- I’m honored to receive 2024 College of Engineering (COE) Excellence in Graduate Student Research Award and 2024 ECE Best PhD Disseration Award.
- One first-authored paper, “Semi-Path: An Interactive Semi-supervised Learning Framework for Gigapixel Pathology Image Analysis,” was accepted by Smart Health and will present at IEEE/ACM CHASE 2024.
- I receieve my PhD degree from UC Davis will join Apple AI/ML (Cupertino, CA) as a ML Researcher in Nov 2023.
- One first-authored paper, “PADCLIP: Pseudo-labeling with Adaptive Debiasing in CLIP for Unsupervised Domain Adaptation,” was accepted by ICCV 2023.
- I’m honored to receive Advancement-to-Candidacy (AC) fellowship from ECE at UC Davis.
- I will join Apple AI/ML (Cupertino, CA) as a ML Research Intern in March 2023.
- I’m honored to receive the Best Paper Award from Workshop on Learning with Limited Labelled Data for Image and Video Understanding at CVPR 2022.
- I will join Amazon Lab126 (Sunnyvale, CA) as an Applied Scientist Intern in June, 2022.
- Our work on ‘’Smoothed Adaptive Weighting for Imbalanced Semi-Supervised Learning: Improve Reliability Against Unknown Distribution’’ was accepted by The International Conference on Machine Learning (ICML) 2022.