Liangliang CaoSenior Staff Research Scientist and Manager, Google
Research Associate Professor (Affiliated) UMass CICS
[Google Scholar], [DBLP], [arXiv]
Liangliang is a senior staff research scientist and manager in Google AI. Recently he is responsible for deploying the cutting-edge end2end speech models for Google's enterprise customers. He is also interested in computer vision and cross-dataset recognizers. He won the 1st place of ImageNet LSVRC Challenge in 2010. He was a recipient of ACM SIGMM Rising Star Award. In his spare time, he enjoys playing with his son, helping young students, and debugging machine learning algorithms. Here is his (outdated) CV.
- ICASSP'21 "Improving Streaming Automatic Speech Recognition With Non-Streaming Model Distillation On Unsupervised Data" [arXiv]
- ICASSP'21 "Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech Recognition" [arXiv]
- ICASSP'21 "Learning Word-Level Confidence For Subword End-to-End ASR" [arXiv]
- Google's On-Premise Speech2Text is launched! It is the first RNN-T model on-premise. I am thankful for the great experience to work as tech lead/manager and to collaborated with many fantastic colleagues. See reports from Forbes, TechTarget, ZDNet.
- SLT'21 "RNN-T Models Fail to Generalize to Out-of-Domain Audio: Causes and Solutions" [arXiv]
- ECCV'20: Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions [paper]
- MICCAI'20: Deep Active Learning for Effective Pulmonary Nodule Detection [
- MICCAI'19 "3DFPN-HS2: 3D Feature Pyramid Network Based High Sensitivity and Specificity Pulmonary Nodule Detection" [paper]