I lead the research and development of foundation models at Amazon AGI, where I focus on the co-evolution of algorithms and systems—the critical intersection that makes AI more capable, efficient, and accessible. My team built the models behind Amazon Nova, Amazon Q, Titan, and the distributed training infrastructure powering Amazon Bedrock and SageMaker HyperPod.
I built this team from zero, starting in 2018 with a focus on distributed training and shared representations. What started as a small group of tech leaders and hackers grew into the engine behind foundation models serving millions through AWS.
Before that, I shaped the open-source AI ecosystem as VP and PMC Chair of Apache MXNet, where I co-authored the Gluon interface. I founded GluonNLP—the first toolkit to reproduce BERT with record-setting training speeds. I served on the ONNX Steering Committee and co-founded the Python Data API Standards Consortium. I believe accessible tools and open standards are essential for an AI future that benefits everyone.
I hold an MS in Computer Science from the University of Maryland and a BS from Shanghai Jiao Tong University.
Amazon AGI, 2024–present
Leading model architecture and training advancement for Amazon's next-generation foundation models. Driving the co-design of algorithms and systems to reduce the cost of intelligence across the stack.
AWS, 2018–2024
Built the team and models from zero. Developed and deployed foundation models underpinning Amazon Q (CodeWhisperer), Titan, Lex, Comprehend, and Kendra. Led LLM pre-training, RLHF, and large-scale distributed training.
AWS, 2018–2024
Contributed core technology for scalable, fault-resilient training infrastructure including Amazon Bedrock and SageMaker HyperPod. Designed systems for training at scale with efficient resource utilization.
Apache MXNet, 2016–2018
Co-authored the Gluon API—an imperative, Pythonic interface for deep learning that became the standard for MXNet. Made deep learning more accessible to researchers and engineers.
Founded, 2018
Created a deep-learning NLP toolkit for the Gluon interface. First to reproduce BERT with record-setting training speeds, accelerating NLP research across the community.
Amazon TRMS, 2013–2015
Designed horizontally scalable machine learning platform and graph-based ML solutions for fraud and abuse detection. Built high-availability key-value stores with expressive transformation DSL for real-time feature engineering.
More talks and podcast appearances coming soon.
VP & PMC Chair
Distributed deep learning framework. Co-authored the Gluon interface.
20.8k starsSteering Committee
Open standard for machine learning model interoperability.
20.5k starsFounder
NLP toolkit for MXNet. First to reproduce BERT at record speeds.
2.5k starsFounding Member
Standardizing array APIs across Python libraries for ecosystem interoperability.
265 stars