Shuming Shi
Principal Researcher And Head Of NLP Center at Tencent AI Lab
Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolShuming Shi is a Principal Researcher and head of the NLP Center at Tencent AI Lab with over 10 years of experience steering research and product-facing natural language systems, including chatbots and text understanding. A Tsinghua-trained PhD, he blends deep academic roots with hands-on engineering from roles at Microsoft Research Asia and Alibaba, moving research into scalable production. His open-source work spans ML infrastructure and scientific computing—contributions to ByteDance’s FedLearner, DeepMD-kit, and Microsoft AI sample projects show a focus on robustness, distributed training, and deployment. He’s equally comfortable refactoring parallel training pipelines and fixing low-level build/configuration issues, reflecting a rare mix of algorithmic insight and MLOps/sysadmin craft. Based in Beijing, he often operates at the intersection of large-scale engineering and research, accelerating real-world NLP systems.
10 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Tsinghua University
Github Skills (35)
javascript10
python10
machine-learning10
cmake10
horovod10
style-transfer10
data-model10
saves10
cicd10
tensorflow10
parallel-computing10
mlmodel10
save10
grpc10
image-processing9
Programming languages (6)
Github contributions (5)
microsoft/pai
Jul 2018 - Sep 2018
Resource scheduling and cluster management for AI
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:61 commits, 56 PRs, 106 pushes in 2 months
Contributions summary:Shuming primarily focused on developing the web portal for the project, contributing to both front-end and back-end functionalities. Their work involved defining the folder hierarchy, implementing new features such as the job submission and marketplace pages, and refining the user interface. They also worked on integrating API endpoints for template search and sharing.
cluster-managementmodel-trainingchainertensorflowcloud
microsoft/samples-for-ai
May 2018 - Sep 2018
Samples for getting started with deep learning across TensorFlow, CNTK, Theano and more.
Role in this project:ML Engineer
ML EngineerContributions:9 commits, 4 PRs, 6 pushes in 3 months
Contributions summary:Shuming primarily contributed to the development and enhancement of a style transfer model. They added TensorBoard and SavedModelBuilder functionalities for improved model monitoring and deployment. Additionally, they adapted the training script to accommodate a remote machine environment, modifying arguments and file paths for better compatibility within the project's infrastructure. These modifications indicate active involvement in refining the model's training process and preparing it for efficient execution and deployment.
mxnetdeep-learningtheanomachine-learningtensorflow
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