Chris Tian - Deputy Principle Staff, Software Architect at China Mobile Research Institute

Chris Tian

Deputy Principle Staff, Software Architect at China Mobile Research Institute

Beijing, Beijing, China

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Summary

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Rockstar

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Top School

Chris Tian is a Deputy Principal Staff Software Architect with 17+ years designing and delivering multimedia, IoT, and mobile terminal systems across China’s leading telecom and device vendors. At China Mobile Research Institute he architects NB-IoT suites and IoT big-data solutions while drawing on prior experience building streaming media servers, DVB platforms, and multimedia frameworks at Motorola and Newauto Video. He blends hands-on development with product architecture and project leadership, and contributes to open-source recommender tooling—integrating LightGCN into the RecBole library. With a background in mechanical engineering and a computer science minor, he brings a systems-thinking approach that connects hardware-aware design, codec and streaming pipelines, and large-scale service architecture. Colleagues rely on him for pragmatic technical strategy that spans research insight to production implementation.

7 years of coding experience

5 years of employment as a software developer

Master's Degree, Mechanical Engineering(CAD/CAM), Master's Degree, Mechanical Engineering(CAD/CAM) at Dalian University of Technology

English, French, Chinese

Github Skills (5)

pytorch10

deeplearning-ai10

recommendation-system10

deep-learning10

python10

Programming languages (3)

C++CSSPython

Github contributions (5)

RUCAIBox/RecBole

Aug 2020 - Jul 2021

A unified, comprehensive and efficient recommendation library

Role in this project:

Back-end Developer

Contributions:7 reviews, 40 commits, 10 PRs in 10 months

Contributions summary:Chris primarily contributed to the development of the LightGCN model, a graph convolutional network for recommendation systems. Their work involved implementing the core LightGCN model functionality, including the necessary layers, loss calculations, and prediction methods. The user's commits focused on integrating the LightGCN model within the recbole library and modifying its format and other code format.

pytorchrecommenderdeep-learningcollaborative-filteringsequential-recommendation

ChangxinTian/ChangxinTian.github.io

Oct 2019 - Oct 2022

Contributions:24 pushes in 2 years 11 months

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