忻斌健

忻斌健 Xin Binjian

Deep Learning Practioner & Software Developer

Biography

Binjian Xin is a deep learning practitioner and software developer. His interests include deep learning, artificial intelligence and software design.

Interests
  • Deep Learning
  • Autonomous Driving
  • Time Series Modeling and Processing
  • Computer Vision
Education
  • PhD in Image Processing, 2008

    University of Karlsruhe

  • MSc in Robotics, 2002

    Tongji University

  • BSc in Electrical Engineering, 1998

    Tongji University

Skills

Technical
Python
C/C++
Data Science
MLOps
Languages
Chinese
English
German
Hobbies
Hiking
Reading
Photography
Cats

Experience

 
 
 
 
 
Newrizon
Senior Technical Director, Advanced Development
November 2020 – May 2024 Shanghai
  • Reinforcemnt learning based BEV controller optimization in multimodal complex environments.
  • Timeseries anomaly detection and battery state of safety prediction based on generative models.
  • Software design & development of streaming data pipelines
 
 
 
 
 
Nio
Senior Manager, Autonomous Driving
November 2015 – November 2020 Shanghai
  • Advanced hardware and software design of autonomous driving systems.
  • Development of intelligent charging and automatic parking assistance system.
  • Application and operation of Intelligent Connected Vehicle (ICV) road test in Shanghai and Beijing.
 
 
 
 
 
Patac/SAIC-GM
Technical Manager, ADAS
November 2015 – November 2020 Shanghai
  • System & software architecture design for active safety domain unit (ADU).
  • PATAC ADU A sample: system and software architecture of embedded platform.
  • Software architecture of SAIC-MAXUS SV73 highway assist.
  • Camera based driver monitoring system.
 
 
 
 
 
Visteon Asia Pacific
Software Manager
January 2015 – August 2015 Shanghai
  • SOP project of instrument clusters.
 
 
 
 
 
Hella Electronics
Senior Manager, Software
July 2014 – January 2015 Shanghai
  • SOP project of BCM and PEPS.
  • Platform project of PEPS, BCM, BSW.
 
 
 
 
 
Harman International
Senior Manager, ADAS
September 2009 – July 2014 Shanghai
  • Development of video based ADAS system.
  • SOP projects of camera based parking systems.
  • Supervision of ADAS advanced research.

Projects

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candycan

Python CAN application wrapper:

  • encapsulation with cached properties,
  • validation via Pydantic,
  • virtual CAN testing via local Actions,
  • a2l file handling with lazy loading and dynamic properties,
  • lazy loading by streaming json processing.
candycan
funes-ts

Time series analysis with generative models:

  • Vanilla GAN
  • Wasserstein GAN
  • Wasserstein GAN with gradient penalty
funes-ts
tspace

Time sequence data pipleline framework for deep reinforcement learning:

  • coordinated ETL and ML pipelines with asynchronous data pipelines,
  • online local/distributed training,
  • reinforcement learning models with regular and recurrent models,
  • offline reinforcement learning with Implict Diffusion Q-learning.
tspace