Learn Dash for Autonomous Vehicle and AI Applications

With Plotly's Lead AI/ML Engineer

October 27, 2021

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From Uber to Lyft, Audi to Ford, numerous companies are racing to develop AI technology for autonomous vehicles (AV). Researchers have made significant open-source contributions along the way, releasing libraries like deck.gl, a 3D visualization tool that can be directly integrated with Mapbox, and streetscape.gl, a collection of React components or building a custom AV dashboard. These libraries have been extremely useful, but require a full-stack team with extensive knowledge in JavaScript, React, Node.js, and webpack.

At Plotly, we want to make these AI tools accessible to the Python community. Using our Dash framework, we created several template apps and components that bring open-source accessibility to existing R&D. Join Xing Han Lu, the Lead AI/ML Engineer at Plotly, in a webinar as he demonstrates how to operationalize this new generation of autonomous vehicles and AI technology.

In this 1-hour recorded webinar, Xing Han shows how to:

  • Implement web-based visualization tools for LIDAR point clouds and bounding boxes
  • Build an Autonomous Visualization System (AVS) in <200 lines of Python using Dash
  • Add flexibility, control, and editable annotations to complex AI visualizations with real-time data processing

About the Speaker

Xing Han Lu is the Lead AI/ML Engineer at Plotly. He created Dash Cytoscape, an open-source network visualization component. Previously, he worked for Deloitte, where he specialized in summarization engines. He has also led IMIA Conference & AAAI Workshop papers for the McGill Clinical and Health Informatics lab. Some of his projects can be found on Kaggle, where he is a Kernels Grandmaster.