Pan is a Research Scientist at Autodesk Research. His primary research interests lie within motion generation using controllable generative models, generative algorithms, and human-computer-Interaction interfaces in the generation processes.
Pan cares about making research results applicable to real-world systems. He also drives a project that helps to cast research results into scalable and production-ready systems. The project builds a tool that creates large systems by finding better ways to orchestrate research results from different areas and data pipelines. The work has been used in various projects now.
Before this, Pan worked on building and simplifying the human factor extraction pipeline for optimizing design solutions.
Pan received a Bachelor’s Degree and a Master of Science in computer science at the University of Toronto. His research focus as a graduate student was computer vision.
Socio-Spatial Comfort: Using Vision-based Analysis to Inform User-Centred Human-Building Interactions
A well-designed workplace has a direct and significant impact on our…
Demo: Semantic Human Activity Annotation Tool Using Skeletonized Surveillance Videos
Human activity data sets are fundamental for intelligent activity…
Design Loop: Calibration of a Simulation of Productive Congestion Through Real-World Data for Generative Design Frameworks
This paper extends the applicability of generative design for space…
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