Shiyan Yang 杨世炎

Scientist, Melbourne, Australia

The goal of my career is to empower machines and AI to better understand and support humans. My research focuses on integrating human factors—behavioral, cognitive, and physiological—into machine learning and AI systems to enhance user safety, performance, and overall experience.

Over the past decade, driver monitoring systems have evolved from lab prototypes to automotive-grade products that save lives on the road. My research helped shape their technical roadmaps, algorithm development, and industry guidelines.

My story

2025–2026

Mutinex

As a Senior Data Scientist, I built Bayesian machine learning models for marketing measurement. It took the probabilistic modeling I had used to understand drivers into a new domain, testing the same methods on human decisions at commercial scale and extending my work beyond automotive.
2017–2024

Seeing Machines

I led the AU$1.35 million CANdrive Automated Vehicle trial and the collaboration with the MIT Advanced Vehicle Technology consortium, with research on distraction, drowsiness, takeover readiness, and gaze-context analysis.
2016–2017

UC Berkeley

As a postdoctoral scholar with Steven Shladover, I studied driver-automation interaction in truck platooning, including operating a three-truck platoon on Bay Area freeways.
2010–2016

Texas A&M University

Doctoral research on human factors and cognitive systems. I proposed “cognitive efficiency”, a metric quantifying how much information a person processes per “unit” of cognitive resources.