Learning the hidden language of the human body
I study how physiology, behavior, environment, and time interact to understand human state and improve human alignment.
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Infer hidden physiological state from signals generated by the body, behavior, and environment.
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Uncover the dimensions and relationships that organize human variation across individuals, environments, and time.
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Use individualized models to identify actions that move people toward desired physiological and performance states.
The Human Alignment Problem
Much of what determines how a human feels and performs is hidden from direct observation.
Human state emerges from interactions among physiology, behavior, environment, and time. These systems continuously generate signals that contain information about underlying state.
My research asks how we can read those signals, map the underlying space, and use that knowledge to guide action.
Selected Research
Research spanning physiological state estimation, biological timing, and personalized decision-making.
Circadian Phase Estimation
READ · MAPInferring internal biological time from noisy, real-world light and activity measurements.
Time Policy & Circadian Health
Mapping how geography, environmental light, biological timing, and civil schedules interact across populations.
MAP
MAP · ALIGNCircadian Digital Twin
Learning individualized models to estimate physiological state and identify actions that accelerate adaptation
Recent Publications
Recent Updates
About Lara
Lara Weed, PhD, is a bioengineer and Wu Tsai Human Performance Alliance Postdoctoral Fellow in the Stanford Intelligent Systems Laboratory, where she is mentored by Prof. Mykel Kochenderfer. Her research combines human experiments, real-world sensing, and computational modeling to investigate hidden physiological state and develop personalized approaches to human health and performance. She completed her PhD in Bioengineering at Stanford with Dr. Jamie Zeitzer focused on human circadian and sleep regulation and building on earlier work in wearable biomechanics and physiological sensing.
