Yang Zhang
University of California-Los Angeles, CA·Computer Science
The world now has billions of "smart" devices, and their batteries add to electronic waste. One alternative is self-sustaining devices that harvest their own power.
- Fields
Computer Science
Engineering
- Topics
energy harvesting
self-sustaining systems
battery-free devices
- Grants
- 1 known grant, through Dec 2026
What they work on
- Identify the information and resource needs of novice and expert developers of self-sustaining, interaction-powered systems through observation of programming sessions, interviews and surveys.
- Create modules that harvest energy from user interactions such as button clicks and device motion, with energy profiling tools and combinable mechanisms built on a shared backbone system.
- Develop toolkits that guide developers in harvester selection, mechanism design, energy profiling and debugging, and evaluate them with technical tests and user studies including A/B tests and pair programming.
More about the research
This project studies a kind of harvested power that comes from how people use a device, such as pressing buttons or moving it. Such interactions are a promising power source. But they are unpredictable in timing and type, and they must be designed for users' needs rather than power goals. This makes them hard for designers to manage, especially for beginners.
Why it matters
Tools that make it easier to build devices powered by everyday user actions could reduce reliance on batteries and charging. That may cut electronic waste and the environmental footprint of smart devices. Designers who are new to self-sustaining systems would gain practical guidance on choosing harvesters, profiling energy use and debugging.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Fahad Dogar
Tufts University, MA·Computer Science
Measure how much delay, or slack, popular applications can tolerate, through user studies and application analysis at the intersection of networking and human-computer interaction.
Phuc Nguyen
University of Massachusetts, MA·Computer Science·Early-career
Build computational models that translate jaw movement and faint facial vibrations, captured by an ear-worn sensor, into speech sounds and commands so users can control devices silently.
Nirupam Roy
University of Maryland, MD·Computer Science·Early-career
Enable sensing of large-scale gestures and movements near walls, floors and tabletops using coded signal projection through passive acoustic micro-structures and an adaptive intermittent computing architecture for battery-free operation.
The school
University of California-Los Angeles: 84 labs on PI Pages, $1.9B a year on research, 803 research doctorates a year.
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