Annie Chen is a designer, scientist, and socio-technical researcher based in the United States.

Her work explores how environmental technologies encounter human and living systems across the climate transition. She develops artifacts and systems that make these encounters legible, enabling new forms of collective sense-making across science, technology, and community life.

After graduating from the Brown|RISD Dual Degree Program, she co-founded BEAM, a research-led creative studio for people & planet. She is also a Research Affiliate at the MIT Media Lab’s Community Biotechnology Initiative and a member of NEW INC, the New Museum’s design, culture, and tech incubator, in the Year 12 Creative Science cohort.

Her work has been supported by NASA Ames Research Center, MIT Media Lab, Science History Institute,
New York Foundation for the Arts, Brown University, EY Intelligent Realities Lab, and more.

CV


Selected Projects

🌀1 ASILOMAR
🌀2 TIDELANDS 2100
🌀3 CIVIC BIOTECHNOLOGY
🌀4 EATING THE WHOLE FISH
🌀5 NASA AMES
🌀6 BEACONS

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NASA AMES RESEARCH CENTER

Lead Researcher
Ames, CA | Providence, RI
2020-2023Biomimetic Swarms for Remote Sensing

PI: Dr. Lynn Rothschild
NASA Ames Research Center, Brown University
AbSciCon Abstract Innovation Proposal

Speculative proposal & series of artifacts developed at NASA Ames for swarm-based aerial platforms to detect life on and off earth. Deep biomimetic inspiration from the dispersion strategies and mechanisms of seed pods. In our search for life off earth, can we look to life on earth?


Inspired by the low-risk, high quantity approach that seed pods take to passive flight, this project explores a swarm-based, biomimetic approach to in situ remote sensing of atmospheres for both on and off-Earth applications. This novel approach, which draws from the dispersion strategy of the dandelion and maple seed to inform the design of miniature aerial platforms, addresses the exploratory platform gap between the current models of in situ measurement and remote satellite sensing, and has the potential to mitigate current shortcomings of both approaches. 

Exceptionally lightweight, low-cost, and low-risk, this concept has the potential to be deployed in a range of applications that are either inefficient or impossible with current remote sensing techniques– from continuous vertical profiling of the transition from space to Earth’s upper atmosphere, to the detection of biological components and the modeling of wind patterns in off-Earth atmospheres like Venus and Mars.

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