Rising Stars 2020:

Boya Wang

Postdoctoral Scholar

The University of Texas at Austin

PhD '20 The University of Texas at Austin

Areas of Interest

  • Biosystems and Computational Biology
  • Control, Intelligent Systems, and Robotics
  • Theory


Single Instruction, Multiple Data Computation with Information Stored in DNA (SIMD||DNA)


DNA is a promising data storage medium due to its high density, stability and longevity. Typical DNA storage schemes are not compatible with “in-memory” computation: Manipulating information requires reading out the stored information through DNA sequencing, computing the updated data via classical computers, and synthesizing new DNA. We designed an information storage paradigm (called SIMD||DNA), which enables in-memory and parallel computation with DNA storage. We first theoretically proved the correctness of two programs: binary counting and cellular automaton Rule 110, the latter of which has been shown to be Turing universal. Then we experimentally built the SIMD||DNA device performing binary counting in the lab. While the binary counting is merely a demonstration, our work presents a step towards highly parallel, high-throughput in-memory computation with data stored in DNA.


Boya Wang is currently a postdoctoral scholar at the University of Texas at Austin, working with David Soloveichik. Her research lies at the interface of computer science, electrical engineering, biology, and chemistry. She engineers molecular systems that are able to execute molecular algorithms. Her work has received the Best Student Paper Award at the International Conference on DNA Computing and Molecular Programming. She received her Ph.D. in BioECE from the University of Texas at Austin in 2020. She obtained her B.Sc. in Chemistry from Huazhong University of Science and Technology in China.

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