Willow Ahrens
Georgia Institute of Technology, GA·Computer Science
Many of the biggest datasets in science are mostly empty. In single-cell genomics, for example, most genes are not expressed in any given cell, so the data naturally form a sparse matrix — a table where the overwhelming majority of entries are zero.
- Fields
Computer Science
Mathematics & Statistics
Engineering
- Topics
sparse arrays
sparse matrices
sparse array programming
- Grants
- 1 known grant, through Jul 2027
What they work on
- Form four coordinated working groups to develop core ecosystem components for sparse array programming — shared designs, data formats, performance metrics and optimization strategies — aligned through a joint committee.
- Establish contributor pathways, a community governance model and communication practices that enable long-term community ownership of the sparse array programming ecosystem.
- Characterize what users of sparse data tools actually need through interviews, workshops and prototype testing, and translate findings into documentation and design decisions.
- Produce a framework, governance model and roadmap that allow the sparse array ecosystem to be sustained and expanded beyond the award period.
More about the research
Storing and computing on only the nonzero entries saves enormous time and memory, and the software techniques for doing so, collectively called sparse array programming, show up across science, engineering and data-driven research. The problem is that the tools are scattered. People working with sparse data face a patchwork of libraries and formats that are hard to combine, compare or extend, which slows research and makes it harder for newcomers to participate.
Why it matters
Sparse data computations underlie work in fields from single-cell genomics to engineering simulation, but fragmented tooling forces researchers to rebuild or reconcile software instead of doing science. A coordinated ecosystem with shared formats, benchmarks and governance could make these tools easier to combine and reuse, lower the barrier for newcomers and students, and strengthen the shared computational infrastructure that many research communities depend on.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
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The school
Georgia Institute of Technology: 50 labs on PI Pages, $1.5B a year on research, 572 research doctorates a year.
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