Texas Advanced Computing Center
University of Texas at Austin
Kelsey M. Beavers, Ph.D.
About Me
I'm a computational biologist interested in using genomics and advanced computing to address one of the most urgent environmental challenges of our time: how to help coral reefs persist in a rapidly changing ocean.
My research began with coral disease. During my Ph.D., I used comparative transcriptomics to investigate stony coral tissue loss disease (SCTLD), exploring the cellular mechanisms underlying disease and the biological factors associated with differences in susceptibility.
Today, my interests have expanded into coral conservation genomics. I am particularly interested in understanding how corals evolve heat tolerance, how genomic information can inform assisted evolution and restoration efforts, and how we can make better use of the biological data the coral research community has already generated.
Advanced Computing for Coral Conservation
At the Texas Advanced Computing Center (TACC), I work at the intersection of life sciences and advanced computing, with direct access to leadership-class computing resources, large-scale data infrastructure, and emerging AI technologies.
This environment gives me the opportunity to think about coral conservation problems at scales that would otherwise be difficult to approach—from integrating large genomic datasets to experimenting with computational methods that can uncover patterns across complex biological systems.
I am especially interested in connecting the rapidly advancing world of high-performance computing with the needs of coral biologists, restoration practitioners, and conservation managers.
AI for Reef Resilience
Current assisted evolution efforts in corals are unlikely to keep pace with ocean warming rates unless there is a significant acceleration in research and implementation (Humanes et al. 2026).
One of my new research areas focuses on applying advancements in deep learning, reinforcement learning, and agentic AI to coral conservation.
I aim to pinpoint challenges where these methods can drastically reduce time to discovery, such as:
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Identifying patterns in large, complex datasets
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Enhancing the synthesis of scientific data
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Analyzing complex conservation scenarios
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Creating tools that enable researchers to better leverage existing knowledge
There is a tremendous (and severely underutilized) opportunity to integrate coral biology, conservation genomics, high-performance computing, and modern AI.
