David Kainer is a staff computational systems biologist at ORNL, specializing in the integration of diverse biological datasets with machine learning for functional gene exploration and genomic prediction.
As a postdoc in the Computational Systems Biology group at ORNL, Kainer was a member of the 2018 Gordon Bell prize-winning team that developed a new algorithm allowing supercomputers to process vast amounts of genetic data and identify genes and potential treatments related to opioid addition.
On the research side at CBI, he is applying machine learning approaches for integrating heterogeneous multi-omic data with the goal of informing genetic improvement of bioenergy feedstocks like poplar and switchgrass.
“Having spent time with CBI’s headquarters, I now think more deeply about how my work may influence the whole of CBI, rather than just my computational biology team,” Kainer said. “Learning how such a large research team and budget is managed effectively were also key to the experience,” he said. “This is not something that can easily be picked up at the postdoc level. Hard decisions have to be made regularly, and it was very valuable to observe how those happen.”
His favorite part of the ECD program came in the opportunity to chair a committee for a new round of internal CBI grants for renewable jet fuel projects. “Every application we received was excellent, and I enjoyed being a major part of the decision-making process,” Kainer said.His advice for other young scientists in the space? “There are so many approaches to producing various forms of bioenergy, and it is hard to predict which ones will be ‘winners,’ so cast a wide net.”