I'm a Senior Data Scientist at Just - Evotec Biologics, with an MS in Computer Engineering. I began at Intel in microchip design before moving to a synthetic biology lab and applying machine-learning/AI methods to genetic circuit design and protein stability prediction.
My work in the Klavins lab (UW) centered on Bayesian and information theoretic methods to improve designs under uncertainty and led to a reinforcement learning tool called Beluga (See Academic Research). I was also co-inventor and founding member of a laboratory automation project called Aquarium - which today is the UW Biofabrication Center (UWBIOFAB). As a part of lab automation, I developed a vision-based application to track wetlab objects and protocol execution.
I'm currently working on new deep-learning approaches to human antibody design with an emphasis on Generative Adversarial Networks (GANs) for antibody discovery and developability. Using GANs to generate humanoid antibodies leads to highly customizable therapeutic discovery libraries - providing a new platform for faster, better drugs.
Check out the preprint to learn more about the Antibody-GAN approach.
RA ECE: Univeristy of Washington, Seattle
MS ECE: Univeristy of Texas, Austin
BS ECE: University of Texas, Austin
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