Speaker "Joe Isaacson" Details Back



Machine Learning to Program Living Cells


Over the past two decades, the ability to engineer increasingly complex genetic circuits, sequences of DNA that encode computational operations in living cells, has advanced rapidly. Progress has resulted from several factors including faster and cheaper DNA sequencing, an improved understanding of cell biophysics and the ability to make targeted genomic modifications using CRISPR. Such advances have long ranging implications for advancing healthcare and drug discovery. Yet despite this progress, biological engineers often spend years creating a single functional design through manual trial-and-error. Drawing inspiration from machine learning and digital logic synthesis, we built a genetic circuit design automation platform, Cello. Cello has aided in the design of some of the most complex genetic circuitry to date.


Joe is the VP of Engineering at Asimov, a startup with the mission to program living cells. We leverage techniques from synthetic biology, systems engineering and machine learning to automate the compilation of genetic circuits. Prior to Asimov, Joe lead machine learning teams at Quora and at URX (Y-combinator startup, acquired by Pinterest). In these roles, Joe helped to build recommendation systems to personalize content discovery, algorithms to optimize advertisement targeting and machine learning models for search and discovery. Prior to joining the startup world, Joe contributed to research at MIT Lincoln Laboratory and Brown University, developing numerical methods for problems in forensics, computer vision and molecular dynamics.