David Koes has a longstanding interest in low-level computer systems. He worked as a compiler developer for Green Hills software prior to receiving is Ph.D. in computer science from Carnegie Mellon University in 2009. After completing his thesis, "Towards a More Principled Compiler," which explored novel approaches to optimal backend compiler optimization, he switched research directions to pursue computational drug discovery. Since launching this new research direction, he developed a number of immediately useful, innovate applications that enable interactive drug discovery: Pharmit, smina, 3Dmol.js, PocketQuery, shapedb, Pharmer, ZINCPharmer, and AnchorQuery. These technologies work together to make the "big data" of chemical space accessible to any researcher with a web browser. Using these tools, he participated in a number of applied drug discovery projects, including the winning Teach-Discovery-Treat entry, which achieved a 33% hit rate against the anti-malarial DHODH enzyme.