Dan received his Bachelors degree from Stanford University in 2002 and a Master’s degree in Artificial Intelligence from the University of Edinburgh in 2003. His Ph.D. work at UCSF coupled inverse kinematics techniques from robotics with protein modeling and design to allow prediction of flexible protein structures to atomic accuracy, earning him the Julius R. Krevans Award for Most Outstanding Dissertation in 2010. As a HHMI Postdoctoral Fellow of the LSRF in George Church’s lab at Harvard, Dan combined computational protein design with genome-wide codon reassignment to engineer essential enzymes that require synthetic amino acids to function, producing the first organisms that require a synthetic amino acid for survival. As a Technology Development Fellow at the Wyss Institute, Dan is developing methods to design proteins bearing synthetic amino acids that offer new functions and properties. He has also developed a generalized platform to produce biosensors for optimized bioproduction and environmental detection of small molecules.