Ziv Scully is completing his PhD in Computer Science at CMU, where he is advised by Mor Harchol-Balter and Guy Blelloch. He graduated from MIT in 2016 with a BS in Mathematics with Computer Science. He is the recipient of an NSF Graduate Fellowship and an ARCS Foundation scholarship. Broadly, Ziv researches the theory of decision making under uncertainty, resource allocation, and performance evaluation. His particular focus has been analyzing and optimizing computer systems and algorithms from a stochastic perspective, studying topics including job scheduling, load balancing, and stochastic combinatorial optimization. Publications of his have been recognized with awards from ACM SIGMETRICS, IFIP PERFORMANCE, and the INFORMS Applied Probability Society.