Ziv Scully joined the faculty at Cornell ORIE in 2023. He completed his Ph.D. in Computer Science at Carnegie Mellon University in 2022, and obtained his B.S. from MIT in 2016. Between graduating from CMU and starting at Cornell, Ziv was a research fellow at the UC Berkeley Simons Institute, and then a postdoc at Harvard SEAS and MIT CSAIL.
Ziv researches the theory of decision making under uncertainty, including stochastic control, resource allocation, and performance evaluation. A particular emphasis of his work is scheduling and load balancing in queueing systems, as motivated by the needs of cloud computing data centers and service systems.
- Applied Probability
- Information Technology Modeling
- Statistics and Machine Learning
Scully, Ziv, Isaac Grosof, and Michael Mitzenmacher. 2022. "Uniform Bounds for Scheduling with Job Size Estimates." Presented at ITCS 2022.
Scully, Ziv, Isaac Grosof, and Mor Harchol-Balter. 2020. "The Gittins Policy Is Nearly Optimal in the M/G/k under Extremely General Conditions." Presented at SIGMETRICS 2021.
Scully, Ziv, Mor Harchol-Balter, and Alan Scheller-Wolf. 2018. "SOAP: One Clean Analysis of All Age-Based Scheduling Policies." Presented at SIGMETRICS 2018.
Selected Awards and Honors
- 2022 SIGMETRICS Doctoral Dissertation Award
- 2022 INFORMS George Nicholson Student Paper Competition Winner
- SIGMETRICS 2021 Best Paper Award
- SIGMETRICS 2019 Outstanding Student Paper Award
- Performance 2018 Best Student Paper Award
- INFORMS Applied Probability Society Best Student Paper Prize Finalist
- Ph.D. (Computer Science), Carnegie Mellon University, 2022
- M.S. (Computer Science), Carnegie Mellon University, 2020
- B.S. (Mathematics with Computer Science), Massachusetts Institute of Technology, 2016