معرفی
Ziv Scully is an Assistant Professor in the Department of Operations Research and Information Engineering at Cornell University. His research focuses on decision-making under uncertainty, particularly in queueing systems and Markovian/Bayesian bandits. He has advised four PhD students and published extensively on scheduling theory, tail latency optimization, and stochastic control.
Education:
- PhD in Computer Science from Carnegie Mellon University (2022), advised by Mor Harchol-Balter and Guy Blelloch
Research Interests: Ziv explores stochastic control approaches to scheduling and resource allocation, with a focus on queueing theory and Gittins indices. His work bridges queueing systems and Pandora's box problems, aiming to achieve asymptotic optimality in tail latency and resource utilization. Recent efforts emphasize heavy-traffic analysis and cost-aware Bayesian optimization.
Key Trends in Articles: His publications address tail probability analysis, Gittins index applications, and asymptotic optimality in queueing systems. He also investigates preemption overhead and workload diffusion approximations using Stein's method.
Advising: Currently mentors four PhD students: Qian Xie, Amit Harlev, Shefali Ramakrishna, and George Yu. No listed grants, but active in the Simons Institute and Harvard/MIT collaborations.
Teaching: Advocates for advanced mathematical rigor in performance modeling education, as highlighted in his 2023 paper on pedagogical approaches.
