I am a Data and Applied Scientist at Microsoft. I got my PhD from the Algorithms, Combinatorics, and Optimization (ACO) Program at Carnegie Mellon, where I was advised by Ben Moseley. My thesis On Combinatorial and Stochastic Optimization won the 2023 Gerald L. Thompson Doctoral Dissertation Award in Management Science.

In Summer 2022, I was an intern at Microsoft Research Redmond in the Cloud Operations Research (CORE) group, where my mentor was Konstantina Mellou. Previously, I obtained a MS in Computer Science and BS in Mathematics from Washington University in St. Louis, where I was advised by Brendan Juba.

Here is my CV, Google Scholar, and DBLP.

Research Interests

I am broadly interested in algorithms and optimization (especially combinatorial and stochastic) in both theory and practice. On the theory side, recently I am interested in adaptivity gaphs and hardness in stochastic combinatorial optimization. On the applied side, I build end-to-end optimization tools to improve decision making in the cloud computing supply chain.

Publications

Author order is alphabetical by last name unless otherwise noted by (*).

Preprints

• Benjamin Moseley, Kirk Pruhs, Marc Uetz, Rudy Zhou
  Minimizing Completion Times of Stochastic Jobs on Parallel Machines is Hard
  In submission. (Link)

Journal Publications

• Konstantina Mellou, Marco Molinaro, Rudy Zhou
  The Power of Migrations in Dynamic Bin Packing
  Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) 2024. (Link) (arXiv)

• Franziska Eberle, Anupam Gupta, Nicole Megow, Benjamin Moseley, Rudy Zhou
  Configuration Balancing for Stochastic Requests
  Mathematical Programming B 2024. (Link)

• Anupam Gupta, Benjamin Moseley, Rudy Zhou
  Structural Iterative Rounding for Generalized k-Median Problems
  Mathematical Programming A 2024. (Link)

• Benjamin Moseley, Kirk Pruhs, Clifford Stein, Rudy Zhou
  A Competitive Algorithm for Throughput Maximization on Identical Machines
  Mathematical Programming B 2024. (Link)

• Sungjin Im, Benjamin Moseley, Rudy Zhou
  The Matroid Cup Game
  Operations Research Letters, 2021. (Link)

• Rudy Zhou, Han Liu, Tao Ju, Ram Dixit (*)
  Quantifying the polymerization dynamics of plant cortical microtubules using kymograph analysis
  Methods in Cell Biology, 2020. (Link) (Pdf) (GitHub)

Conference Publications

• Anupam Gupta, Benjamin Moseley, Rudy Zhou
  Bayesian Probing on Graphs
  Integer Programming and Combinatorial Optimization (IPCO) 2026 (To appear)

• Benjamin Moseley, Heather Newman, Kirk Pruhs, Rudy Zhou
  Robust Gittins for Stochastic Scheduling
  Sigmetrics 2025. (Link) (arXiv)

• Konstantina Mellou, Marco Molinaro, Rudy Zhou
  The Power of Migrations in Dynamic Bin Packing
  Sigmetrics 2025. (Link) (arXiv) (Slides)

• Konstantina Mellou, Marco Molinaro, Rudy Zhou
  Online Demand Scheduling with Failovers
  International Colloquium on Automata, Languages, and Programming (ICALP) 2023. (Link) (arXiv) (Slides)

• Franziska Eberle, Anupam Gupta, Nicole Megow, Benjamin Moseley, Rudy Zhou
  Configuration Balancing for Stochastic Requests
  Integer Programming and Combinatorial Optimization (IPCO) 2023. (Link) (arXiv) (Slides)

• Anupam Gupta, Benjamin Moseley, Rudy Zhou
  Minimizing Completion Times for Stochastic Jobs via Batched Free Times
  Symposium on Discrete Algorithms (SODA) 2023. (Link) (arXiv) (Slides)

• Benjamin Moseley, Kirk Pruhs, Clifford Stein, Rudy Zhou
  A Competitive Algorithm for Throughput Maximization on Identical Machines
  Integer Programming and Combinatorial Optimization (IPCO) 2022. (Link) (arXiv) (Slides)

• Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou
  Robust Online Correlation Clustering
  Neural Information Processing Systems (NeurIPS) 2021. (Link) (Full Version) (Slides)

• Anupam Gupta, Benjamin Moseley, Rudy Zhou
  Structural Iterative Rounding for Generalized k-Median Problems
  International Colloquium on Automata, Languages and Programming (ICALP) 2021. (Link) (arXiv) (Slides)

• Sungjin Im, Mahshid Montazer Qaem, Benjamin Moseley, Xiaorui Sun, Rudy Zhou
  Fast Noise Removal for k-Means Clustering
  Artificial Intelligence and Statistics (AISTATS) 2020. (Link) (arXiv) (Slides)

Teaching

• Main Instructor at Carnegie Mellon University:
  • MSBA Machine Learning Fundamentals (Course Designer, Spring 2024)
  • MBA Calculus Fundamentals (Spring 2022, Spring 2023)