I am currently a postdoc in the Operations Research Department at Carnegie Mellon University. I graduated in May 2023 from the same department through the the Algorithms, Combinatorics, and Optimization (ACO) Program, 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. My e-mail is: rbz@andrew.cmu.edu. Here is my Google Scholar and DBLP.

I am on the job market for both academia and research positions in industry.

Research Interests

Broadly I am interested in operations research and theoretical computer science. I am working on developing new technical tools to design algorithms for fundamental optimization problems with a focus on online and stochastic models. I am also working on applying these algorithms to applications in logistics and the cloud computing supply chain.

Publications

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

Journal Publications

• Benjamin Moseley, Kirk Pruhs, Clifford Stein, Rudy Zhou
  A Competitive Algorithm for Throughput Maximization on Identical Machines
  Mathematical Programming B 2024. (Link)
  (Conference Version) Integer Programming and Combinatorial Optimization (IPCO) 2022. (Link) (Slides)

• 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

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

• Franziska Eberle, Anupam Gupta, Nicole Megow, Benjamin Moseley, Rudy Zhou
  Configuration Balancing for Stochastic Requests
  Integer Programming and Combinatorial Optimization (IPCO) 2023. (Link) (Full Version) (Slides)
  Minor Revision at Mathematical Programming B

• Anupam Gupta, Benjamin Moseley, Rudy Zhou
  Minimizing Completion Times for Stochastic Jobs via Batched Free Times
  Symposium on Discrete Algorithms (SODA) 2023. (Link) (Full Version) (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, Ben Moseley, Rudy Zhou
  Structural Iterative Rounding for Generalized k-Median Problems
  International Colloquium on Automata, Languages and Programming (ICALP) 2021. (Link) (Full Version) (Slides)
  Minor Revision at Mathematical Programming A

• 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) (Full Version) (Slides)

Teaching

• Main Instructor at Carnegie Mellon University:
  • MSBA Machine Learning Fundamentals (Course Designer, Spring 2024)
  • MBA Calculus Fundamentals (Spring 2022, Spring 2023)
• Teaching Assistant at Carnegie Mellon University:
  • Graph Theory (Fall 2020, Fall 2021)
• Teaching Assistant at Washington University in St. Louis:
  • Computational Geometry (Fall 2017)
  • Object-Oriented Software Development Laboratory (Spring 2017)