I am a 5th (and final) year PhD student in the Operations Research Department at Carnegie Mellon University. In particular, I am a student in the Algorithms, Combinatorics, and Optimization (ACO) Program. My advisor is Ben Moseley.
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.
I am on the job market for both academia and research positions in industry.
Currently, my main interests are Optimization under Uncertainty and Data-driven Optimization. I am very interested in developing new models and technical tools to design and analyze algorithms for fundamental problems in these areas. Some particular models I am investigating are stochastic, online, and with predictions. More broadly, I am interested in Approximation Algorithms and Combinatorial Optimization.
- Konstantina Mellou, Marco Molinaro, Rudy Zhou
Online Demand Scheduling with Failovers
arXiv 2022. (Link)
Author order is alphabetical by last name unless otherwise noted by (*).
Franziska Eberle, Anupam Gupta, Nicole Megow, Benjamin Moseley, Rudy Zhou
Configuration Balancing for Stochastic Requests
Integer Programming and Combinatorial Optimization (IPCO) 2023. (Link)
Anupam Gupta, Benjamin Moseley, Rudy Zhou
Minimizing Completion Times for Stochastic Jobs via Batched Free Times
Symposium on Discrete Algorithms (SODA) 2023. (Link)
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) (Full Version) (Slides)
In submission to Math Programming
Sungjin Im, Benjamin Moseley, Rudy Zhou
The Matroid Cup Game
Operations Research Letters, 2021. (Link)
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)
In submission to Mathematics of Operations Research
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)
- Main Instructor at Carnegie Mellon University:
- MBA Calculus Fundamentals (Spring 2022 Session 1, Spring 2022 Session 2)
- 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)