I am currently an incoming postdoc at the University of Toronto a postdoc in Discrete Optimization Group at the Technical University of Munich, working with Prof. Andreas Wiese and Prof. Stefan Weltge.

Previously, I was a postdoc in the Department of Computer Science and Engineering at the University at Buffalo, where I was advised by Prof. Shi Li. Before that, I was a Ph.D. student in the Department of Computer Science at the City University of Hong Kong, where I was supervised by Prof. Minming Li. Before that, I was an undergrad in Computer Science and Technology at the Hefei University of Technology.

During my grad school and postdoc, I was a long-term visitor at Carnegie Mellon University, where I worked with Prof. Ben Moseley and Prof. Sungjin Im. I was also a short-term visitor in Theory Group at Nanjing University, in Prof. Xiaowei Wu’s group at the University of Macau, in Prof. Peter Kling’s group at the University of Hamburg.

Email: ruilongzhang.cn@gmail.com; ruilong.zhang@tum.de

Here is my DBLP.

Misc: I finally cannot join the University of Toronto because of a visa issue.

Research Interests

I am broadly interested in algorithm design and analysis for combinatorial optimization problems. More specifically, I aim to design approximation and online algorithms with worst-case guarantees under different computational models: offline, online, computational economics, machine learning, and artificial intelligence.

• Approximation and Online Algorithms on Combinatorial Optimization
  
• Scheduling and Network Design
  
• Algorithmic Fairness; Multiagent System; Machine Learning Foundations
  

Publications

Per convention of the TCS community, authors of a paper in conference proceedings or journals have equal contributions and are sorted alphabetically.

Conferences:

• Public Events Scheduling with Busy Agents. (Full Version)
  Bo Li, Lijun Li, Minming Li, Ruilong Zhang.
  IJCAI 2024
• Polylogarithmic Approximations for Robust s-t Path. (Full Version)
  Shi Li, Chenyang Xu, Ruilong Zhang.
  ICALP 2024
• Sampling for Beyond-Worst-Case Online Ranking. (Link)
  Qingyun Chen, Sungjin Im, Ben Moseley, Chenyang Xu, Ruilong Zhang.
  AAAI 2024
• Auction Design for Value Maximizers with Budget Constraints and Return-on-spend Constraints. (Full Version)
  Pinyan Lu, Chenyang Xu, Ruilong Zhang.
  WINE 2023
• Scheduling with a Limited Testing Budget. (Full Version)
  Christoph Damerius, Peter Kling, Minming Li, Chenyang Xu, Ruilong Zhang.
  ESA 2023
• Online State Exploration: Competitive Worst Case and Learning-Augmented Algorithms. (Link)
  Sungjin Im, Ben Moseley, Chenyang Xu, Ruilong Zhang.
  ECML/PKDD 2023
• Online Dynamic Acknowledgement with Learned Predictions. (Full Version)
  Sungjin Im, Ben Moseley, Chenyang Xu, Ruilong Zhang.
  INFOCOM 2023
• Min-max Submodular Ranking for Multiple Agents. (Full Version)
  Qingyun Chen, Sungjin Im, Ben Moseley, Chenyang Xu, Ruilong Zhang.
  AAAI 2023
• Multiagent MST Cover: Pleasing All Optimally via A Simple Voting Rule. (Full Version)
  Bo Li, Xiaowei Wu, Chenyang Xu, Ruilong Zhang.
  AAAI 2023
• Fair Scheduling for Time-dependent Resources. (Link) (Full Version)
  Bo Li, Minming Li, Ruilong Zhang.
  NeurIPS 2021
• Improved Scheduling with a Shared Resource via Structural Insights. (Link)
  Christoph Damerius, Peter Kling, Minming Li, Florian Schneider, Ruilong Zhang.
  COCOA 2020
• Minimizing the Cost of Batch Calibrations. (Link)
  Vincent Chau, Minming Li, Yinling Wang, Ruilong Zhang, Yingchao Zhao.
  COCOON 2019

Journals:

• Online Scheduling of Parallelizable Jobs in the Directed Acyclic Graphs and Speed-up Curves Models. (Link)
  Ben Moseley, Ruilong Zhang, Shanjiawen Zhao.
  Theoretical Computer Science (2022).
• A Note on the Online Interval Scheduling Secretary Problem. (Link)
  Bo Li, Chenhao Wang, Ruilong Zhang.
  Operations Research Letters (2022).
• Minimizing the Cost of Batch Calibrations. (Link)
  Vincent Chau, Minming Li, Yinling Wang, Ruilong Zhang, Yingchao Zhao.
  Theoretical Computer Science (2020).
  A preliminary version appears in COCOON 2019.

Last updated: May 07, 2024.