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Peer review is the backbone of scientific research. Yet peer review is called "biased," "broken," and "unscientific" in many scientific disciplines. This problem is further compounded with the near-exponentially growing number of submissions in various computer science conferences. Due to the prevalence of "Matthew effect'' of rich getting richer in academia, any source of unfairness in the peer review system, such as those discussed in this tutorial, can considerably affect the entire career trajectory of (young) researchers. This tutorial will discuss a number of systemic challenges in peer review such as biases, subjectivity, miscalibration, dishonest behavior, and noise. For each issue, the tutorial will first present insightful experiments to understand the issue. Then the tutorial will present computational techniques designed to address these challenges. Many open problems will be highlighted which are envisaged to be exciting to the WSDM audience, and will lead to significant impact if solved.

WSDM 2021 Tutorial on Systematic Challenges and Computational Solutions on Bias and Unfairness in Peer Review