Mina Konaković Luković and Yunsheng Tian’s paper Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations has been accepted to NeurIPS 2020. In this paper, we propose a novel multi-objective Bayesian optimization algorithm called DGEMO that is used to automate the process of discovering the Pareto-optimal solutions for multi-objective problems, while minimizing the number of performed evaluations. Our algorithm predominantly outperforms relevant state-of-the-art methods on all the benchmark problems.