Ivan Stelmakh has accepted NES offer to join the School’s faculty in September 2023 after spending one year at Max Planck Institute for Intelligent Systems working with Moritz Hardt, Director of the Social Foundations of Computation.
Ivan is currently a fifth-year PhD student in the Machine Learning Department at Carnegie Mellon University advised by Nihar Shah and Aarti Singh. Before CMU, he received a BS in Applied Mathematics and Physics from Moscow Institute of Physics and Technology.
His research interests lie in the broad area of learning from people with a focus on developing tools and techniques to support human decision-making in scientific peer review. Specifically, in his doctoral thesis, he proposes a set of tools and experiments that aim at improving fairness and efficiency of academic peer review. The rapid growth of the number of submissions to leading publication venues has identified a need for automation of some parts of the peer-review pipeline. However, there is evidence that application of off-the-shelf technologies may amplify unfairness of the process and lead to other unintended consequences. In his research, Ivan aims at identifying and overcoming such unintended consequences by designing tools and techniques to support fair, equitable and efficient peer review.
Ivan’s research is featured in publication venues including the Conference and Workshop on Neural Information Processing Systems (NeurIPS), the Association for the Advancement of Artificial Intelligence, the Journal of Machine Learning Research, and ScienceMag News. It was employed by the International Conference on Machine Learning, NeurIPS, EC, and other conferences and improved the experience of more than 10,000 researchers.
Ivan’s CV is available here.