Ivan has played an integral part in developing and leading Project #1105: Self-tuning servers for Kubernetes as the Principal Investigator. This project focuses on developing a tool that tunes cloud applications autonomously while identifying different workloads and adapting the configuration accordingly. It minimizes the need for the engineering team to instrument their code or constantly try esoteric configurations on their environments to maximize the performance of running their application in a cost-effective manner.
Ivan's engagement in the project has led to strongly maintained weekly progress and tremendous value for the IBM team. Under his supervision, his group conducted extensive background research to shape and direct the current project. He continues to encourage and guide the team towards continued success. His judgement has been invaluable in finding a balance between depth of research in key areas and expansion into new ones in a research domain that is vast and open-ended.
Ivan is heavily involved in sharing research through papers, workshops, and industry talks at various conferences and exposes the community to the potential of meaningful innovation.
University of Toronto
University of Victoria