I am a second year CS PhD student at Cornell University where I am fortunate to be advised by Lorenzo Alvisi. Prior to grad school I completed my undergrad in CS at TU Berlin, Germany. Outside research, I am an avid tennis player and member of the Cornell Club Tennis team.
My passion lies in analytical thinking and formal rigor as applied to computing systems. My research addresses the design of large scale distributed systems, specifically efficient Byzantine fault tolerance, transaction processing and wide area replication. I am also interested in the use of Machine Learning to design systems to efficiently leverage distributed and on-demand learning. I aim to pursue foundational research that can actually be realized and deployed.
My current research focuses on building robust and efficient replication systems that provide strong consistency. More concretely, my ongoing research is concerned with byzantine fault tolerant replication and in particular how to achieve high degrees of parallelism and decentralization.
Schmidt et al. "Unsupervised Anomaly Event Detection for Cloud Monitoring Using Online Arima." 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion). IEEE, 2018.
Schmidt et al. "Unsupervised Anomaly Event Detection for VNF Service Monitoring Using Multivariate Online Arima." 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2018.