Over Chris’s 22 year career at PSC, he has largely focused on issues related to the performance, monitoring, and diagnosis of data transport over high speed networks. He approaches this from multiple angles including how applications interact with the network, analysis of network and TCP stack metrics, and OS/stack interactions. Current areas of research include developing a machine learning analysis approach to the automatic identification of sub-optimal bulk TCP flows using extended TCP stack metrics. The end goal of all his work is to improve the way in which networks support the process of scientific discovery.
Previous projects include HPN-SSH, Web10g, TestRig, and XSight.
Chris is a relatively frequent speaker at conferences such as Internet2’s Tech Ex and Global Summit.
He also likes cats and making his own cured meats. Draw whatever relationship between the two you like.