This community is interested in understanding and affecting the interaction between computing systems and society through engineering, computer science and public policy research, education, and public engagement.
We build new protocols and architectures to improve the robustness and performance of computer networks. We develop practical solutions in wireless networks, network security, traffic engineering, congestion control, and routing.
The Systems CoR is focused on building and investigating large-scale software systems that power modern computers, phones, data centers, and networks, including operating systems, the Internet, wireless networks, databases, and other software infrastructure.
Data often has geometric structure which can enable better inference; this project aims to scale up geometry-aware techniques for use in machine learning settings with lots of data, so that this structure may be utilized in practice.
Last week MIT’s Institute for Foundations of Data Science (MIFODS) held an interdisciplinary workshop aimed at tackling the underlying theory behind deep learning. Led by MIT professor Aleksander Madry, the event focused on a number of research discussions at the intersection of math, statistics, and theoretical computer science.
A webpage today is often the sum of many different components. A user’s home page on a social-networking site, for instance, might display the latest posts from the users’ friends; the associated images, links, and comments; notifications of pending messages and comments on the user’s own posts; a list of events; a list of topics currently driving online discussions; a list of games, some of which are flagged to indicate that it’s the user’s turn; and of course the all-important ads, which the site depends on for revenues.