Study analyzes how networks can distort voters’ perceptions and change election results.

MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.

“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.

Along with studying theory, "it's also important to me that the work we are doing will help to solve real-world problems,” says LIDS student Omer Tanovic.

MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.

System better allocates time-sensitive data processing across cores to maintain quick user-response times.