Parker A. Hall
MIT EECS | Undergraduate Research and Innovation Scholar
Pattern Mining for Network Traffic Management
- Artificial Intelligence and Machine Learning
To more efficiently route network traffic, service providers require extra information about the packets that are sent across the network. Information about the sender, receiver, contents, and so on used to be easily accessible by inspecting the data packets, but today, these packets are largely encrypted. As such, all this information must be estimated by recognizing certain patterns present in the traffic of the network. My project aims to implement the MACE algorithm to extract important lower-dimensional information from multi-modal data, possibly incorporating such an algorithm into a neural network to improve training speed.
“I am participating in SuperUROP because I hope to gain valuable research experience in the computer science field. I have been participating in UROPs for the past two years, and I am excited to take on this new project. I hope to learn more about neural networks and their intersection with feature-extracting algorithms.”