Research Scientist and Data Scientist, Security and Privacy Research Lab
Li Chen is a data scientist and research scientist in the Security and Privacy Lab at Intel Labs, where she focuses on developing state-of-the-art robust machine learning and deep learning algorithms for security analytics including applications in malware detection and image classification in the adversarial setting. Li Chen received her Ph.D. degree in Applied Mathematics and Statistics from Johns Hopkins University. Her research has been featured in a number of pioneering scientific and engineering journals and conferences including IEEE Transactions on Pattern Analysis and Machine Intelligence, Annals of Applied Statistics, IEEE Security and Privacy, ACM CCS, ACM KDD, Parallel Computing, AAAI Conference on Artificial Intelligence, SPIE, International Joint Conference on Artificial Intelligence, ACSAC and Spring Research Conference on Statistics and Industry Technology.
Her research interests primarily include adversarial machine learning, statistical pattern recognition, random graph inference, and inference for high-dimensional data.
This paper presents HeNet, a hierarchical ensemble neural network, applied to classify hardware-generated control flow traces for malware detection. Deep…
For random graphs distributed according to stochastic blockmodels, a special case of latent position graphs, adjacency spectral embedding followed by…
Sorry, there was an error in your submission.