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. She is also the co-primary investigator (PI) and research lead at the Intel Science & Technology Center for Adversary-Resilient Security Analytics. She designs the roadmaps with Intel and Georgia Tech PIs to jointly meet both industrial and academic research objectives. She provides research direction and in-depth technical guidance to advance the ARSA research agenda. Prior to joining Intel Labs, Li was a Data Scientist in Software and Services Group at Intel, where she focused on developing advanced and principled machine learning methods for cloud workload characterization and cloud computing performance. Li Chen received her Ph.D. degree in Applied Mathematics and Statistics from Johns Hopkins University. Her research interests primarily include machine learning, statistical pattern recognition, random graph inference, data mining, and inference for high-dimensional data. 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, Parallel Computing, AAAI Conference on Artificial Intelligence and SPIE. She has given more than 30 technical presentations, including at the Joint Statistical Meeting (the largest statistics conference in North America), AAAI conference, International Joint Conference on Artificial Intelligence, and Spring Research Conference on Statistics and Industry Technology.
