Aylin Caliskan is a Postdoctoral Research Associate and a CITP Fellow at Princeton University. Her work on the two main realms, security and privacy, involves the use of machine learning and natural language processing. She currently works on big-data-driven discrimination and inference through machine learning. She also has ongoing research on privacy preserving information disclosure and contextual integrity.

In her previous work, she demonstrated that de-anonymization is possible through analyzing linguistic style in a variety of textual media, including social media, cyber criminal forums, source code, and executable binaries. She is extending her work to develop countermeasures against de-anonymization. Aylin's other research interests include designing privacy enhancing tools to prevent unnecessary private information disclosure while quantifying and characterizing human privacy behavior. She holds a PhD in Computer Science from Drexel University and a Master of Science in Robotics from the University of Pennsylvania.