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. 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, and source code. She is currently extending her de-anonymization work to include non-textual data such as binary files and developing countermeasures against de-anonymization. Aylin's other research interests include quantifying and classifying human privacy behavior and designing privacy nudges to avoid private information disclosure as a countermeasure. At Princeton, she works with Dr. Arvind Narayanan on text sanitization of sensitive documents for public disclosure, which can enable researchers to share data with linguists, sociologists, psychologists, and computer scientists without breaching the research subjects' privacy. She holds a PhD in Computer Science from Drexel University and a Master of Science in Robotics from the University of Pennsylvania.