Aylin Caliskan-Islam is a postdoctoral research associate at Center for Information Technology and Policy at Princeton University. Aylin Caliskan-Islam is a Postdoctoral Research Associate at CITP. 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 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. Her work has been featured in prominent privacy and security conferences such as Usenix Security Symposium, IEEE Symposium on Security and Privacy, Privacy Enhancing Technologies Symposium, and the Workshop on Privacy in the Electronic Society. In addition, she has given lectures and talks on privacy, security, and machine learning subjects at the Chaos Communications Congress and Drexel University. She holds a PhD in Computer Science from Drexel University and a Master of Science in Robotics from the University of Pennsylvania.