Aylin Caliskan

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.


33. Chaos Communication Congress, 32. Chaos Communication Congress, 31. Chaos Communication Congress

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.


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