Michael Carl Tschantz received a Ph.D. from Carnegie Mellon University in 2012 and a Sc.B. from Brown University in 2005, both in Computer Science. Before becoming a researcher at the International Computer Science Institute in 2014, he did two years of postdoctoral research at the University of California, Berkeley. He uses the models of artificial intelligence and statistics to solve the problems of privacy and security. His interests also include experimental design, formal methods, and logics. His current research includes automating information flow experiments, circumventing censorship, and securing machine learning. His dissertation formalized and operationalized what it means to use information for a purpose.
EventsI'm on the PC for
- The 1st Workshop on Data and Algorithmic Transparency (DAT'16), an event co-located with the Data Transparency Lab Conference and the Workshop on Fairness, Accountability, and Transparency in Machine Learning;
- The 17th Privacy Enhancing Technologies Symposium (PETS 2017);
- The 2016 IEEE Computer Security Foundations Symposium (CSF 2016).