Daniel Masny is a postdoctoral researcher at the University of California, Berkeley. He received a computer science diploma from Karlsruhe Institute of Technology in 2012 and his Ph.D. from Ruhr Universität Bochum in 2016.
Daniel's main research focus is the cryptographic potential of hard learning problems like Learning Parity with Noise and Learning with Rounding, as well as the concept of weak pseudorandom functions. He contributed to the field of chosen-ciphertext secure public key encryption, the notion of key dependent message security and leakage resilient cryptography.
