Yanyi Liu, a doctoral student in computer science at Cornell Tech, has been named a 2022 J.P. Morgan Ph.D. Fellow. The fellowship is awarded to graduate students annually who have the skills and imagination to potentially transform the fields of artificial intelligence and data analytics in productive ways.
In the research for which he won this award, Liu aims at developing best-possible secure constructions of cryptographic primitives that protect the authenticity and confidentiality of communication on the internet. “The goal here is to obtain a truly secure encryption scheme from a computational assumption that is as weak as possible,” said Liu. He describes this as entailing a “search for an ‘unbreakable’ code.” Liu is currently focusing on the possibility of basing one-way functions on worst-case hardness assumptions through the notion of Kolmogorov complexity.
Liu, who is advised by CS professors Rafael Pass and Elaine Shi (formerly in the Cornell CS department and now at Carnegie Mellon University), works in the field of theory of computing.
Last year, Liu’s collaborative research with Pass “On the Possibility of Basing Cryptography on EXP ≠ BPP” received a Best Paper award at CRYPTO 21. Prior to attending Cornell, he obtained his bachelor’s degree in computer science from Tsinghua University, Beijing.
The J.P. Morgan AI Research Awards — of which the Ph.D. fellowship is a part — empower the best research thinkers across AI today.