Alexander Golovnev

Alexander Golovnev is an Assistant Professor at Georgetown University's Computer Science Department. His research focuses on computational complexity, algorithms, pseudorandomness, learning theory, and cryptography. He received his PhD from New York University in 2017, advised by Oded Regev and Yevgeniy Dodis, with postdoctoral positions at Columbia University, Yahoo Research, and Harvard University.

His current teaching includes Matrix Rigidity (Spring 2025) and Introduction to Algorithms. He has developed a 5-Course Specialization on Discrete Mathematics and organized workshops on Matrix Rigidity and Fine-Grained Cryptography. Service includes program committees for CSR'22, FOCS'22, STOC'24, CCC'24, and ITC'25.

Research interests span quantum computing reductions, lattice problems, circuit complexity, and fine-grained cryptography. His recent publications explore worst-case to average-case reductions, function inversion tradeoffs, and SNARK constructions.

Awards include NSF CAREER Award (2024), Rabin Postdoctoral Fellowship (2018-2020), and IPEC excellent student paper award (2012).

Current PhD/Master's advisees: Sidhant Saraogi (joint with Justin Thaler), Karthik Gajulapalli, Samuel King, and Satyajeet Nagargoje.