- Algorithms for Massive Data
- Randomized and Streaming Algorithms
Vladimir Braverman research interest includes streaming and sketching algorithms, sub-linear algorithms and their applications to data science, software defined networks, cosmology, and machine learning. He obtained his B.S. and M.S. degrees from Ben-Gurion University of the Negev, Israel, and his Ph.D. degree from University of California, Los Angeles in 2011. He is a member of The Institute for Data Intensive Engineering and Science (IDIES) and a member of Executive Committee of The Johns Hopkins Mathematical Institute for Data Science (MINDS).
In 2017, Braverman was the recipient of the National Science Foundation’s CAREER Award.