Theoretical Foundations of Big Data Analysis, in Particular Sublinear Algorithms and Lower Bounds in Various Models of Computation for Processing Massive Datasets Such as Streaming, Distributed Communication, Massively Parallel Computation, and Sublinear Time Algorithms
1 faculty research Theoretical Foundations of Big Data Analysis, in Particular Sublinear Algorithms and Lower Bounds in Various Models of Computation for Processing Massive Datasets Such as Streaming, Distributed Communication, Massively Parallel Computation, and Sublinear Time Algorithms on GradNova.
S
Associate Professor and Associate Director of Graduate Studies
Algorithmic Graph Theory, Communication Complexity, Online Algorithms, and Algorithmic Game Theory
Theoretical Foundations of Big Data Analysis, in Particular Sublinear Algorithms and Lower Bounds in Various Models of Computation for Processing Massive Datasets Such as Streaming, Distributed Communication, Massively Parallel Computation, and Sublinear Time Algorithms
Complexity and Algorithms in Graphs
Optimization and Search Problems
+3