Arvind Krishna Saibaba

Arvind Krishna Saibaba is an Associate Professor in the Department of Mathematics at North Carolina State University, within the College of Sciences. He holds a PhD in Computational and Mathematical Engineering from Stanford University (2013). His research focuses on inverse problems, numerical linear algebra, and their applications in medical imaging and geosciences. He is particularly known for developing efficient algorithms for large-scale Bayesian inverse problems and randomized numerical methods.

Dr. Saibaba’s work bridges theoretical advancements with practical applications, including parametric kernel approximations, tensor train decompositions, and hybrid projection methods. His recent publications (2023–2025) address cutting-edge topics such as edge-preserving regularization, Monte Carlo diagonal estimation, and non-Gaussian randomized low-rank approximations. He leads research in computational frameworks for dynamic inverse problems and has contributed to geophysical modeling and medical imaging techniques.

• Grants:
  • Collaborative Research: Randomized Algorithms For Dynamic and Hierarchical Bayesian Inverse Problems
  • RTG: Randomized Numerical Analysis
  • ATD: Collaborative Research: Computationally Efficient Algorithms for Detecting Anomalous Atmospheric Emissions

He is affiliated with the Faculty Research Group in Numerical Analysis and Scientific Computing. While no specific awards are listed here, his prolific publication record and grant activity reflect his impactful contributions to computational mathematics.