Siva Balakrishnan

Associate Professor

Bio

I was previously a postdoctoral researcher in the Department of Statistics at the University of California, Berkeley, working with Martin Wainwright and Bin Yu. Prior to that, I was a Ph.D. student in the Language Technologies Institute (a part of the School of Computer Science) at Carnegie Mellon University, advised by Jaime Carbonell. As a graduate student, I was the recipient of a Gates Foundation Fellowship to study interactions between human and HIV proteins, and a recipient of a Richard King Mellon Fellowship for outstanding research in the life sciences.

Specific Research Interests

I am broadly interested in statistical machine learning. Most recently, I have been working on understanding algorithms for solving non-convex estimation problems.

Lab Groups

• Causal Inference Working Group
• StatML Theory

Areas of Research

• Foundations of Inference
• Optimization & Algorithms
• Nonparametric Methods
• High-Dimensional Statistics
• Topological & Functional Data Analysis
• Clustering & Unsupervised Methods
• Statistical Machine Learning