Colloquium

Ten years into the revival of deep networks and artificial intelligence, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture of intelligence in general. We introduce two fundamental principles, Parsimony and Self-consistency, that address two fundamental questions regarding Intelligence: what to learn and how to learn, respectively. We […]

This talk will begin by discussing phase transitions in high-dimensional statistical inference problems. Some effort will be made to distinguish between problems with random structure (e.g., random codes and sparse PCA) and problems with deterministic structure (e.g., highly symmetric codes such as Reed-Muller codes). For problems with deterministic structure, we will observe that symmetry can […]

Effective theories play a fundamental role in how we reason about the world. Although real physical processes are very complicated, useful models abstract away the irrelevant degrees of freedom to give parsimonious representations. In contrast, overly complex models can be difficult to evaluate, suffer from numerical instabilities, and may overfit data. They also obscure useful […]

In this talk, I will discuss my group’s work on fabricating micro- and nanosensing platforms for health monitoring. My group has developed novel electronic sensing modalities and has demonstrated their use for both in vitro with human clinical samples and in vivo in animals. In the first part of my talk, I will discuss sensor […]