My real name: Daniel O'Connor.

I'm an assistant professor in the Mathematics and Statistics department at University of San Francisco.

Background: Applied math PhD at UCLA, researched algorithms for large scale convex optimization with advisor Lieven Vandenberghe. I did a postdoc in the UCLA Department of Radiation Oncology, where I developed algorithms for radiation treatment planning.

Here's my PhD thesis: http://escholarship.org/uc/item/4z1126w3#page-1

Here are some of my stackexchange highlights:

How would you discover Stokes's theorem?

What was Feynman's "much better way of presenting the electrodynamics"?

The intuition behind the SVD

The intuition behind the dual problem in optimization

The intuition behind Lagrange multipliers

Deriving the gradient boosting machine algorithm

Why does the fundamental theorem of calculus work?

What is the Jacobian matrix?

Intuition behind the chain rule

Understanding a proof of the inverse function theorem

Discovering the discrete Fourier transform

Computing the gradient of $\frac12 | Ax - b |^2$ with finesse

An easy way to discover Taylor approximation with a formula for the remainder

Intuitive explanation of the multivariable change of variables formula

A natural proof of the Cauchy-Schwarz inequality

What is integration by parts, really?

Understanding the Laplace operator conceptually

An easy derivation of Cramer's rule