Enzo A. Bergamo

Enzo A. Bergamo
  • Doctoral Candidate

Contact Information

Teaching

All Courses

  • MATH5130 - Comput Linear Algebra

    A number of important and interesting problems in a wide range of disciplines within computer science are solved by recourse to techniques from linear algebra. The goal of this course will be to introduce students to some of the most important and widely used algorithms in matrix computation and to illustrate how they are actually used in various settings. Motivating applications will include: the solution of systems of linear equations, applications matrix computations to modeling geometric transformations in graphics, applications of the Discrete Fourier Transform and related techniques in digital signal processing, the solution of linear least squares optimization problems and the analysis of systems of linear differential equations. The course will cover the theoretical underpinnings of these problems and the numerical algorithms that are used to perform important matrixcomputations such as Gaussian Elimination, LU Decomposition and Singular Value Decomposition.

Knowledge at Wharton

Greenhushing: When Firms Do More Than They Say

Some companies downplay their environmental efforts, a practice known as greenhushing. A new working paper co-authored by Wharton’s Serguei Netessine finds that this gap between what firms say and what they do is associated with higher subsequent abnormal stock returns.Read More

Knowledge @ Wharton - 9/8/2026
AI Is Producing More Software. Why Isn’t It Being Used?

A Wharton study finds that while AI dramatically speeds up software development, human bottlenecks prevent many of those gains from reaching customers.Read More

Knowledge @ Wharton - 9/8/2026
The Hidden Financial Risks of the AI Boom

Joao Gomes, Wharton professor of finance and senior vice dean of research, centers, and academic initiatives, explains why the Federal Reserve needs to pay closer attention to how the massive AI boom is being financed.Read More

Knowledge @ Wharton - 9/4/2026