The author is Andreas Griewank, Ph.D., a member of the Board of Trustees of Yachay Tech.

When we talk about Algorithmic Differentiation or Automatic Differentiation (DA), the basic reference is a book entitled Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. Its author is Andreas Griewank, Ph.D., Dean of the School of Mathematical Sciences and Information Technology and member of the Board of Trustees of Yachay Tech. This year, the second edition of the book, co-authored by Ph.D. student Andrea Walther, turns 10 and was reprinted as the demand for the book has increased and has exceeded 2,800 citations.

Automatic Differentiation has been applied to fields such as identification of parameters, resolution of nonlinear equations, numerical integration of differential equations and, mainly, optimization. The DA opens up opportunities to improve the accuracy and speed of a computer system, creating new and improved algorithms. This is why it is essential that experts in artificial intelligence and computer science have this tool, and that is precisely what Andreas Griewank’s book promotes.

This year, the second edition of the book, which remains number one within the Artificial Intelligence community, was reprinted because Andreas Griewank’s affiliation changed to Yachay Tech University. From the University, Griewank is working on the third edition of the book, along with his doctoral student, Andrea Walther with whom, in addition, he has made about 6 publications in the last 2 years.