My research area is in the domain of (Deep) Neural Networks or Deep Learning. My current focus is on recurrent neural networks (gated and ungated) and their efficient architectural realization/implementation as well as feedback (recurrent) neural networks as Attention Networks and Associative Memories.

My research has spanned several areas of Dynamical and Adaptive Systems and Circuits, including chaotic dynamics in circuits and systems.

Over the years, I have developed and taught several courses on Neural Networks and Deep Learning and their computational frameworks and platforms. Parts of my developed courses have matured into a compact (text-)book. This book is entitled:

"Recurrent Neural Networks: from simple to gated architectures."

The book has just been published by Springer-Nature in January 2022. Here is the link at Springer, and it can also be found on Amazon.

I have taught a version of my developed Neural Networks and Deep Learning course online, pretaped lecture modules, and two weekly online meetings for Q & A. The link will be available soon. To get a flavor of this course, here is the welcoming intro to the class attendees in 2019-2020: