Machine Learning on VLSI

About the track

Description

It is the newest course offered by the EAMTA. In this track, the students acquire basic notions of Machine Learning techniques and their implementation on integrated circuits.

Track goal

The goal of this course is to give a comprehensive overview of deep neural networks, including training techniques and network synthesis. Additionally, the course will cover the implementation of neural network components and the consideration for data input and output.

A final project will be proposed that includes the design of a neural network for a specific problem and the creation of an architecture for its implementation.

Prerequisites

This course is intended for advanced students, graduate students, and professionals who have a background in VLSI. If you do not have this background, it is recommended that you take the basic VLSI track.

Minimum content

  • Introduction: neural networks on chip
  • Basic concepts of Machine Learning (ML): network and layers
  • Case study
  • VLSI implementation of Machine Learning blocks
  • Advanced  structures of ML

Professors

Dr. Eng. Pedro Julián (UNS, CONICET)

Pedro Julián (UNS, Bahía Blanca) holds an Electronics Engineer and PhD degrees in Control Systems both from Universidad Nacional del Sur (UNS), Bahía Blanca. He is currently Site Manager of the Bahia Blanca Allegro Design Center and Associate Professor at UNS.

Eng. M. Celeste Cebedio (Ph.D. Candidate)

María Celeste Cebedio is an Electronic Engineer and a PhD candidate in Engineering at the National University of Mar del Plata (UNMDP), where she works as a lecturer and researcher. She is a member of the Communications Laboratory and the ICYTE Institute, and her research focuses on the use of artificial intelligence for modeling wireless communication channels in underwater environments. She teaches in the areas of Communications and Digital Systems within the Department of Electronics and Computing at UNMDP, and is a co-author of the book Wireless Communications: Fundamentals and Techniques.

Dr. Eng. Luciana De Micco

Luciana De Micco (UNMdP, Mar del Plata) holds a PhD in Engineering from the National University of Mar del Plata (UNMdP), Argentina. She is currently an Independent Researcher of the National Council for Scientific and Technical Research (CONICET), Full Professor at the Faculty of Engineering, National University of Mar del Plata, and a member of the Institute for Scientific and Technological Research in Electronics (ICYTE), UNMdP–CONICET.

Menzatiuk Oleksandra, BSc

Oleksandra got her Bachelor’s degree in Computer Science at Taras Shevchenko National University of Kyiv, Ukraine. She is currently pursuing her Master’s degree in Artificial Intelligence at Johannes Kepler University Linz, Austria while working as part of Embedded Artificial Intelligence team in Silicon Austria Labs.

Resources

Preparation content

SLACK EAMTA-CAE

Schedule