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.

Lucas Starita (Electronic Engineering Student)

Lucas Starita is an advanced Electronics Engineering student at the National University of Mar del Plata (UNMDP), Argentina.
He currently serves as a Teaching Assistant in the area of Projects within the Department of Electronics and Computing at UNMDP, where he supports project-based learning activities and assists students in the development and implementation of electronic systems. His role involves guiding students in translating conceptual designs into technically feasible solutions under real engineering constraints.

Ignacio de Pedro Mermier

Ignacio de Pedro Mermier holds an Electronics Engineer degree from the University of Buenos Aires (UBA) and is a Master’s candidate in Artificial Intelligence. He worked at UBA for six years as a teacher in the Semiconductor Devices course. Currently, he works as an Analog Design Engineer at Allegro Microsystems, where he is part of the Position/Speed sensor team. Ignacio is the winner of the 22nd Microelectronics Olympiad hel in Armenia, recognition that highlights his expertise in the field of microelectronics.

Resources

Preparation content

Participants are strongly encouraged to join the course WhatsApp group using the following link:

👉 https://chat.whatsapp.com/BfMnRYX62MeAnvRLaMhpVo

Through this group, you will gain access to preparatory materials, important announcements, and instructions for installing the software that will be used during the sessions. Completing these steps in advance will help ensure a smooth start and allow us to focus on the core content from day one.

Once you join, feel free to introduce yourself and raise any questions you may have. Active participation and early preparation will help you make the most of the learning experience. We look forward to working with you!

 

SLACK EAMTA-CAE

Schedule