Starts 18 Oct 2021
Ends 22 Oct 2021
Central European Time
Online -
An ICTP Virtual Meeting

TinyML enables machine learning technologies to perform on-device analytics of sensor data at extremely low power. This allows for new scientific applications to be developed at an extremely low cost and at large scale.
In recent years, hardware advancements have made it possible for microcontrollers to perform calculations much faster. Improved hardware has made it easier for developers to build programs on these devices. Perhaps the most important trend for scientists has been the rise of tiny machine learning, or TinyML.
Between hardware advancements and the TinyML community’s recent innovations in machine learning, it is now possible to run increasingly complex deep learning models directly on microcontrollers. TinyML represents a collaborative effort between the embedded power systems and machine learning communities, which traditionally have operated independently.
  • ML general concepts
  • Scientific Applications of ML
  • Introduction to TinyML
  • Examples of TinyML applications

B. PLANCHER, Harvard University, USA
V.J. REDDI, Harvard University, USA
S. STINCKWICH, United Nations University Institute in Macau, China


Clement Onime (ICTP), Nishanth Sastry (University of Surrey), Marco Zennaro (ICTP), Local Organiser: Marco Zennaro