Call for Participation:

tinyML Summit and Research Symposium

tinyML Summit and Research Symposium
March 15, 2021
Online

Registration Link: https://form.jotform.com/210112778977059?src=vjr

Tiny machine learning (tinyML) is a fast-growing field of machine learning technologies and applications, including algorithms, hardware, and software capable of performing on-device sensor (vision, audio, IMU, biomedical, etc.) data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery-operated devices. tinyML systems are becoming “good enough” for (i) many commercial applications and new systems on the horizon; (ii) significant progress is being made on algorithms, networks, and models down to 100 kB and below; and (iii) initial low power applications in vision and audio are becoming mainstream and commercially available. There is growing momentum demonstrated by technical progress and ecosystem development.

The tinyML research symposium serves as a flagship venue for research at the intersection of machine learning applications, algorithms, software, and hardware in deeply embedded machine learning systems. The event will be held along with the tinyML Summit that is open for all to attend between March 22-26, 2021. The research symposium itself is held on March 26th, 2021. We hope to invite you all to attend the conference and learn about tinyML!

A few highlights from the summit and research symposium:

  • Keynote speeches from
    • Luca BENINI (ETH Zurich),
    • Sek CHAI (LatentAI),
    • Vikas CHANDRA (Facebook)
    • Song HAN (MIT),
    • Diana MARCULESCU (UAustin),
    • Mohammad RASTEGARI (Apple)
  • Tutorials from
    • Pete WARDEN (Google),
    • Song CHEN (Facebook),
    • KHOBARE&PATEL (Qualcomm)
    • JONGBOOM&SITUNAYAKE (Edge Impulse)
  • Oral paper presentation and poster session
  • Industry talks from Qualcomm, Edge Impulse, Facebook, Syntiant and Microsoft

 

Program Chairs,
Vijay Janapa Reddi, Harvard University
Boris Murmann, Stanford University