About
The Symposium will be held in conjunction with the tinyML Summit 2024, the premier annual gathering of senior level technical experts and decision makers representing fast growing global tinyML community.
Tiny machine learning (tinyML) is a fast-growing field of machine learning technologies enabling on-device sensor data analytics at extremely low power, typically in the milliwatt range and below. The tinyML ecosystem is fueled by (i) emerging commercial applications and new systems concepts on the horizon; (ii) significant progress on algorithms, networks, and models down to 100 kB and below; and (iii) current low-power applications in vision and audio that are already becoming mainstream and commercially available. There is growing momentum demonstrated by technical progress and ecosystem development in all of these areas. The tinyML research symposium serves as a flagship venue for related research at the intersection of machine learning applications, algorithms, software, and hardware in deeply embedded machine learning systems.
The tinyML Research Symposium is held in conjunction with the tinyML Summit, the premier annual gathering of senior level technical experts and decision makers representing fast growing global tinyML community.
Venue
Hyatt Regency San Francisco Airport
1333 Bayshore Highway, Burlingame, CA 94010
Contact us
Committee
Tinoosh MOHSENIN
General Co-Chair
University of Maryland Baltimore County
Paul WHATMOUGH
General Co-Chair
Qualcomm
Wolfgang FURTNER
Program Co-Chair
Infineon Technologies
Charlotte FRENKEL
Program Co-Chair
Delft University of Technology
Boris MURMANN
Steering Committee
Stanford University
Eiman KANJO
Publication Chair
Imperial College London
Marian VERHELST
KU Leuven
Vijay JANAPA REDDI
Harvard University