Description |
An ICTP meeting in person This workshop aims to develop sustainable university programs in embedded machine learning (also known as TinyML). We will do so by first bridging the gap between leveraging standard open-access course materials and adapting these materials for local and regional contexts. We will also share best practices and learnings that our network has gained through their implementation of these adaptations over the past few years. We will then augment these courses by exploring the development of university research programs centered on embedded machine learning. We will discuss how to leverage these programs to provide students and faculty with extra-curricular experience and develop new technologies and publications in the field of embedded machine learning. We will also explore how these research agendas can be used to support scientific applications and sustainable development. Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee. |
REGISTRATION: Upon arrival, Visitors not staying in the ICTP Guest Houses, are kindly requested to complete registration formalities at the Adriatico Guest House (Lower level). The Registration Desk will be open from 8.30 to 09.15.
Speaker: | Marco ZENNARO (ICTP, Italy) |
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Speaker: | Marco ZENNARO (ICTP, Italy) |
Speaker: | Manuel ROVERI (Politecnico of Milan) |
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Speaker: | Marcelo ROVAI (UNIFEI IESTI, Brazil) |
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Speaker: | Brian PLANCHER (Barnard College, Columbia University) |
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Speaker: | Jesus LOPEZ (Universidad Autonoma de Occidente, Colombia) |
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Speaker: | Jeremy ELLIS (Mission Secondary School, Canada) |
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Speaker: | Alessandro GRANDE (Edge Impulse) |
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Speaker: | Evgeni GOUSEV (TinyML Foundation) |
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Speaker: | David CUARTIELLES (Malmo University) |
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Speaker: | Marcus RUB (Hahn-Schickard-Gesellschaft für angewandte Forschung e.V.) and Thomas AMBERG (University of Applied Sciences and Arts Northwestern) |
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Speaker: | Sebastian BUETTRICH (University of Oregon, NSRC and ICTP, Italy) |
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Speaker: | Solomon Gizaw TULU (Addis Ababa University) |
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Speaker: | Ronald CRIOLLO (Escuela Superior Politécnica del Litoral, Ecuador) |
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Speaker: | Diego MENDEZ CHAVES (ICTP, Italy) |
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Speaker: | Rosdiadee Bin NORDIN (UKM, Malaysia) |
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All participants are cordially invited to the Welcome Reception
Speaker: | Eric PAN (Seeed Studio) |
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Speaker: | Pietro MANZONI (Universidad Politecnica de Valencia) |
Speaker: | Paul KUCERA (UCAR/COMET) |
Speaker: | Cyril CAMINADE (ICTP) |
Speaker: | Marcelo ROVAI (UNIFEI IESTI) and Jose Antonio BAGUR (Arduino) |
Neena GOVEAS (TinyML research and human health monitoring) Jose Antonio BAGUR (Anomaly Detection Course)
Laila KAZIMIERSKI (Animal tracking) Milan LUKIC (Lightweight digit recognition in utility metering, Anomaly detection in logistics asset tracking, Detection of fungal disease outbreak risk in agriculture) Jackline TUM (leveraging TinyML for illegal Logging detection) Halleluyah AWORINDE (Leveraging TinyML for vocalization signal-based Poultry Health Management) Brian PLANCHER (ML Sensors and Environmental Impact of TinyML)
Brian PLANCHER facilitator
in Groups outline the key points for the following sections: Courses that can (and need) to be taught, best practices on sharing educational materials, steps toward building a research program, curriculum diagrams building off of (or centered around TinyML), etc.
shuffle the groups up and have them keep working for cross pollination (we can random the groups ahead of time)
last random shuffle and group work
report back on final landing points for the various sections and discuss as a large group. Hopefully we can all align on the outline of the paper for each section.
Speaker: | Stephen OZOIGBO (ARM) |
(Group Work, Brian PLANCHER facilitator) Where can we go from here? On-device learning? EE? CE? CS? AI? Connections to other domains? Robotics?
how does this all fit in your curriculum? What can be done to improve your local experience and effectiveness?
how can we better collaborate on teaching and research – what systems do we need to put in place? Can we leverage the learnings in LATAM to improve this elsewhere?