Mattia Cenedese
@mattiacenedese
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Zurich, Switzerland
Joined May 2019
Just published in @Nature_NPJ: we present a data-driven methodology for the high-performance control of continuum robots, including "squishy" robots :) Paper: https://t.co/XPpvF8f9pA Great collaboration with @ETH_en @GeorgeHallerETH
Data-driven, nonlinear, SSM-based model-predictive control of soft robots outperforms other model reduction approaches by a large margin, as shown in https://t.co/2NA0FCSROw. Collaborators at @stanford and @ETH_en: @heateralora, @mattiacenedese, and @drmapavone
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Thanks @ETH_en, I am honored to receive the Silver Medal for my doctoral thesis. It has been an amazing journey, and I express my gratitude to everyone who was part of it.
The doctoral students Francesca Breveglieri, Mattia Cenedese, Cosima Du Pasquier, Hongri Gu, Nolan Lassaline, Carmelo Sferrazza and Ines Weber receive the Silver Medal of ETH Zurich for their outstanding doctoral theses. Congratulations! https://t.co/Ob70ledqp8
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Great time at #AMLDEPFL22 , exciting interactions, inspiring talks, and an opportunity to share my research. I hope to join @appliedmldays again in the future!
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Excited that our research has been published on @NatureComms and highlighted by @ETH_en in this news article. Here is the full paper
Researchers at ETH Zurich have developed a new #algorithm that allows them to model the dynamics of physical systems from observations. In the future it could be applied to the onset of #turbulence and tipping points in #climate. @eth_dmavt
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Interested in data-driven nonlinear model reduction? Check-out our code below with examples from fluid and structural dynamics.
SSMLearn, a Matlab package for learning reduced-order models of non-linearizable behavior from data is now available (with demos on numerical and experimental data sets). Download from here: https://t.co/3HtFngemp3
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