ep4 - Alessandro Chiuso: From system identification to computer vision and back

07/12/22 • 38 min

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In this episode, our guest is Alessandro Chiuso. Alessandro is a Professor in the Department of Information Engineering at the University of Padova. The episode covers several topics, including Alessandro’s research trajectory, his work in system identification and vision, and his passion for skiing. Check out Alessandro’s website here: http://automatica.dei.unipd.it/people/chiuso.html
Outline
00:00 - Intro
01:51 - Research trajectory
03:52 - Influential figures
08:20 - System identification
17:07 - Regularized system identification
23:30 - Vision
28:40 - Data-driven methods
30:32 - Future of system identification
33:40 - Question from the audience
34:19 - Advice to future students
35:50 - Skiing at a semi-professional level

Episode links
Giorgio Picci's website: http://www.dei.unipd.it/~picci/
Stefano Soatto's website: http://web.cs.ucla.edu/~soatto/
ERNSI: https://people.kth.se/~bo/ERNSI/
System identification: https://en.wikipedia.org/wiki/System_identification
Regularized system identification: https://tinyurl.com/yc7b7myt
Origin of “regularization”: https://tinyurl.com/y4jmk75f
Hirotugu Akaike: https://en.wikipedia.org/wiki/Hirotugu_Akaike
Structure from motion: https://tinyurl.com/35canfnx
Dynamic textures: https://tinyurl.com/28bdwhwm
Skiing: https://tinyurl.com/2p8xzau6

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Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
Spotify: https://tinyurl.com/4rwztj3c
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Acknowledgments and sponsors
This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

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Previous Episode

ep1 - A brief prehistory of control theory

This episode breaks the ice with a bit of the pre-history of control theory. We discuss three iconic ancestors of the science of feedback, including water clocks developed by Ktesibios, the earliest known thermostat, and governors, a class of mechanical devices, which, without exaggeration, have enabled the first industrial Revolution in Britain.

Outline
00:00 -Intro
01:32 - Ktesibios
06:15 - Cornelis Drebble
11:55 - Governors

Episode links

Ktesibios

https://en.wikipedia.org/wiki/Ctesibius

Drebble

Governors

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Next Episode

ep5 - Sean Meyn: Markov chains, networks, reinforcement learning, beekeeping and jazz

In this episode, our guest is Sean Meyn, Professor and Robert C. Pittman Eminent Scholar Chair in the Department of Electrical and Computer Engineering at the University of Florida. The episode features Sean’s adventures in the areas of Markov chains, networks and Reinforcement Learning (RL) as well as anecdotes and trivia about beekeeping and jazz.
Outline
00:00 - Intro
00:22 - Sean’s early steps
03:53 - Markov chains
08:45 - Networks
18:26 - Stochastic approximation
25:00 - Reinforcement Learning
38:57 - The intersection of Reinforcement Learning and Control
42:37 - Favourite theorem
44:05 - Beekeeping and jazz
48:47 - Outro
Episode links
Sean’s website: https://meyn.ece.ufl.edu/
Sean’s books: shorturl.at/CFGRY (and T. Sargent's review: shorturl.at/hlGNR)
G. Zames: shorturl.at/JPRWX (see also: shorturl.at/chiw5)
State space model: shorturl.at/hST07
The life and work of A.A. Markov: shorturl.at/qsv35
Fluid model: shorturl.at/HKN56
M/M/1 queue: shorturl.at/dQW36
Borkar-Meyn theorem: shorturl.at/eSTV4
NCCR Automation Symposia: shorturl.at/csv03 (see also shorturl.at/ekpZ3)
V. Konda’s PhD Thesis: shorturl.at/bdrv7