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Industrial Research School in Smart Industry

Posted on 28 May, 201928 May, 2019 by Gunnar Mathiason

We’re applying for a new national Research School that is about Smart Industry.

I believe that this is a good format for quickly boosting the collaboration and knowledge transfer between industry and academia, when it comes to making use of recent AI techniques. The KK foundation pays a part and employers of a company can spend time to develop their skills together with researchers at our five universities. These PhD students will be active to develop their Smart Industry within the collaborating companies, and from day one.

After my recent few years of collaboration in projects with the Swedish steel industry, I realize that a research school like this one can make a real difference. There are so many problems available, which can be worked on in collaboration, making use of the latest findings in AI and machine learning.

Join us! We need your letter-of-intents, from collaboration partners to be, at Aug 14 2019 latest.

Here’s our current Research School in Information Technology that I’m leading: http://www.his.se/IPSI/

For more info about our next Research School in Smart Industry, go here: https://smartindustrysweden.se/

The Rookies

LINKS

Univ. of Skövde web page/email
SAIL research group web
TimeEdit bookings
DiVA publication list
Google Scholar
LinkedIn
Orc ID 0000-0001-7106-0025
EDAS 1390100

Applications
PKAIS

Current projects

AIMe
INSITE-X
Smart Industry Sweden

Past projects
Swedish Metal
Dataflow

RESEARCH BIO

Senior lecturer in computer science, with a research background in analysis of complex systems, distributed systems and databases, and applied ML.

The research focus in recent years includes explainable and trustworthy AI systems. Along with dramatically increased capabilities of algorithms, there is a now need for designing AI system intentionally for capabilities of for instance explaining AI model uncertainty and AI model assumptions. The adaptation degree of AI used in  new critical application areas will depend on how transparent automated decisions will be.

Since 2016, Dr. Mathiason has developed multiple collaborations with the Swedish steel industry with the intention to increase utilization of AI in the steel industry. Leading the recent projects Dataflow (Outokumpu, Jernkontoret, funded by VINNOVA), Swedish Metal (SSAB and Sandvik SMT, funded by KK), and now INSITE-X (Ovako, Ouokumpu, funded by VINNOVA) several novel papers were published on advanced process analysis using deep learning (DL): In Dataflow, DL was used for revealing the exact part steel sheet shapes determining telescoping errors, while in Swedish Metal a complex steel converter process was modelled using DL. The new project INSITE-X (Ovako and Outokumpu) will use DL to learn a detailed digital twin from only high-resolution data to model dynamic in-production machine behavior.

In 2019, Dr. Mathiason was appointed by Jernkontoret for delivering texts on the strategic utilization of AI in industry for further developing the research agenda of VINNOVA’s Strategic Innovation Program Metallic Material. Dr. Mathiason has also been an adjunct member of Jernkontoret’s Board of Digitalization since 2019.

Keywords: "Complex systems, Analytics, Machine Learning"

MUSIC GIGS

Sound Engineering:
Ebbot Lundberg with Julia Frej
Franska Trion
Bro Mesa
Moonica Mac
Louise Hoffsten

Simon Swanström med LSH
July-Aug 2021 at Lilla Björkö

Ebbot Lundberg with Julia Frej
Aug 2019 at Lilla Björkö

Performances:
Band: Stranger in Town 2020 -
(A Toto Covid Project)
Keyboards

Band: The Rookies 2020 -
(A Classic Rock Project)
Keyboards

Band: Candle Lights 2020 -
(Band)
Keyboards

Band: Graceland 2010 - 2019
(Elvis Presley Tribute)

Keyboards

Band: Sound 2019
(Piano backing tracks+Allsång Mariestad)

MORE

Memorial Stig Mathiason here

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