DATA SCIENCE STAFF MEETING RAYMOND VELDHUIS Time : 13:30 15:30 - - PowerPoint PPT Presentation

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DATA SCIENCE STAFF MEETING RAYMOND VELDHUIS Time : 13:30 15:30 - - PowerPoint PPT Presentation

Jun 23, 2023 135 likes •317 views

DATA SCIENCE STAFF MEETING RAYMOND VELDHUIS Time : 13:30 15:30 Location : ZI 2042 Attendees : DS members (21 attendees) MT : Raymond (EE), Maurice (CS) en Nelly (AM) CALENDAR 1 Photo to be taken: you are requested to be present at the

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DATA SCIENCE STAFF MEETING

RAYMOND VELDHUIS

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Time : 13:30 – 15:30 Location : ZI 2042 Attendees : DS members (21 attendees) MT : Raymond (EE), Maurice (CS) en Nelly (AM) CALENDAR 1 Photo to be taken: you are requested to be present at the University

  • f Twente Logo at the head entrance at 13:40 hrs

2 Word of welcome Raymond 3 The mission of DS, its organisation, and its position in the faculty EEMCS Raymond 4 Plans for joint research Raymond 5 Plans regarding teaching Raymond 6 Plans for discussing books, per chapter Raymond 7 W.v.t.t.k.

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AGENDA - REVISITED

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing

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AGENDA

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing

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  • Driven by the digitalisation of society
  • Need within EWI for structural availability, development and anchoring of knowledge
  • Information Retrieval, Data Processing and Management
  • Machine Learning – Pattern Recognition – Deep Learning
  • Computational Statistics
  • Image and Signal Processing
  • Sufficient support (bottom up and top down) to set up a ‘group’
  • List of researchers that expressed their interest

⇒Proposal approved by MT

BACKGROUND

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Interdisciplinary Data Science

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ORGANISATION

Group (DMB), permanent staff listed only EWI - Data Science - https://www.utwente.nl/en/eemcs/ds/ Raymond Veldhuis, Luuk Spreeuwers, Didier Meuwly, Chris Zeinstra, Geert-Jan Laanstra, Bertine Scholten Maurice van Keulen, Djoerd Hiemstra, Doina Bucur, Christin Seifert, Jan Flokstra, 1 assistant prof (vac.) Mannes Poel SOR: Nelly Litvak, Jasper Goseling, Marie-Colette van Lieshout, Computational Statistics: 1 full prof (vac), assistant prof (vac) Christophe Brüne, Pranab Mandal, Nirvana Meratnia Zilverling 4 East wing

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ORGANISATION

Group (DMB), permanent staff listed only EWI - Data Science - https://www.utwente.nl/en/eemcs/ds/ Raymond Veldhuis, Luuk Spreeuwers, Didier Meuwly, Chris Zeinstra, Geert-Jan Laanstra, Bertine Scholten Maurice van Keulen, Djoerd Hiemstra, Doina Bucur, Christin Seifert, Jan Flokstra, 1 assistant prof (vac.) Mannes Poel SOR: Nelly Litvak, Jasper Goseling, Marie-Colette van Lieshout, Computational Statistics: 1 full prof (vac), assistant prof (vac) Christophe Brüne, Pranab Mandal, Nirvana Meratnia Zilverling 4 East wing Management Team Secretariat

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  • It is our mission to to work on explainable data science by developing methods for autonomous,

reliable and robust gathering, preparation, and analysis of the data, to enable relevant, trustworthy and explainable results.

  • From https://www.utwente.nl/en/eemcs/ds/

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MISSION

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AGENDA

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing

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RESEARCH

INVENTORY Mathematical modelling Data processing Image &Signal processing ML

Sources

  • Information

systems

  • Sensors
  • Internet
  • Social media

Prepare

  • Search
  • Extract
  • Transform
  • Combine
  • Clean

Analyze

  • Machine

learning

  • Mining
  • Visualize

Use

  • Interpret
  • Deploy
  • Decide
  • Multidisciplinary
  • Work on fundamental aspects

as well as on applications

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  • Resilient, reliable, explaining and substantiating:
  • Providing resiliency against real-world threats to the functioning of smart services.
  • Providing insight in the reliability and accuracy of the outcomes of inferences on data.
  • Providing valuable insight in the why of the outcomes of these inferences.
  • In order to achieve this, we will work on integrated data-driven and model-based approaches

and their theoretical foundations.

  • Distinctiveness:
  • More interdisciplinary.
  • Explicit focus on accountable methods that substantiate their outcomes, rather than on black-

box solutions.

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CHARACTERISTICS

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AGENDA

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing

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  • Master
  • Transition of current Data Science activities in the Master to an integrated track
  • With flavours: Signal and Image processing (EE), AM, CS, BIT.
  • Graduation in different educational programs.
  • Development of new courses
  • Collaboration with BMS and the relation to BIT must also be discussed and defined.
  • Central ’display’ is desirable.
  • Bachelor
  • Minor?
  • Combined track in CS Research Project

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TEACHING

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AGENDA

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing

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  • Plans for setting up joint research
  • Plans for discussion/reading groups
  • Staff meetings: every 6 weeks
  • Outreach (outside EWI, UT)
  • Hiring staff (vacancies: 2 assistant profs, 1 full prof)
  • Rehousing

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COMING UP

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AGENDA

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing

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AGENDA

Number Topic 1 Photo session 2 Welcome 3 DS, background, organisation and mission 4 Research 5 Teaching 6 Plans 7 A.O.B. 8 Closing