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

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 University of 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 Raymond EEMCS 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.

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 3

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 4

BACKGROUND  Driven by the digitalisation of society  Need within EWI for structural availability, development and anchoring of knowledge }  Information Retrieval, Data Processing and Management Interdisciplinary  Machine Learning – Pattern Recognition – Deep Learning Data Science  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 5

ORGANISATION EWI - Data Science - https://www.utwente.nl/en/eemcs/ds/ Group (DMB), permanent staff listed only 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.) Zilverling 4 Mannes Poel East wing SOR: Nelly Litvak, Jasper Goseling, Marie-Colette van Lieshout, Computational Statistics: 1 full prof (vac), assistant prof (vac) Christophe Brüne, Pranab Mandal, Nirvana Meratnia 6

Management Team Secretariat ORGANISATION EWI - Data Science - https://www.utwente.nl/en/eemcs/ds/ Group (DMB), permanent staff listed only 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.) Zilverling 4 Mannes Poel East wing SOR: Nelly Litvak, Jasper Goseling, Marie-Colette van Lieshout, Computational Statistics: 1 full prof (vac), assistant prof (vac) Christophe Brüne, Pranab Mandal, Nirvana Meratnia 7

MISSION  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/ 8

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 9

RESEARCH Mathematical Data INVENTORY modelling processing • Multidisciplinary ML • Work on fundamental aspects as well as on applications Image &Signal processing Sources Prepare Analyze Use • Information • Search • Machine • Interpret systems learning • Extract • Deploy • Sensors • Mining • Transform • Decide • Internet • Visualize • Combine • Social media • Clean 10

CHARACTERISTICS  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. 11

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 12

TEACHING  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 13

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 14

COMING UP • 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 15

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 16

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 17