Oudemanhuispoort, Amsterdam, Netherlands

Past ADS Event: Coffee & Data on Personalisation & Recommendations

Room C0.17, Oudemanhuispoort 4-6, Amsterdam


Access to information is increasingly being shaped by personalised recommendations. People worry about tunnel vision and being caught in a filter bubble. In this ADS Coffee & Data we will address Personalisation and Recommendations in the development of algorithms, and the implications on society of the surge in personalisation.


08:45 – 09:00 Welcome reception with coffee

09:00 – 09:05 Introduction by Maarten de Rijke (Informatics Institute, UvA)

09:05 – 09:35 Julia Kiseleva (TU/e & UserSat) Understanding & Predicting User Satisfaction on Mobile Devices

09:35 – 10:05 Anne Schuth (Blendle) Recommending News

10:05 – 10:20 Coffee break

10:20 – 10:50 Xinyi Li (Informatics Institute, UvA) Personalisation & Academic Search

10:50 – 11:20 Balazs Bodo (Institute for Information Law, UvA) Personalised Communication from a User’s Perspective

11:20 – 11:30 Open discussion & wrap-up

11:30 – Drinks and snacks


Amsterdam Data Science accelerates data science research by connecting, sharing and showcasing world-class technology, expertise and talent from Amsterdam on a regional, national and international level. Our research enables business and society to better gather, store, analyse and present data in order to gain valuable insights and make informed decisions.


ADS is an initiative of:

• Informatics Institute (IvI), Universiteit van Amsterdam (UvA)

• Amsterdam Business School and Amsterdam School of Economics, Faculty of Economics and Business, UvA

• Computer Science, Vrije Universiteit (VU) Amsterdam

• Hogeschool van Amsterdam (HvA)

• Centrum Wiskunde en Informatica (CWI)

We organise Coffee & Data meetings and seminars on cutting-edge research, technologies and best practices.

We invite you to:

• share the data challenges in your organisation with the ADS community

• discover innovative ways to apply data science across fields

• network and discuss leading issues with students and top data scientists