Trust in Data Science 2019

Level and Target group

The summer school will be open to graduate students, PhD students, postdoctoral researchers and early-career professionals in any field related to data science.

Members of the Doctoral School of (Bioscience) Engineering and Natural Sciences.

The increasingly central role of data in today’s economy, as well as in data-driven research (e.g. the digital humanities, medicine, biology), has brought to the fore important questions around data ownership, data protection, privacy, and fairness of data-driven algorithms. This 3-day workshop for students, early-career researchers, and professionals will cover the technical and legal aspects of how to ensure data science approaches can be trusted to treat individuals fairly and with consideration for privacy. It will be of interest both to researchers into data science algorithm design as well as to researchers working with personal data; the target group of this course will include computer scientists, electrical and biomedical engineers, bioinformaticians, neuroinformaticions, medical informaticians, statisticians, molecular biologists, and other researchers and developers.

Organising & Scientific Committee

  • Prof. Tijl De Bie (Ghent University, BE)
  • Dr. Maryam Fanaeepour (Ghent University, BE)

Programme

For more information and updated website please check this website: 2019 Trust in Data Science Summer School

•    Legalizing Ethics in Data Science
•    Algorithmic Fairness and Validity
•    Privacy in Practice
•    Differential Privacy
The program will run each day from approximately 9.30 to 18.00 except for the last day which will be half day.
There will be a dinner event (still needs to be confirmed) on the evening of Thursday June 20, 2019

Dates and Venue

  • Wednesday June 19 to Friday June 21, 2019
  • Het Pand, Onderbergen 1, 9000 Gent, Belgium

Lecturers

The list of speakers is awaiting confirmation and will be updated as necessary.
Confirmed Speakers:
•    Prof. Graham Cormode - University of Warwick, UK
Graham Cormode is a Professor in Computer Science at the University of Warwick in the UK, where he works on research topics in data management, privacy and big data analysis. Previously, he was a principal member of technical staff at AT&T Labs-Research. His work has attracted over 12,000 citations in the literature and has appeared in over 100 conference papers, 40 journal papers, and been awarded 30 US Patents.
Cormode is the co-recipient of the 2017 Adams Prize for Mathematics for his work on Statistical Analysis of Big Data. He has also edited two books on applications of algorithms to different areas, and co-authored a third. More information can be found at http://dimacs.rutgers.edu/~graham/.
•    Prof. Bettina Berendt - University of Leuven, Belgium
Bettina Berendt is a professor in the Artificial Intelligence / Machine Learning and Data Mining group at the Department of Computer Science at the University of Leuven. Her research interests are data and text mining and in particular the interactions with how people make decisions faced with the artificial and human intelligence they find online. This means investigating how mining affects and interacts with privacy and data protection, how it can liberate and increase diversity – or discriminate, and what ethical choices people face when dealing with data and data science. Within this range of topics and methods, Bettina has concentrated on combining methods from data mining, HCI, and behavioural economics, and investigated questions arising for data subjects, researchers, institutional decision-makers, teachers, and regulators. More information can be found at https://people.cs.kuleuven.be/~bettina.berendt.
Before coming to Leuven, Bettina was a professor in the Information Systems Institute of Humboldt University Berlin. She studied Business, Economics, and Artificial Intelligence in Berlin/Germany, Cambridge/UK and Edinburgh/UK. She obtained her PhD in Computer Science and Cognitive Science from Hamburg University/Germany and her Habilitation in Information Systems from Humboldt University Berlin.
•    Prof. Toon Calders - University of Antwerp, Belgium
Toon Calders obtained his PhD at the University of Antwerp in Belgium in 2003. He is a professor in the Departement Wiskunde – Informatica at the University of Antwerp, also partly employed at Université Libre de Bruxelles (ULB). His research interests include pattern mining, entity resolution, discrimination and fairness aware data mining, and data stream processing.


To be confirmed soon: Legal Speaker

Registration

Registration link: see weblink: 2019 Trust in Data Science Summer School

Registration fee

Free of charge for members of the UGent Doctoral Schools of Engineering and Natural Sciences. External applicants are required to pay a registration fee of €90. Accommodation is not provided.
Participants are asked to complete the application form, including brief statements of their career and motivation. Successful applicants will be notified within 7 days of their application and sent a link for payment (for non-UGent members) to confirm their place.

Number of participants

Maximum 30

Language

English

Evaluation criteria (doctoral training programme)

100% attendance as well as active participation