UM Data Science Research Seminar: Thursday 23 March
On Thursday 23 March, the Institute of Data Science organizes the monthly UM Data Science Research Seminar, this time in collaboration with the Faculty of Psychology and Neuroscience (FPN).
Date: Thursday 23 March 2023
Time: 12:00 -13:00 (lunch meeting)
Location: PHS1, room C3.015
Speakers are Prof. Elia Formisano ("Semantically-informed deep neural networks for sound recognition") and Ph.D. Candidate Gijs Wijngaard ("Transformer-based automated audio captioning: applications and evaluation metrics").
For more information and abstracts, please visit the event page
Please register by 17 March (strict deadline)
The UM Data Science Research Seminar Series aims to bring (prospective) UM scientists together to share their data science-related research, making these events an ideal opportunity for networking! During the research seminars you can enjoy a free lunch, offered to you by the organizing parties.
WiDS Maastricht Conference 2023
The Institute of Data Science is pleased to announce the FOURTH edition of the WiDS Maastricht Conference 2023, that will take place on Tuesday 7 March 2023 (IN PERSON).
WiDS Maastricht features outstanding data science contributions from women working in data science, AI and related technical fields. This technical conference provides an opportunity to hear about the latest data science related research and connect with others in the field.
This year, the speakers and the audience will focus and reflect on the impact of data science for the social good.
For more information and registration, please visit the event page.
Thesis Defense Dr. Chang Sun
We are proud to announce that Dr. Chang Sun has successfully defended her thesis "Privacy-preserving personal data analysis" on Monday 14 November 2022. Congratulations to Chang and her supervisors Prof. Dr. Michel Dumontier and Dr. Johan van Soest!
An ever-increasing amount of data is generated by our citizens and used in our daily life every single day. These massive amounts of data can be used to improve digital technologies and develop data-driven innovations that can impact every aspect of people’s lives. However, a lack of sharing of, access to, and reuse of data from multiple organizations hinders the analysis possibilities and hence potential insights from the data. Several challenges have been recognized, such as technical barriers, security, data-protection compliance to one or more legal jurisdictions, privacy concerns, and trust issues.
We aim to develop new privacy-preserving data sharing and analysis techniques that strengthen and extend the (re-)use of personal data while maximally protecting individuals’ privacy. To achieve this aim, this thesis addresses the research challenges of personal data sharing and (re-)use from the perspectives of data organizations, scientific researchers, and individuals.
UM Data Science Research Seminar Series
The UM Data Science Research Seminar series serves as a forum to learn about, discuss and critique high impact publications from all facets of Data Science.
Datathons are data-focused hackathons which invites students and faculty members from all backgrounds as well as practitioners from industry and government to participate in a global challenge.