Let us introduce: new team members

In the past few months, several new team members have started at Maastricht University, Utrecht University, and VU Amsterdam. The Portal task, the ODISSEI Social Data Science Team (SoDa), and the Distributed Analytics Techniques task are all welcoming new members.

Margherita Martorana
PhD Student, VU Amsterdam
Portal

Margherita Martorana joined ODISSEI as a PhD student at the VU in January. She works on the Portal and Distributed Learning teams. Margherita is originally Italian but has lived in London for eight years before moving to The Netherlands in July 2020. She has a B.Sc. in Biological Sciences and an M.Sc. in Bioinformatics, both received from London universities. She has also worked as a Data Scientist for a government learning platform. Margherita is a big enthusiast of all sciences. What interested her most about the ODISSEI project was its aim to provide an infrastructure for ground-breaking social research. Her motivation is to learn something new every day and challenge herself to accomplish demanding tasks and projects.

Jonathan de Bruin 
Research Engineer, Utrecht University
Social Data Science Team (SoDa)

Jonathan de Bruin works at the ODISSEI Social Data Science Team (SoDa) where he supports researchers with data science and research engineering questions. SoDa’s ambition is to connect data-intensive research to the latest developments in IT and the ODISSEI infrastructure. Next to his work at ODISSEI, Jonathan also works on questions related to open source software, with the FAIR data and Software team at Utrecht University. With the team’s slogan ‘Open is not enough’ Jonathan and the team try to maximise the potential of research data and software. Jonathan also contributes to transparent academic research related to the corona pandemic. One of the ways he does so is through the volunteer project ‘CoronaWatchNL, which earned the Dutch Data Prize in 2020.

Helen Lam
Data Steward
Social Data Science Team (SoDa)

Helen Lam works as a data steward and researcher for the ODISSEI Social Data Science Team (SoDa). Primarily, she works on the Kansenkaart’ project by Bastian Ravesteijn. Helen started working on the Kansenkaart project as a research assistant at Erasmus University Rotterdam. She completed a Master’s degree in Economics and Business, also at Erasmus University.

Leonardo Vida 
Research Engineer, Utrecht University
Social Data Science Team (SoDa)

Leonardo Vida works as a research engineer at the Social Data Science Team (SoDa) of ODISSEI, where he deals with programming challenges related to spatial data analysis and more. He is a recent graduate in applied data science from Utrecht University. Next to working with SoDa, Leonardo, also works as a research engineer within the internal research department at Utrecht University, where he works on supporting research projects within the university, on domains spanning from humanities to computational biology.

Pedro V. Hernández Serrano 
Applied Data Scientist, Maastricht University
Distributed Analytics Techniques

Pedro Hernández Serrano is an applied data scientist at the Institute of Data Science, Maastricht University and works on privacy-preserving distributed analytics techniques. He has a Bachelor’s degree in Actuarial Science and a Master’s degree in Data Science. Pedro contributes to enhancing scientific discovery in societally relevant problems by implementing data science technologies in research. He is one of the core developers of the Data Infrastructure for Law & Policy scholars at Maastricht University and the main Data Engineer of two NWO-IDG projects. Pedro teaches quantitative methods and has specialized in conducting scalable reproducible data analysis on social sciences and humanities data.

Chang Sun 
PhD candidate, Maastricht University
Distributed Analytics Techniques

Chang Sun is a PhD candidate working at the Institute of Data Science at Maastricht University on the Distributed Analytics Techniques team. She works on privacy-preserving data mining and federated/distributed machine learning technologies to solve the problem of analysing sensitive data across multiple independent data parties. She is also developing a personal data vault platform where people can take full control of their own data in order to strengthen and extend the (re-)use of personal data while maximally protecting individuals’ privacy. Chang achieved her Master’s degree in Artificial Intelligence in 2017 and then started her PhD research in the data science domain. Her long-term research goal is to find ways to balance the emerging importance of responsible data practices with the social and scientific value of research. 

Birgit Wouters
PhD candidate, Maastricht University
Distributed Analytics Techniques

Birgit Wouters is a researcher at Maastricht University, and has joined the Distributed Analytics Techniques team. Her research interests centre around data governance and the legal, societal and ethical issues surrounding big data research and privacy. As such, she was responsible for the ethical-legal framework of the FAIR Health-project, a collaboration between IDS, CBS and the Maastricht Study; and of the LIME Project, focusing upon the development of the Personal Health Train. She studied European Law at Maastricht University and International & European Politics at Edinburgh University, before starting her PhD research at Maastricht University, focusing upon the role of the patient and/or citizen in the context of personalized medicine.


Photo thumbnail by Lukas from Pexels