Postdoctoral Researcher

• Sep 2022 - Present

Ph.D. Candidate

• Oct 2017 - Aug 2022

Research focus on privacy-preserving data mining, distributed machine learning. Projects: 1. Analyzing Partitioned FAIR Health Data Responsibly Built a scalable and feasible infrastructure that analyzes data from different data parties in a privacy-preserving manner. This project built a FAIR data station at each data party and send algorithms to them instead of transferring data. 2. Citizen-Centric Data Platform: Empowering Citizens in Responsible Use of Personal Data To… Show more Research focus on privacy-preserving data mining, distributed machine learning. Projects: 1. Analyzing Partitioned FAIR Health Data Responsibly Built a scalable and feasible infrastructure that analyzes data from different data parties in a privacy-preserving manner. This project built a FAIR data station at each data party and send algorithms to them instead of transferring data. 2. Citizen-Centric Data Platform: Empowering Citizens in Responsible Use of Personal Data To build a platform that consists of an integrated set of components for requesting subsets of data stored in personal data vaults and analyzing them in privacy-preserving manner using a combination of SOLID data pods, Personal Health Train technology, and FAIR data and service standards. 3. Distributed Analytics on Educational Data To apply the privacy-preserving distributed analytics technologies to study the impact of the presence of special educational needs (SEN) students on the social and emotional development of students without SEN and teacher work stress. 4. Secure Learning Use Case Study Creating a set of diverse reference use cases to 1) identify important requirements (e.g., scalability, sensitivity) that the desired solution should adhere to; 2) assess how these requirements shape the set of the feasible solutions. 5. Generative Models for Sequential Data Provided an overview of existing deep generative models in sequential data and propose a classification that categorizes the current state-of-the art methods by data type and key technological concepts. 6. Knowledge Graph for CBS Microdata This project mapped metadata of all CBS microdata sets into one knowledge graph in Dutch and English using semantic web technologies and NLP. Researchers can easily query the metadata, explore the relations among multiple datasets, and find the needed variables.

Internship Student

• Jan 2017 - Jul 2017

Master Thesis Internship on Twitter Account Classification. The goal is to classify private, business, non-commercial user in Twitter by using machine learning algorithm. This helps us to understand user behavior in social media such as who is the main spreader and contributor on certain topics. Master Thesis Internship on Twitter Account Classification. The goal is to classify private, business, non-commercial user in Twitter by using machine learning algorithm. This helps us to understand user behavior in social media such as who is the main spreader and contributor on certain topics.

Intern researcher

• Sep 2016 - Jan 2017

Did a research project on a recommendation system for curriculum based on students competence and skills. I have published one paper from this project - "Discovering Hidden Course Requirements and Student Competences from Grade Data." in Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Did a research project on a recommendation system for curriculum based on students competence and skills. I have published one paper from this project - "Discovering Hidden Course Requirements and Student Competences from Grade Data." in Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization.