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Yingqian Zhang (pronounce: [Ying-Chyen Jahng]) is an Associate Professor in the Information Systems group at Eindhoven University of Technology (ºÚÁϸ£ÀûÍø). Her research interests lie in the area of Artificial Intelligence for decision-making, particularly, machine learning, deep reinforcement learning, (trustworthy) data-driven optimization, and socially aware algorithms, and their applications in various problem domains, including logistics, transportation, manufacturing, and public service. 

She has developed a range of state-of-the-art data-driven optimization algorithms for decision-making that integrate deep learning and reinforcement learning to tackle complex, dynamic, and uncertain environments.  These advances enable adaptive, efficient, and robust decision making beyond traditional optimization methods. In addition, her algorithmic design extends beyond purely economic objectives to explicitly incorporates social values, such as fairness and transparency, establishing frameworks that ensure AI-driven decisions are not only effective but also safe, human-in-the-loop, and socially responsible.

SUPERVISION

Yingqian Zhang is promotor of 
- Abdo Abouelrous
- Luca Begnardi
- Xia Jiang
- Chengpeng Hu
- Minshuo Li
- Jesse van Remmerden
- Bart von Meijenfeldt
- Igor Smit

I optimize decisions in a data-rich environment using AI.

Yingqian Zhang received her PhD in Computer Science from the University of Manchester, UK.  She  worked as an Assistant Professor in Econometrics Institute a t Erasmus University Rotterdam, and as a postdoc researcher in the Algorithmics group at TU Delft. She was a visiting professor in the Institute for Advanced Computer Studies at University of Maryland, College Park, USA.  

Yingqian is the Chair of the Benelux Association for Artificial Intelligence (, and on the Technical Board for the European Big Data Value Association ().  She is an associate editor of journal Annals of Mathematics and Artificial Intelligence, and serves yearly as a member of the technical Program Committee for major AI conference such as IJCAI, AAAI, AAMAS, ECAI.  She is on the executive committee of the working group (Data Science meets Optimisation) of EURO (Association of European Operational Research Societies) to promote collaboration between AI and OR communities on the direction of machine learning and optimization.