Yingqian Zhang is as an Assistant Professor in the Information Systems group at Eindhoven University of Technology (TU/e). Her research interests lie in the area of Artificial Intelligence, particularly, machine learning, data-driven optimization, multi-agent system, and algorithm design.
She enjoys optimizing decision making with data, designing efficient algorithms, conducting simulations, and developing models and mechanisms involving cooperative or self-interested players. The application domains of Yingqian’s current research include e-commerce, transportation and logistics, and sharing economy. Her current funded projects examine Prescriptive AI for decision-making in online AD auctions, predictive maintenance, lane selection in transportation, and service logistics.
Yingqian Zhang received her PhD in Computer Science from the University of Manchester, UK. She has 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 in 2015. She also teaches at the Jheronimus Academy of Data Science.
Yingqian is active in the AI community. She is on the board of BNVKI (Benelux Association for Artificial Intelligence), serves yearly as a member of the technical Program Committee for major AI conference such as IJCAI, AAAI, AAMAS, ECAI, and acts as a reviewer for journals including Artificial Intelligence, Autonomous Agents and Multi-agent Systems, IEEE Transactions on TKDE, Journal Distributed Computing. Recently she joined the executive committee of the working group DSO (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.
Optimal display-ad allocation with guaranteed contracts and supply side platformsComputers and Industrial Engineering (2019)
Solving bin-packing problems under privacy preservation: possibilities and trade-offsInformation Sciences (2019)
Remaining useful lifetime prediction via deep domain adaptationarXiv (2019)
A decision support method to increase the revenue of ad publishers in waterfall strategy2019 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, (CIFEr2019) (2019)
A PSO-based algorithm for reserve price optimization in online ad auctions2019 IEEE Congress on Evolutionary Computation (2019)