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. Her research expertise is largely in the area of Artificial Intelligence – machine learning and multi-agent systems. Yingqian is particularly interested in data-driven optimization (or prescriptive analytics), optimization and coordination in multi-agent system, using techniques from data mining and machine learning, algorithmic design, mathematical modelling, and applied game theory. She enjoys optimizing decision making with big 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, manufacturing, and sharing economy. Current project examine Data driven decision-making in e-commerce and Data analytics for 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 at Erasmus University Rotterdam from 2010 to 2015, and as a postdoc researcher in the Algorithmics group at TU Delft. She was a faculty research assistant in the Institute for Advanced Computer Studies at University of Maryland, College Park, USA in 2004. She is part of Business Process Intelligence and Smart Mobility research clusters at the Information Systems group and also teaches at the Jheronimus Academy of Data Science and is on the board of BNVKI (Benelux Association for Artificial Intelligence). Yingqian regularly contributes to leading publications and reviews papers for several journals such as Artificial Intelligence, IEEE Transactions on TKDE, Journal of Parallel Computing and Journal Distributed Computing and is a member of the technical Program Committee for more than 20 conferences, including International Joint Conference on Autonomous Agents and Multi-Agent Systems, International Symposium on Intelligent Distributed Computing and International Conference on Integration of AI and OR Techniques in Constraint Programming.
A Branch-and-Price approach to find optimal decision trees(2018)
Modeling participation behavior in repeated task allocations with fuzzy connectives2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 (2017)
Fair task allocation in transportationOmega : The International Journal of Management Science (2017)
Auction optimization using regression trees and linear models as integer programsArtificial Intelligence (2017)
Learning decision trees with flexible constraints and objectives using integer optimization14th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR 2017) (2017)
- Design of Service Operations
- Business Intelligence
- Business Analytics
No ancillary activities