| 2026 | ACL | Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization. | Xia Jiang, Jing Chen, Cong Zhang, Jie Gao, Chengpeng Hu, Chenhao Zhang, Yaoxin Wu, Yingqian Zhang |
| 2026 | CPAIOR | Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks. | Minshuo Li, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim P. M. Nuijten |
| 2025 | AAAI | Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems. | Igor G. Smit, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim P. M. Nuijten |
| 2025 | CPAIOR | Algorithm Configuration in Sequential Decision-Making. | Luca Begnardi, Bart von Meijenfeldt, Yingqian Zhang, Willem van Jaarsveld, Hendrik Baier |
| 2025 | ECAI | Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration. | Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang |
| 2025 | ICAART | Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks. | Ya Song, Laurens Bliek, Yingqian Zhang |
| 2025 | ICLR | DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints. | Xia Jiang, Yaoxin Wu, Chenhao Zhang, Yingqian Zhang |
| 2025 | ICML | Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization. | Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang |
| 2025 | ISCC | Pair-Bid Auction Model for Optimized Network Slicing in 5G RAN. | Mengyao Li, Sebastian Troia, Yingqian Zhang, Guido Maier |
| 2025 | MICCAI | Contrastive Masked Video Modeling for Coronary Angiography Diagnosis. | Zhiming Shao, Yingqian Zhang, Zechen Wei, Yong Ge, Chen Wang, Guodong Ding, Lei Gao, Liwei Zhang, Yundai Chen, Jie Tian, Hui Hui |
| 2024 | ICAPS | Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning. | Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh |
| 2024 | IJCAI | Cross-Problem Learning for Solving Vehicle Routing Problems. | Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou, Zhiguang Cao, Wen Song, Yingqian Zhang, Senthilnath Jayavelu |
| 2024 | IJCNN | DSD-GAN: Double-Scale Discriminators GAN for Enhanced Chinese Brush Baimiao Painting Colorization. | Xiaoyang Bi, Yingqian Zhang, Sim Kuan Goh |
| 2024 | IJCNN | LMGAN: A Progressive End-to-End Chinese Landscape Painting Generation Model. | Yingqian Zhang, Shaomin Xie, Xiangrong Liu, Nian Zhang |
| 2023 | ACML | Deep Reinforcement Learning for Two-sided Online Bipartite Matching in Collaborative Order Picking. | Luca Begnardi, Hendrik Baier, Willem van Jaarsveld, Yingqian Zhang |
| 2023 | CIBCB | Trustworthy Artificial Intelligence in Medical Applications: A Mini Survey. | Mohsen Abbaspour Onari, Isel Grau, Marco S. Nobile, Yingqian Zhang |
| 2023 | GECCO | Learning to Adapt Genetic Algorithms for Multi-Objective Flexible Job Shop Scheduling Problems. | Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek |
| 2023 | NetSoft | Auction-based network slicing for 5G RAN. | Ligia Maria Moreira Zorello, Kazem Eradatmand, Sebastian Troia, Achille Pattavina, Yingqian Zhang, Guido Maier |
| 2022 | CIBCB | Comparing Interpretable AI Approaches for the Clinical Environment: an Application to COVID-19. | Mohsen Abbaspour Onari, Marco S. Nobile, Isel Grau, Caro Fuchs, Yingqian Zhang, Arjen-Kars Boer, Volkher Scharnhorst |
| 2022 | ICAART | Grouping of Maintenance Actions with Deep Reinforcement Learning and Graph Convolutional Networks. | David Kerkkamp, Zaharah Allah Bukhsh, Yingqian Zhang, Nils Jansen |
| 2021 | IJCNN | A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning. | Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak |
| 2021 | IJCNN | Learning 2-opt Local Search from Heuristics as Expert Demonstrations. | Paulo da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak |
| 2020 | ACML | A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. | Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak |
| 2020 | ACML | Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning. | Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay |
| 2020 | ICAART | Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled. | Herbert van Leeuwen, Yingqian Zhang, Kalliopi Zervanou, Shantanu Mullick, Uzay Kaymak, Tom de Ruijter |
| 2020 | IPMU | Dynamic Pricing Using Thompson Sampling with Fuzzy Events. | Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak |
| 2020 | SMC | Reserve price optimization with header bidding and Ad Exchange. | Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak, Ali Izzet Metin, Gnen Seil Tarakioglu, Cosku Bas |
| 2020 | SMC | Predicting Water Pipe Failures with a Recurrent Neural Hawkes Process Model. | Jeroen Verheugd, Paulo Roberto de Oliveira da Costa, Reza Refaei Afshar, Yingqian Zhang, Sjoerd Boersma |
| 2019 | AAAI | Learning Optimal Classification Trees Using a Binary Linear Program Formulation. | Sicco Verwer, Yingqian Zhang |
| 2019 | CEC | A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions. | Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak |
| 2019 | ICAART | A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. | Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak |
| 2019 | ICAART | Reinforcement Learning Method for Ad Networks Ordering in Real-Time Bidding. | Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak |
| 2019 | ICAART | Boosting Local Search Using Machine Learning: A Study on Improving Local Search by Graph Classification in Determining Capacity of Shunting Yards. | Arno van de Ven, Yingqian Zhang, Wan-Jui Lee |
| 2019 | ICAART | Determining Capacity of Shunting Yards by Combining Graph Classification with Local Search. | Arno van de Ven, Yingqian Zhang, Wan-Jui Lee, Rik Eshuis, Anna Wilbik |
| 2019 | RANLP | Term Based Semantic Clusters for Very Short Text Classification. | Jasper Paalman, Shantanu Mullick, Kalliopi Zervanou, Yingqian Zhang |
| 2019 | SMC | A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand. | Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak |
| 2019 | SMC | Machine Learning based Simulation Optimisation for Trailer Management. | Dylan Rijnen, Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang |
| 2018 | SMC | Shunting Trains with Deep Reinforcement Learning. | Evertjan Peer, Vlado Menkovski, Yingqian Zhang, Wan-Jui Lee |
| 2017 | CPAIOR | Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization. | Sicco Verwer, Yingqian Zhang |
| 2017 | SMC | Modeling participation behavior in repeated task allocations with fuzzy connectives. | Qing Chuan Ye, Yingqian Zhang, Uzay Kaymak |
| 2012 | AAMAS | Revenue prediction in budget-constrained sequential auctions with complementarities. | Sicco Verwer, Yingqian Zhang |
| 2012 | PRIMA | Mechanism for Robust Procurements. | Yingqian Zhang, Sicco Verwer |
| 2010 | ICAART | Coordinating Agents - An Analysis of Coordination in Supply-chain Management Tasks. | Chetan Yadati, Cees Witteveen, Yingqian Zhang |
| 2008 | ECAI | Of Mechanism Design Multiagent Planning. | Roman van der Krogt, Mathijs de Weerdt, Yingqian Zhang |
| 2003 | KI | Monitoring Agents Using Declarative Planning. | Jrgen Dix, Thomas Eiter, Michael Fink, Axel Polleres, Yingqian Zhang |