| 2026 | CaiSE | Time Series Foundation Models for Process Model Forecasting. | Yongbo Yu, Jari Peeperkorn, Johannes De Smedt, Jochen De Weerdt |
| 2025 | IJCAI | Capturing Individuality and Commonality Between Anchor Graphs for Multi-View Clustering. | Zhoumin Lu, Yongbo Yu, Linru Ma, Feiping Nie, Rong Wang |
| 2024 | ICCAD | GACER: Granularity-Aware ConcurrEncy Regulation for Multi-Tenant Deep Learning. | Yongbo Yu, Fuxun Yu, Zhi Tian, Xiang Chen |
| 2024 | ICPM | Multidimensional Process Model Forecasting (MuDiPMF). | Yongbo Yu |
| 2024 | ICPM | Multivariate Approaches for Process Model Forecasting. | Yongbo Yu, Jari Peeperkorn, Johannes De Smedt, Jochen De Weerdt |
| 2023 | DAC | EagleRec: Edge-Scale Recommendation System Acceleration with Inter-Stage Parallelism Optimization on GPUs. | Yongbo Yu, Fuxun Yu, Xiang Sheng, Chenchen Liu, Xiang Chen |
| 2022 | CEC | A Genetic Programming-Based Hyper-Heuristic Approach for Multi-Objective Dynamic Workflow Scheduling in Cloud Environment. | Yongbo Yu, Tao Shi, Hui Ma, Gang Chen |
| 2022 | WWW | Powering Multi-Task Federated Learning with Competitive GPU Resource Sharing. | Yongbo Yu, Fuxun Yu, Zirui Xu, Di Wang, Minjia Zhang, Ang Li, Shawn Bray, Chenchen Liu, Xiang Chen |
| 2021 | CEC | Achieving Multi-Objective Scheduling of Heterogeneous Workflows in Cloud through a Genetic Programming Based Approach. | Yongbo Yu, Hui Ma, Gang Chen |
| 2019 | AAAI | Network Structure and Transfer Behaviors Embedding via Deep Prediction Model. | Xin Sun, Zenghui Song, Junyu Dong, Yongbo Yu, Claudia Plant, Christian Bhm |
| 2019 | CEC | Achieving Flexible Scheduling of Heterogeneous Workflows in Cloud through a Genetic Programming Based Approach. | Yongbo Yu, Yalian Feng, Hui Ma, Aaron Chen, Chen Wang |