Publications   [] [By Topic] [By Year]     

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* = corresponding author of the paper with students or team members supervised by me. '= co-first authors with equal contribution by alphabetical order. # = authors in alphabetical order    

Distributed and Parallel Computing

• D. Xue, Y. Chen, J. Liu, Y. Zhang, G. Ni, M. Zhang, T. Wo, Z. Zheng, C. Hu, J. Ouyang, R. Yang*. Characterizing and Mitigating Productivity Loss in Large-Scale Model Training: An Empirical Study. in Proc. of the 41th IEEE/ACM ASE 2026

• H. Xue, K. Zhang, X. Zhang, Z. Li, C. Luo, Y. Yang, T. Wo, C. Hu, Y. Li, Y. Zhou, P. Zhang, T. Zhang, R. Yang*. MicroWeaver: A Constraint-Guided Structure-Semantic Aware Approach to Automated Microservice Decomposition. in Proc. of the 41th IEEE/ACM ASE 2026

• Z. Ye, T. Wo, D. Xue, M. Zhang, Y. Teng, C. Hu, R. Yang*. CrossPool: Efficient Multi-LLM Serving for Cold MoE Models through KV-Cache and Weight Disaggregation, arXiv Preprint, 2026

• W. Xiong, Z. Jiang, Z. Ge, X. Wang, C. Luo, T. Wo, C. Hu, R. Yang*. AeroFlow: Accelerating Serverless Workflows through Serialization-Free WebAssembly Execution. in Proc. of the 55th ACM ICPP 2026

• J. Wang, X. Zhou, X. Sun, Y. Zhang, Y. Li, T. Wo, X. Wang, C. Hu, R. Yang. Maestro: Workload-Aware Cross-Cluster Scheduling for LLM-Based Multi-Agent Systems. in Proc. of the 46th IEEE ICDCS 2026

• J. Wang, Y. Zhou, X. Zhou, X. Xie, X. Sun, T. Wo, C. Hu, R. Yang. DeepShare: Assurance-Driven Deep Learning Job Scheduling for Multi-Tenant Clusters. in Proc. of the 28th IEEE CLUSTER 2026

• Y. Zhang, R. Yang*, J. Liu, W. Jiang, T. Ye, Y. Liao, P. Zhang, T. Zhang, K. Shang, T. Wo, C. Hu, C. Song, J. Ouyang. Cuckoo: Deadline-Aware Job Packing on Heterogeneous GPUs for DL Model Training. in Proc. of the 16th ACM SoCC 2025

• Y. Zhang, H. Shen, R. Yang*, D. Tian, Y. Luo, M. Zhang, L. Li, C. Hu, T. Wo, C. Song, J. Ouyang. Cauchy: A Cost-Efficient LLM Serving System through Adaptive Heterogeneous Deployment. in Proc. of the 16th ACM SoCC 2025

• Y. Yang, J. Liu, J. Chen, X. Sun, T. Wo, C. Hu, C. Song, J. Ouyang, R. Yang. KAIR: A Statistical and Causal Approach to Pinpointing Stragglers in Distributed Model Training. In Proc. of the 40th IEEE/ACM ASE 2025

• M. Zhang, G. Li, C. Guo, R. Yang*, S. Wang, H. Bao, X. Li, M. Xu, T. Wo, C. Hu. SuperFE: A Scalable and Flexible Feature Extractor for ML-based Traffic Analysis Applications. In Proc. of the 20th ACM EuroSys 2025

• Z. Liu, R. Yang*, J. Ouyang, W. Jiang, T. Ye, M. Zhang, S. Huang, J. Huang, C. Song, D. Zhang, T. Wo, C. Hu. KALE: Elastic GPU Scheduling for Online DL Model Training. In Proc. of the 15th ACM SoCC 2024

• R. Yang and J. Xu. Resilient QoS-Aware Workload Co-Scheduling and User Anomaly Detection in Shared Computing Clusters, the UK Alan Turing Institute Workshop on Edge-Cloud Infrastructure for Distributed Intelligent Computing, 2023

• Z. Wen, R. Yang*, B. Qian, Z. Wang, H. Peng, J. Xu, A.Y. Zomaya, R. Ranjan. Janus: Latency-Aware Traffic Scheduling for IoT Data Streaming in Edge Environments. IEEE Trans. on Services Computing (TSC), 2023

• R. Yang', J. Zhu', X. Sun, T. Wo, C. Hu, H. Peng, J. Xiao, A. Y. Zomaya, J. Xu. QoS-Aware Co-Scheduling for Distributed Long-Running Applications on Shared Clusters, IEEE Trans. on Parallel and Distributed Systems (TPDS), 2022

• Y. Song, L. Jiao, R. Yang, T. Wo and J. Xu. Incentivizing Online Content Caching in Distributed Edge Networks via Auction-Based Subsidization. 19th IEEE International Conference on Sensing, Communication, and Networking (SECON), 2022

• X. Sun, W. Wang, S. Qiu, R. Yang, S. Huang, J. Xu, Z. Wang. STRONGHOLD: Fast and Affordable Billion-scale Deep Learning Model Training. IEEE/ACM SC 2022

• G. Yeung, B. Borowiec, R. Yang*, A. Friday, R. Harper, P. Garraghan. Horus: Interference-aware and Prediction-based Scheduling in Deep Learning Systems. IEEE Trans. on Parallel and Distributed Systems (TPDS), 2021

• R. Yang, C. Hu, X. Sun, P. Garraghan, T. Wo, Z. Wen, H. Peng, J. Xu and C. Li. Performance-aware Speculative Resource Oversubscription for Large-scale Clusters, IEEE Trans. on Parallel and Distributed Systems (TPDS), 2020

• C. Mommessin', R. Yang'*, N. Shakhlevich, X. Sun, S. Kumar, J. Xiao, J. Xu. Affinity-Aware Resource Provisioning for Long-Running Applications in Shared Clusters. Journal of Parallel and Distributed Computing (JPDC), 2023

• R. Yang', J. Zhu', C. Hu, T. Wo, S. Xue, J. Ouyang and J. Xu. Perphon: a ML-based Agent for Workload Co-location via Performance Prediction and Resource Inference. ACM Symposium on Cloud Computing (SoCC), 2019

• X.Sun, C. Hu, R. Yang*, P. Garraghan, T. Wo, J. Xu, J. Zhu, C. Li. ROSE: Cluster Resource Scheduling via Speculative Over-subscription. in the 38th IEEE ICDCS 2018

• Z. Zhang, C. Li, Y.Tao, R. Yang*, H. Tang, J. Xu. Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale, in the 40th VLDB 2014,

• X. Sun, C. Hu, R. Yang*, P. Garraghan, C. Li. ROSE: Cluster Scheduling through Efficient Resource Overselling, ACM/USENIX SOSP, 2017 (poster)

• R. Yang', J. Zhu', C. Hu, T. Wo, S. Xue, J. Ouyang, J. Xu. Perph: A Workload Co-location Agent with Online Performance Prediction and Resource Inference. IEEE/ACM CCGRID 2021

• R. Yang, Z. Wen, D. McKee, T. Lin, J. Xu and P. Garraghan. Software-Defined Fog Orchestration for IoT Services. Book Chapter, Fog and Fogonomics Challenges and Practices, Wiley, ISBN: 978-1-119-50109-1 [link] [googlebook] [preprint]

• Z. Wen, R. Yang*, P. Garraghan, T. Lin, J. Xu and M. Rovatsos. Fog Orchestration for IoT Services, in IEEE Internet Computing (IC), IEEE Computer Society (SCI-IF = 1.929, Q1) (Highly Cited Paper)

• G. Yeung, B. Borowiec, R. Yang*, A. Friday, R. Harper, P. Garraghan. Horus: An Interference-aware Resource Manager for Deep Learning Systems. International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), 2020

• C. Hu, J. Zhu, R. Yang*, H. Peng, T. Wo, S. Xue, X. Yu, J. Xu, R. Ranjan. Toposch: Latency-Aware Scheduling Based on Critical Path Analysis on Shared YARN Clusters. IEEE Conference on Cloud Computing (Cloud), 2020

• R. Yang, X. Ouyang, Y. Chen, P. Townend, J. Xu. Intelligent Resource Scheduling: a Machine Learning Perspective. in the 12th IEEE SOSE 2018,

• S. Kumar, R. Yang, R. Singh, R. Bahsoon, J. Xu, R. Buyya. MatchCom: Stable Matching-Based Software Services Composition in Cloud Computing Environments. The 24th International Conference on Web Engineering (ICWE), 2024

• N. V. Shakhlevich, T. Erlebach, C. Mommessin, R. Yang, X. Sun, S. Kumar, J. Xiao, J. Xu. Vector Bin Packing for Resource Management in Distributed Systems: A Case Study. The 19th International Workshop on Project Management and Scheduling (PMS). The Association of European Operational Research Societies. 2024

• T. Erlebach#, S. Kumar, C. Mommessin, N. V. Shakhlevich, X. Sun, J. Xiao, J. Xu, R. Yang#. Affinity Aware Scheduling in Distributed Computing via Vector Bin Packing. The 33rd European Conference on Operational Research (EURO 2024 Copenhagen).

• J. Wang, G. Wang, T. Wo, X. Wang and R. Yang*. RESCAPE: A Resource Estimation System for Microservices with Graph Neural Networks and Profile Engine. The 15th IEEE Joint Cloud Conference (JCC) (Best Paper Award)

• W. Peng, J. Wang, T. Wo and R. Yang*. PrecisionProbe: Non-intrusive Performance Analysis Tool for Deep Learning Recommendation Models. The 15th IEEE Joint Cloud Conference (JCC)

• R. Yang. Efficient and Reliable Resource Scheduling at Internet Scale: Theory and Practice, PhD. thesis, 2017 (with Honor, Outstanding Graduate Award of Beijing Graduates)

• R. Yang and J. Xu. Computing at Massive Scale: Scalability and Dependability Challenges, in the 10th IEEE International Symposium on Service Oriented System Engineering (SOSE 2016)

• Y. Wang, R. Yang, T. Wo, W. Jiang, C. Hu. Improving Utilization through Dynamic VM Resource Allocation in Hybrid Cloud Environment, in the 20th IEEE ICPADS 2014,

• W. Wang, C. Hu, T. Wo and R. Yang*. YarnPlus: A Yarn Based Framework for Fine-Grained Resource Sharing in Heterogeneous Computing Environments, in the 11th CCF CNCC 2013,

• S. Xue, C. Hu, J. Zhu, R. Yang*. Shaready: A Resource-Isolated Workload Co-location System. in the 13th IEEE SOSE, 2019

System Dependability

• X. Mou, Z. Wu, C. Luo, S. Chen, X. Liu, C. Hu, R. Yang*. Multi-Modal Anomaly Detection: A Survey. IEEE Trans. on Big Data (TBD), 2026

• X. Mou, R. Wang, T. Wang, Z. Wu, F. Guo, J. Sun, S. Chen, P. Zhang, T. Zhang, T. Wo, H. Peng, C. Hu, X. Liu, R. Yang*. CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments. in Proc. of IEEE/ACM ASE 2026

• R. Shi, S. Lyu, R. Yang, W. Wu, C. Liu, C. Hu, C. Luo. DynCA: An Effective Algorithm for 3-Wise Combinatorial Interaction Testing in Highly Configurable System. in Proc. of IEEE/ACM ASE 2026

• Z. Lin, J. Zhu, M. Zhou, X. Wang, Z. Sun, R. Yang, D. Lo, L. Li. To Run or Not to Run: Analyzing the Cost-Effectiveness of Code Execution in Code Agents. The 35th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2026)

•T. Wang, R. Wang, X. Mou, X. Li, T. Wo, S. Chen, X. Liu, R. Yang. MOC: Mamba-Based Multi-Scale One-Class Time-Series Anomaly Detection. in Proc. of IEEE ICASSP 2026

• F. Yu, C. Huang, R. Yang, H. Cheng, Y. Ding, Y. Ma, K. Wang, Z. Zhang. AutoSecGPU: Lightweight GPU-TEE Made Practical with Automatic Evidence Generation. in Proc. of IFIP SEC 2026

• F. Yu, C. Huang, Z. Hua, Y. Ding, K. Wang, R. Yang, H. Cheng, B. Yu. LGT4CG: Lightweight GPU-TEE for cloud GPUs. Journal of Systems Architecture, 2026

• M. Chen, K. Wang, C. Huang, F. Yu, R. Yang, H. Cheng, M. Chen. LASEFlow: A Label-Aware Security Enhancement Framework for Serverless Workflows. In Proc. of IEEE TrustCom 2025

• X. Sun, X. Liu, Q. Ye, H. Hu, R. Yang, H. He, W. Zhang. DPDeno: A Post-Processing Framework for Releasing Differentially Private Spatio-Temporal Mobility Features. IEEE Transactions on Information Forensics and Security (TIFS), 2025

• Z. Wang, J. Liu, P. Zhang, X. Sun, X. Wang, T. Wo, C. Hu, C. Song, J. Ouyang, R. Yang*. KAIOps: A Platform Solution of End-to-End Multi-Modal AIOps for AI Training at Scale. In Proc. of the 40th IEEE/ACM ASE 2025

• X. Mou, R. Wang, T. Wang, R. Yang*, S. Chen, J. Sun, T. Wo, X. Liu. CAPMix: Robust Time Series Anomaly Detection Based on Abnormal Assumptions with Dual-Space Mixup. arXiv Preprint, 2025

• T. Wang, R. Wang, X. Mou, M. Ma, T. Wo, R. Yang*, X. Liu. An Improved Time Series Anomaly Detection by Applying Structural Similarity. arXiv Preprint, 2025

• Z. Zou, M. Zhang, G. Li, R. Yang, T. Wo, C. Hu, M. Xu. Recent Advances in Programmable Switches Driven Network Security. Journal of Software, 2025 (In Chinese)

• Y. Zhao, M. Zhang, T. Wo, R. Yang, C. Hu. BTDefense: A Priority-Aware Adaptive Strategy Against the Block Table Overflow Attack in vLLM. The 30th Symposium on Operating Systems (SOSP), 2024, poster

• X. Sun, W. Zhang, H. He, R. Yang. A Survey on Differentially Private Methods for Trajectory Data. Journal of Network and Information Security (In Chinese), 2025

• R. Wang, X. Mou, R. Yang*, K. Gao, P. Liu, C. Liu, T. Wo and X. Liu. CutAddPaste: Time Series Anomaly Detection by Exploiting Abnormal Knowledge. In Proc. of the 30th ACM KDD, 2024

• X. Sun, Q. Ye, H. Hu, J. Duan, T. Wo, J. Xu and R. Yang. LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy. In Proc. of IEEE ICDE 2024

• L. He, Y. Yang, Q. Wu, H. Liu, R. Yang, X. Wang, H. Peng, Y. Liao, P. Zhou. BotDGT: Dynamicity-aware Social Network Bot Detection with Dynamic Graph Transformers. In Proc. of the 33rd IJCAI, 2024

• T. Li, Z. Hong, Q. Cai, L. Yu, Z. Wen, and R. Yang*. BISSIAM: Bispectrum Siamese Network Based Contrastive Learning for UAV Anomaly Detection, IEEE Trans. on Knowledge and Data Engineering (TKDE), 2021

• Y. Hei', R. Yang', H. Peng, L. Wang, X. Xu, J. Liu, H. Liu, J. Xu, L. Sun. Hawk: Reliable Android Malware Detection through Heterogeneous Graph Neural Network. IEEE Trans. on Neural Networks and Learning Systems (TNNLS), 2021

• Y. Song, T. Wo, R. Yang*, Q. Shen and J. Xu. Joint Optimization of Cache Placement and Request Routing in Unreliable Networks. Journal of Parallel and Distributed Computing (JPDC), 2021

• Z. Wen, T. Lin, R. Yang*, S. Ji, R. Ranjan, A. Romanovsky, C. Lin, J. Xu. GA-Par: Dependable Microservice Orchestration Framework for Geo-Distributed Clouds, IEEE Trans. on Parallel and Distributed Systems (TPDS), 2019 [full version]

• R. Yang, Y. Zhang, P. Garraghan, Y. Feng, J. Ouyang, J. Xu, Z. Zhang, C. Li. Reliable Cloud Service in Massive-scale Systems through Effective Low-cost Failover. in IEEE Trans. on Services Computing (TSC), 2017 (IF=11.02, CCF-A)

• P. Garraghan, X. Ouyang, R. Yang*, D. McKee, J. Xu. Straggler Root-cause and Impact Analysis for Massive-scale Virtualized Cloud Datacenters, in IEEE Trans. on Services Computing (TSC), 2017 (IF=11.02, CCF-A) (Highly Cited Paper)

• X. Ouyang, P. Garraghan, R. Yang, P. Townend, and J. Xu. Reducing Late-Timing Failure at Scale: Straggler Root-Cause Analysis in Cloud Datacenters, in the 46th IEEE/IFIP DSN 2016 (short)

• P. Garraghan, R. Yang*, Z. Wen, A. Romanovsky, J. Xu, R. Buyya, R. Ranjan. Emergent Failures: Rethinking Cloud Reliability at Scale. IEEE Cloud Computing, 2018 (SCI-IF = 2.929, Q1)

• L. Cui, J. Li, T. Wo, B. Li, R. Yang, Y. Cao, J. Huai. HotRestore: A Fast Restore System for Virtual Machine Cluster, in the 28th USENIX Large Installation System Administration Conference (LISA 2014)

• R. Yang, T. Wo, C. Hu, J. Xu and M. Zhang. D2PS : a Dependable Data Provisioning Service in Multi-tenants Cloud Environment. in the 17th IEEE HASE 2016

• X. Ouyang, C. Wang, R. Yang, P. Townend, J. Xu. ML-NA: a Machine Learning based Node Performance Analyzer Utilizing Straggler Statistics. In the 23th IEEE ICPADS 2017

• R. Yang, J. Ouyang, C. Hu. Fail at Scale. Communications of CCF, 2016 (In Chinese)

• P. Townend, S. J. Clement, D. Burdett, R. Yang*, J. Shaw, B. Slater, J. Xu. Improving Data Center Efficiency Through Holistic Scheduling In Kubernetes. in the 13th IEEE SOSE, 2019

• Y. Li, X. Sun , R. Yang* , X. Sun, S. Chen, S. Wang, A. Bhuiyan, A. Y. Zomaya, J. Xu. GNNRI: detecting anomalous social network users through heterogeneous information networks and user relevance exploration. in the International Journal of Machine Learning and Cybernetics, 2024

AI Algorithms and Applications

• H. Wang, R. Yang*, H. Peng, S. Jie, X. Yu, J. Li, T. Wo, X. Liu, C. Tian, J. Niu. Fed-HDDH: A Hyperbolic Directional Diffusion Hypernetwork for Federated Learning. in Proc. of the ACM MM 2026

• J. Liu, Y. Zhang, T. Huang, W. Xu, R. Yang*. Distilling Cross-Modal Knowledge via Feature Disentanglement. in Proc. of AAAI 2026 (oral)

• H. Wang, P. Liu, J. Sun, R. Yang*, X. Yu, T. Wo, X. Liu, J. Niu, C. Tian. Federated Adversarial Reentangled Feature Augmentation. in Proc. of IEEE ICME 2026

• C. Luo, T. Chen, R. Yang*, W. Wu, C. Hu. GenSC: A Novel and General Local Search Framework for Set Covering Problem. Frontiers of Computer Science (FCS), 2025

• H. Wang, R. Yang*, J. Sun, H. Peng, X. Mou, T. Wo and X. Liu. IOP: An Idempotent-Like Optimization Method on the Pareto Front of Hypernetwork. in Proc. of AAAI 2025 (oral)

• K. Yang, D. Zhang, M. Qi, X. Peng, S. Zhao, R. Yang, X. Yang. AURANAV : Safety-Centric Navigation through Real-Time Familiarity and Social Awareness. In Proc. of IEEE JCC 2025.

• Y. Yang, Q. Wu, B. He, H. Peng, R. Yang, Z. Hao, Y. Liao. SEBot: Structural Entropy Guided Multi-View Contrastive learning for Social Bot Detection. The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

• B. Qian, Y. Xuan, D. Wu, Z. Wen, R. Yang, S. He, J. Chen, and R. Ranjan. Edge-Cloud Collaborative Streaming Video Analytics with Multi-agent Deep Reinforcement Learning. IEEE Network. 2024

• Q. Wu, Y. Yang, H. Liu, R. Yang, Y. Liao, P. Zhou. BotSCL: Heterophily-aware Social Bot Detection with Supervised Contrastive Learning. The 27th International Conference on Pattern Recognition (ICPR)

• J. Zhao, R. Yang, S. Qiu, Z. Wang. Unleashing the Potential of Acquisition Functions in High Dimensional Bayesian Optimization. Transactions on Machine Learning Research (TMLR), 2024

• Y. Yang, R. Yang*, H. Peng, Y. Li, T. Li, Y. Liao, P. Zhou. FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection. ACM WWW 2023

• R. Yang', Y. Yang', Y. Li, K. Cui, Z. Yang, Y. Wang, J. Xu, H. Xie. RoSGAS: Adaptive Social Bot Detection with Reinforced Self-supervised GNN Architecture Search. Transactions on the Web (TWEB), 2022

• D. Zou, H. Peng, X. Huang, R. Yang, J. Li, J. Wu, C. Liu, P. S. Yu. SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. ACM WWW 2023

• J. Zhao, R. Yang, S. Qiu, Z. Wang. Enhancing High-dimensional Bayesian Optimization by Optimizing the Acquisition Function Maximizer Initialization. arXiv Preprint, arXiv:2302.08298, 2023

• Z. Wen, H. Hu, R. Yang*, B. Qian, R. Sham, R. Sun, J. Xu, P. Patel, O. Rana, S. Dustdar, R. Ranjan. Orchestrating Networked Machine Learning Applications using Autosteer. IEEE Internet Computing, 2022

• H. Peng, R. Yang, Z. Wang, J. Li, L. He, P. S. Yu, A. Y. Zomaya, R. Ranjan. LIME: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks. IEEE Trans. on Computers (TC), 2021

• H. Peng, J. Li, Y. Song, R. Yang, R. Ranjan, P. S. Yu, L. He. Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks, ACM Trans. on Knowledge Discovery from Data (TKDD), 2021

• H. Peng, R. Zhang, Y. Dou, R. Yang, J. Zhang, and P. S. Yu. Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks, ACM Trans. on Information Systems (TOIS), 2021 (Hot Paper in ESI)

• Q. Li, H. Peng, J. Li, C. Xia, R. Yang, L. Sun, P. S. Yu, L. He. A Survey on Text Classification: from Traditional to Deep Learning. ACM Trans. on Intelligent Systems and Technology (TIST) (Highly Cited Paper)

• H. Peng, J. Li, Z. Wang, R. Yang, M. Liu, M. Zhang, P. S. Yu, L. He. Lifelong Property Price Prediction: A Case Study for The Toronto Real Estate Market. IEEE Trans. on Knowledge and Data Engineering (TKDE)

• B. Qian, J. Su, Z. Wen, D.N. Jha, Y. Li, Y. Guan, D. Puthal, P. James, R. Yang, A. Y. Zomaya, O. Rana, L. Wang, R. Ranjan. Orchestrating Development Lifecycle of ML-Based IoT Applications: a Survey. ACM Computing Surveys (CSUR), 2020

• H. Peng, J. Li, S. Wang, L. Wang, Q. Gong, R. Yang, B. Li, L. He and P. S. Yu. Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. IEEE Trans. on Knowledge and Data Engineering (TKDE), 2019 (Highly Cited Paper)