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"I find that the harder I work, the more luck I seem to have." Thomas Jefferson Associate Professor, School of Software, Beihang University, China Co-Director of Reliable, Automated and Intelligent Distributed Systems Lab (RAIDS Lab) Office: D306 New Main Building Location: #37 Xueyuan Rd., Haidian District, Beijing, China Email: {renyuyang, renyu.yang} AT buaa DOT edu DOT cn (main) or renyu.yang1 AT gmail DOT com |
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[News] [Bio] [Research Interest] [Experience] [Publications] [Team] [Research Grants] [Teaching and Presentations] [Professional Services] [Misc] What's New (26/09/2024) A new approach to defense attacks to LLM serving has been accepted by, and will be presented in the poster session of ACM SOSP 2024. (26/09/2024) Our work on Elastic GPU Scheduling for Online DL Model Training is accepted by ACM SoCC 2024. Big Congrats to Ziyang, Weihan and Tianyu! (22/08/2024) Our work on Advanced Feature Engineering for Intelligent Traffic Analysis Applications is accepted by ACM EuroSys 2025. Big Congrats! (20/07/2024) Our work on GNN-based resource estimation for microservices received the best paper award of IEEE JCC 2024. Congrats to Jinghao! (17/05/2024) Two papers are accepted by ACM KDD 2024. Big congrats to Rui, Xudong and Yingguang! (16/04/2024) Our work on Dynamic Graph Transformers for Bot Detection is accepted by IJCAI 2024. (08/12/2023) Our work on Recovering from Poisoning Attacks is accepted by ICDE 2024. (29/08/2023) Our work on IoT streaming management is accepted by IEEE Trans. on Services Computing. ~$ No news is good news...Check older events. Short Bio I am an Associate Professor and Co-Director of Reliable, Automated and Intelligent Distributed Systems Lab (RAIDS Lab) at Beihang University, China. Before moving back to Beijing, I worked in the UK as a lead Research Fellow funded by the UK EPSRC (2020-2023), with the School of Computing and Leeds Institute for Data Analytics (LIDA), both at the University of Leeds, and as a research scientist (2018-2020) at Edgetic Ltd., a UK-based high-tech spin-out company that employs distributed computing, machine learning, and hardware-software co-designing to reshape the future of data center efficiency and intelligence. Prior to this, I was a research scientist and lead project manager with the Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC), Beijing, China. When I was a PhD student, I was also with Alibaba Group (2014-2016) and engaged in the development and research on intelligent resource scheduling and performance optimization for computing infrastructures at Internet scale. My research interests include large-scale dependable distributed systems, trustworthy data-centric engineering, deep learning systems and applications such as graph representation learning, anomaly detection, etc. I have published 70+ refereed journal and conference papers (Googe Scholar 3,000+ citations, h-index=26, as of Sept. 2024), including top ACM/IEEE Transactions and conference proceedings such as TPDS, TC, TKDE, TNNLS, TSC, TOIS, ACM Computing Surveys (CSUR), EuroSys, SC, SoCC, ICDCS, DSN, VLDB, ICDE, WWW, KDD, IJCAI, etc. I received the Best Paper Award of IEEE ISADS 2013 and IEEE JCC 2024, and awarded Alan Turing Institute Post-Doctoral Enrichment Award 2022 and the Grand Class of Scientific and Technological Progress Award of Chinese Institute of Electronics of year 2017 (the only grand class award since the award is established) for the key contribution to the reliable resource management at massive scale and its industrial and societal impact. I co-founded the highly successful and internationally leading research consortium COLAB between Leeds, Alibaba and Beihang University. I am currently acting as an associate editor of ACM Computing Surveys, and on the program committees of many conferences, including IJCAI, ECAI, AAAI, CLOUD, etc., I was also the program/area chair of multiple conferences. My official university web page in Chinese is here 中文简介 Research Interests Broadly, I am interested in designing system modules and/or mechanisms for tackling trade-offs in efficiency, performance, reliability and cost for distributed and parallel computing systems at scale such as cloud computing, big data, deep learning training/inference, IoT, etc. My research mainly focuses on: • Enhanced resource efficiency of large-scale computing infrastructures: QoS-aware resource management [VLDB'14, ICDCS'18, SoCC'19, TPDS'20a, CCGRID'21, TPDS'22a, TSC'23, EuroSys'25], DL model training acceleration [TPDS'22b,SC'22,SoCC'24], and multi-objective optimization [TPDS'20b, JPDC'21, SECON'22, JPDC'23], etc.; • Enhanced system dependability: fault tolerance and failure recovery [VLDB'14,LISA'14,HASE'16,TSC'17, DSN'16,TSC'19], anomaly detection [TNNLS'21, TKDE'21, TWEB'22, WWW'23b, IJCAI'24, KDD'24b] and dependability modeling [ICDE'24, SOSP'24 poster] • Enhanced intelligent systems and applications: data-centric engineering [SOSE'16,CSUR'20,TKDE'23], graph representation learning [TC'21,TOIS'21,WWW'23a, KDD'24a], etc. Education • 2011.9 - 2017.2: PhD. Computer Science (with Distinction Honor), supervised by Prof. Jie Xu and Prof. Tianyu Wo, Beihang University, China • 2011.9 - 2017.1: Exchange PhD. Student (funded by China 973 iVCE Grant and EPSRC CoLab Grant), supervised by Prof. Jie Xu and Dr. Paul Townend, University of Leeds, UK • 2007.9 - 2011.6: BSc. Computer Science (equivalent to 1st Class Honours), supervised by Prof. Tianyu Wo, Beihang University, China Work Experience • 2023.5 - present: Associate Professor, School of Software, Beihang University, Beijing, China • 2020.9 - 2023.4: Lead Research Fellow, University of Leeds, Leeds, UK • 2018.6 - 2020.8: Research Scientist, Edgetic Ltd., UK and Adjunct Research Fellow at University of Leeds, Leeds, UK • 2018.2 - 2018.2: Visiting Researcher (work with Dr. Peter Garraghan), Lancaster University, Lancashire, UK • 2016.4 - 2016.5: Visiting Researcher (work with Dr. Zhenyu Wen), University of Edinburgh, Edinburgh, UK • 2017.3 - 2018.5: Research Scientist and Project Manager, Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC), Beijing, China • 2014.2 - 2016.2: R&D Intern (Mentored by Zhuo (Joe) Zhang and Chao Li), Fuxi Distributed Scheduling Group, Alibaba Group, Beijing, China • 2011.9 - 2017.2: Teaching and Research Assistant, Team Leader, Networked Computing Group, Beihang University, Beijing, China Selected Recent Publications • 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. ACM EuroSys 2025 (CCF A) • 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. ACM SoCC 2024 (CCF B, premier conference on Cloud) • 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. ACM KDD 2024 (CCF A) • 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. ACM KDD 2024 (CCF A) • 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. IEEE ICDE 2024 (CCF A) • 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 TSC 2023 (CCF A) • 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 (CCF A) • Y. Yang, R. Yang, Y. Li, H. Peng, T. Li, Y. Liao, P. Zhou. FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection. ACM WWW 2023 (CCF A) • J. Zhu, R. Yang, 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 TPDS 2022 (CCF A) • X. Sun, W. Wang, S. Qiu, R. Yang, S. Huang, J. Xu, Z. Wang. STRONGHOLD: Fast and Affordable Billion-scale Deep Learning Model Training. ACM/IEEE SC 2022 (CCF A) • G. Yeung, B. Borowiec, R. Yang, A. Friday, R. Harper, P. Garraghan. Horus: Interference-Aware and Prediction-Based Scheduling in Deep Learning Systems. IEEE TPDS 2021 (CCF A) • 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 TKDE 2021 (CCF A) • Y. Hei, R. Yang, H. Peng, L. Wang, X. Xu, J. Liu, H. Liu, J. Xu, L. Sun. Hawk: Rapid Android Malware Detection through Heterogeneous Graph Neural Network. IEEE TNNLS 2021 (CAAI A/CORE A*, IF14.255) • 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 TC 2021 (CCF A) • H. Peng, R. Zhang, Y. Dou, R. Yang, J. Zhang, and P. S. Yu. Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks. ACM TOIS 2021 (CCF A) • 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 TPDS 2020 (CCF A) • 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 TPDS 2019 (CCF A) • X. Sun, C. Hu, R. Yang, P. Garraghan, T. Wo, J. Xu, J. Zhu, C. Li. ROSE: Cluster Resource Scheduling via Speculative Over-subscription (poster, demo). IEEE ICDCS 2018 (CCF B/CORE A) ACM SOSP 2017 poster (CCF A) • 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. IEEE TSC 2017 (CCF A) • More publications: [Complete List] [DBLP] [Googe Scholar] Selected Research Grants I had the opportunity to work closely with many institutes around the world and engaged in many government/industry funded research projects to solve real-world problems with innovative cloud and analytic technologies. Ongoing • Effective Scheduling for Multi-tenant AI Clusters (¥0.3M), funded by National Natural Science Foundation of China, PI, 2025-2027 • Time Series Anomaly Detection for Managing Data and Devices in Production Process at Scale (¥0.3M), funded by Beijing Natural Science Foundation, PI, 2025-2027 • Enabling Generic LLMs on PaddlePaddle and AI Chips (¥6.4M), funded by Beijing Municipal S&T Commission and Baidu Inc., Co-I, 2024-2025 • Enhancing Model Training and Inference (¥0.5M), funded by Company X's Research Programme, PI, 2024 - 2025 • LLMs-Assisted Information Retrieval Platform (¥0.2M), funded by CAE, PI, 2024 • Efficient Resource Scheduling for Intelligent Computing Infrastructures (¥0.2M), funded by Advanced Multidisciplinary Research Programme, Beihang University, PI, 2024 - 2025 • Cloud Native Technology: Theory and Practice (¥100K), funded by Digital Textbook Funding Programme, Beihang University, PI, 2024 • Anomaly Management and Decision Making in Massive Custom Manufacturing (¥1.8M), funded by National Key Research and Development Programme, Co-author and Key Member, 2024 - 2026 • Making Model Training More Reliable in Large-Scale AI Clusters (¥0.4M), funded by Huawei, Co-author and Key Member, 2024 - 2025 Completed • Essentials of Modern Cloud Computing (¥400K), funded by Core Curriculum Redefined Programme, National College of Engineering Excellence, Co-I, 2023 - 2024 • Algorithmic Scheduling Support for Efficient AI Model Training (¥300K), funded by Kuaishou Research Funding, Co-PI, 2023 - 2024 • Resilient Multi-Agent Deep Reinforcement Learning for Green Logistics Scheduling, funded by the Turing Enrichment Scheme, the Alan Turing Institute, PI, 2022.3 - 2022.10 • New Edge-Cloud Infrastructure for Distributed Intelligent Computing (£55K), funded by Turing Pilot Project, the Alan Turing Institute, Co-I, 2022.1 - 2023.4 • Algorithmic Support for Massive Scale Distributed Systems (EP/T01461X/1, £1.1M) funded by UK Engineering and Physical Sciences Research Council (EPSRC), co-author and project leader, 2020.9 - 2023.4 • Farm Observatory Instrumentation (£4M+), University of Leeds, module leader, 2021.3 - 2023.4 • Server Modelling Capability (No.45904, £300K), funded by Innovate UK Programme, UKRI, co-author and module leader, 2020.2 - 2020.8 • Boden Type Data Center One (No.768875, €2.87M), funded by European Comission’s Horizon 2020 Programme (Horizon 2020), module leader, 2018.6 - 2019.12 • Pin the Tail: Understanding Straggler Manifestation in Internet-based Distributed Systems (EP/P031617/1, £97K), UK Engineering and Physical Sciences Research Council (EPSRC), module leader, 2017.9 - 2019.12 • Cloud Operating System - Multiple-grained Resource Management and Scheduling (No. 2016YFB1000503), supported by National Key Research and Development Programme, co-author, project leader/coordinator, 2016.6 - 2018.5 • Storage Model and Mechanism for Joint Clouds (No. 2016YFB1000103), supported by National Key Research and Development Programme, co-author, project leader/coordinator, 2016.5 - 2017.11 • On-demand Resource Aggregation and Execution in Massive-scale iVCE Environments (No.2011CB302602), supported by China 973 Fundamental Research and Development Programme, co-author, project leader/coordinator, 2012.1 - 2015.9 • ChinaCloud Phase II: Fundmental Key Software for Cloud Platforms (No.2013AA01A213), supported by National 863 Hi-Tech Research and Development Programme, key member, 2013.1 - 2014.1 • ChinaCloud Phase I: Resource Virtualization and Scheduling (No. 2011AA01A202), supported by National 863 Hi-Tech Research and Development Programme, key member, 2011.9 - 2013.12 Research Team PhD Students • Yuzheng Zhang (2025.9- , BeihangU) • Junhong Liu (2024.9- , BeihangU) • Huaqiang Qiu (2024.9- , BeihangU) • Rui Wang (2023.9- , BeihangU, w/ Prof. Xudong Liu): KDD'24, FCS'24, ICASSP'23, SDM'23 • Hui Wang (2023.9- , BeihangU, w/ Prof. Xudong Liu) • Yihui Zhang (2023.9- , BeihangU, w/ Prof. Tianyu Wo) • Jinghao Wang (2023.5- , BeihangU, w/ Prof. Chunming Hu and Dr. Xu Wang): JCC'24 Best Paper • Yang Zhang (2023.9- , BeihangU, w/ Prof. Chunming Hu) • Yingguang Yang (2021.7-, USTC, w/ Prof. Yong Liao and Dr. Pengyuan Zhou): TWEB'23, WWW'23, arXiv'23, IJCAI'24, KDD'24 MSc Students • [Class 2022] Weihan Jiang, Tianyu Ye, Ziyang Liu, Di Wang (co-supervised w/ Prof. Tianyu Wo/Chunming Hu) • [Class 2023] Zhida Jiang, Yilong Li, Zeying Wang (co-supervised w/ Prof. Tianyu Wo/Chunming Hu) • [Class 2024] Zexin Wu; Shiyi Huang (w/ Dr. Xu Wang), Yujie Wang, Yuxuan Chen (w/ Prof. Tianyu Wo/Xudong Liu) • [Class 2025] Yitang Yang • [Part Time] Yao Zhang, Lu Pei, Xiaoyu Liu, Tianyou Zeng, Zhiqi Zhang, Haiyang Tang Team Alumni: ~$ alumni Teaching and Presentations • Essentials of Modern Cloud Computing (Graduate Level, National College of Engineering Excellence, with Prof. Chunming Hu and co), Spring 2024 • Foudations of Cloud Computing (Undergraduate Level, BeihangU), Spring 2024 • Foudations of Software Engineering (Undergraduate Level, BeihangU), Spring 2024 • Scientific Research Class (Undergraduate Level, BeihangU), Autumn 2023/2024 • Service Computing (Graduate Level, BeihangU, with Dr. Xu Wang), Autumn 2023, Autumn 2024 • Operating Systems (XJCO2211, Undergraduate Level, UoLeeds, with Prof. Jie Xu), Autumn 2020-2022 • Essentials of Cloud Computing (CS61839, Graduate Level, BeihangU, with Prof. Chunming Hu), Spring 2017 • Talks given in different venues such as academic conferences or industrial meeting-ups can be found here: ~$ talks Selected Professional Services • Associate Editor of ACM Computing Surveys (CSUR) • Lead Guest Editor: "Machine Learning for Dependable Edge Computing Systems and Services" Special Issue in the journal of Big Data and Cognitive Computing (BDCC), (SCI-indexed) • Guest Editor: "Machine Intelligent Information and Efficient Systems" Special Issue in the journal of Electronics (SCI-indexed, IF=2.690) • Review Editor@Editorial Board: Frontiers in Big Data, Frontiers in High Performance Computing • Program Chair: IEEE International Conference on Joint Cloud Computing (JCC) 2020, 2019, etc. • Area/Track Chair: IEEE International Conference on Cloud Computing (CLOUD) 2021. • PC Member: IJCAI, ECAI, AAAI, CLOUD, UCC, BDCAT, HPCC, etc. • Journal Reviewers: TPDS, TDSC, TC, TKDE, TSC, TSE, TCC, TKDD, CSUR, etc. • More professional services can be found here: ~$ services Selected Awards • Best Paper Award of IEEE Joint Cloud Conference (JCC), 2024 • UK Alan Turing Institute Post-Doctoral Enrichment Award, 2022 • IEEE Outstanding Service Award, IEEE JCC-SOSE, 2020 • The Grand Class of Scientific and Technological Progress Award of Chinese Institute of Electronics, 2017 (2017年度中国电子学会科技进步特等奖) • The State Scientific and Technological Progress Award, 1st Prize Nominee, 2018 (2018年度国家科学进步一等奖提名) • Outstanding Graduate Award of Beijing Graduates, 2017 • Guanghua Scholarship Award for outstanding students, 2014 • Best Paper Award of the IEEE 11th International Symposium on Autonomous Decentralized System(ISADS), 2013 • Excellent Academic Award of The Institute of Advanced Computing Technology, Beihang University • Excellence Student Scholarship of Beihang University • Second Prize of Fengru Cup, 2010, 2009 Misc Outside of work, I really enjoy [News] [Bio] [Research Interest] [Experience] [Publications] [Team] [Research Grants] [Teaching and Presentations] [Professional Services] [Misc]
Updated by Aug. 2024
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