Yiyuan Yang 杨毅远
Official Website
Ph.D. Candidate, Department of Computer Science, University of Oxford

| Biography | Research Interest | Education and Intern | Selected Publications | Projects | Honors and Awards | Activities and Services | Invited Talks and Lives |

Email: yiyuan.yang@cs.ox.ac.uk (prior)        yyy1997sjz@gmail.com        yangyy19@tsinghua.org.cn
[Google Scholar] [ResearchGate] [GitHub] [LinkedIn] [Wechat] [Chinese Resume]

Biography

 Yiyuan Yang is a D.Phil. (Ph.D.) student in the Department of Computer Science at the University of Oxford, specializing in data mining, time series, audio, signal processing, generative models, and large language models. His work focuses on real-world applications in healthcare, industrial sensors, energy, and traffic. He holds a master’s degree in the Department of Automation at Tsinghua University and a bachelor’s degree from the Experimental Class of the School of Artificial Intelligence and Automation & Qiming College at Huazhong University of Science and Technology. He has also gained valuable experience through internships at Alibaba DAMO Academy and Huawei Noah's Ark Lab.

Yiyuan is an avid open-source contributor, with projects amassing over 25,000 GitHub stars. He has authored two bestselling books based on his tutorials and published over 20 papers in top conferences such as KDD, NeurIPS, AAAI, CIKM, ICASSP, and Interspeech. He also serves as a reviewer for leading journals and conferences, including TPAMI, TKDE, TIFS, TNNLS, TOMM, Neurocomputing, NeurIPS, KDD, WWW, AAAI, SDM, and IJCNN, etc. In his free time, Yiyuan enjoys singing and participating in various sports.

Research Interest

 I work in the field of Intelligent sensing systems, Time series, LLM, Spatio-temporal data mining, Reinforcement learning, Audio, Generative model, Machine learning, and Deep learning. Currently, I focus on the following research topics: I love collaborating with others! If you're interested in working together, feel free to reach out — don't hesitate!😊😊

Education and Intern

Selected Publications

 Please see my full list at [Google Scholar Profile]

Conferences:

    [11] C. Zhang, Y. Zhang, L. Peng, Q. Wen, Y. Yang, C. Fan, M. Jiang, L. Fan and L. Sun, 'Advancing Multivariate Time Series Anomaly Detection: A Comprehensive Benchmark with Real-World Data from Alibaba Cloud,' CIKM 2024 [Link]

    [10] Y. Yang, N. Trigoni, A. Markham, 'Pre-training Feature Guided Diffusion Model for Speech Enhancement,' Interspeech 2024 [Arxiv]

    [9] L Qian, Z Ibrahim, W Du, Y. Yang, R.JB Dobson, 'Unveiling the Secrets: How Masking Strategies Shape Time Series Imputation,' IJCAI24 - AI4TS: AI for time series analysis workshop (IJCAI Workshop 2024) [Arxiv]

    [8] Y. Yang, K. Zhou, N. Trigoni, A. Markham, 'SSL-Net: A Synergistic Spectral and Learning-based Network for Efficient Bird Sound Classification,' ICASSP 2024 [Arxiv]

    [7] C.Zhu, Y.Yang, K. Yang, H. Zhang, Q. Yang, C. L. Philip Chen, 'AI-based Energy Transportation Safety: Pipeline Radial Threat Estimation using Intelligent Sensing System', AAAI 2024 [Arxiv] [Code] [Public Data]

    [6] K.Zhou, J.Zhong, S.Shin, K.Lu, Y.Yang, A.Markham, N.Trigoni, 'DynPoint: Dynamic Neural Point For View Synthesis', NeurIPS 2023 [ArXiv] [Code] [Poster]

    [5] Y.Yang, C.Zhang, T.Zhou, Q.Wen, L.Sun, 'DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection', KDD 2023 [ArXiv] [Code] [Video] [Poster] [Slides]

    [4] Y.Yang, R.Li, Q.Shi, X.Li, G.Hu, X.Li and M.Yuan, 'SGDP: A Stream-Graph Neural Network Based Data Prefetcher,' IJCNN 2023 [ArXiv] [PDF] [Code] [Slides]

    [3] X.Li, Q.Shi, G.Hu, L.Chen, H.Mao, Y.Yang, M.Yuan, J.Zeng and Z.Cheng, 'Block Access Pattern Discovery via Compressed Full Tensor Transformer,' CIKM 2021 [Link] [PDF]

    [2] Y. Yang, Y. Li, H. Zhang, 'Pipeline Safety Early Warning Method for Distributed Signal using Bilinear CNN and LightGBM,' ICASSP 2021 [Link] [PDF] [Poster] [Slides] [Video]

    [1] Y. Yang, Y. Li, T. Zhang, Y. Zhou, and H. Zhang, 'Early Safety Warnings for Long-Distance Pipelines: A Distributed Optical Fiber Sensor Machine Learning Approach,' AAAI 2021 [Link] [PDF] [Poster] [Slides] [Video]

Journals:

    [5] S. Du, H. Zhang, C. Gong, Y. Yang, X. Jiang, L. Zhou, T. Zhang, Y. Ma, J. Meng, Y. Li, 'A Pipeline Inspection Gauge Positioning Method Based on Distributed Fiber Optic Vibration Sensing,' IEEE Sensors Journal (IEEE SENS J), 2024. (Q1, IF=4.3) [Link]

    [4] C. Gong*, Y. Yang*, H. Zhang, J. Meng, Y. Ma, S. Du, Y. Li, 'A Pipeline Intrusion Detection Method Based on Temporal Modeling and Hierarchical Classification in Optical Fiber Sensing,' IEEE Sensors Journal (IEEE SENS J), 2024. (Q1, IF=4.3, equal contribution) [Link]

    [3] C. Zhu, Y. Pu, Y. Yang, Z. Lyu, C. Li, Q. Yang, 'Localizing and tracking of in-pipe inspection robots based on distributed optical fiber sensing,' Advanced Engineering Informatics (AEI), 2024. (Q1, IF=8.8) [Link] [PDF]

    [2] Y. Yang, H. Zhang, Y. Li, 'Pipeline Safety Early Warning by Multi-feature-fusion CNN and LightGBM Analysis of Signals from Distributed Optical Fiber Sensors,' IEEE Transactions on Instrumentation and Measurement (IEEE T INSTRUM MEAS), 2021. (Q1, IF=5.6) [Link] [PDF]

    [1] Y. Yang, H. Zhang, Y. Li, 'Long-Distance Pipeline Safety Early Warning: A Distributed Optical Fiber Sensing Semi-Supervised Learning Method,' IEEE Sensors Journal (IEEE SENS J), 2021. (Q1, IF=4.3) [Link] [PDF]

Book:

PrePrint:

    [5] Y. Yang, Z. Wu, Y. Chu, Z. Chen, Z. Xu, Q. Wen, 'Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives,' 2024. [ArXiv]

    [4] Z. Z. Darban, Y. Yang, G. I. Webb, C. C. Aggarwal, Q. Wen, M. Salehi, 'DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series,' 2024. [ArXiv]

    [3] W. Du*, J. Wang*, L. Qian*, Y. Yang*, F. Liu, Z. Wang, Z. Ibrahim, H. Liu, Z. Zhao, Y. Zhou, W. Wang, K. Ding, Y. Liang, B. A. Prakash, Q. Wen, 'TSI-Bench: Benchmarking Time Series Imputation,' 2024. [ArXiv] [Code]

    [2] Y. Yang, M. Jin, H. Wen, C. Zhang, Y. Liang, L. Ma, Y. Wang, C. Liu, B. Yang, Z. Xu, J. Bian, S. Pan, Q. Wen, 'A Survey on Diffusion Models for Time Series and Spatio-Temporal Data,' 2024. [ArXiv] [Github Repo]

    [1] Z.Zhong, Z.Yu, Y.Yang, W.Wang, K.Yang, 'PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly Detection,' 2024. [ArXiv]

Projects
  • LeeDL-Tutorial: A Chinese deep learning tutorial and it has already collected stars and forks on GitHub, which includes an an e-book and codes. Here are some links to our book. [Douban] [Dangdang] [Jingdong]
  • Easy-RL: A reinforcement learning tutorial and it has already collected stars and forks on GitHub, which includes an e-book and an online tutorial. Also, there is an online tutorial collaboration with Baidu PaddlePaddle AI Studio, and more than 2,000 learners participated in this class. Here are some links to our book. [Douban] [Taobao] [Dangdang] [Jingdong]
    Our book topped the list of new computer books on Dangdang and the list of AI-field New books on Jingdong within ten days. The number of related tweet reads exceeded 100,000, and it was recommended to the libraries of the North China Electric Power University, Shanghai Ocean University, Tsinghua University. Also, it is included in the National Library of China, Library of Tsinghua University, Library of Shanghai Jiao Tong University, Library of Zhejiang University, Library of Chinese Academy of Sciences, Library of Oxford Merton College, and so on. The electronic version has been downloaded over 10,000 times, and the paper version won the PTP key book selection and Excellent book for 2022 Q1th in PTP.
  • Academic Trends Analysis: A data-mining-based tutorial on the analysis of academic trends of arxiv platform. I am the main person in charge. Here is a video and a competition on Alibaba Tianchi platform. More than 4,300 teams participated in this competition. Here are some introductions about our tutorial. [Poster] [Link1] [Link2]
  • Ensemble Learning: An ensemble learning tutorial. There is a video of the case study and an introduction to our tutorial. [Link]

Honors and Awards
  • 2023, 2022 Bestselling Book (Easy-RL：强化学习教程) and Influential Author, Epubit, PTPress.[Link][Picture1][Picture2][Certification][Trophy]
  • 2022, Clarendon Scholar, University of Oxford.
  • 2022, Outstanding Graduate, Beijing.
  • 2022, Outstanding Master's Thesis, Tsinghua University.
  • 2022, Outstanding Graduate, Department of Automation, Tsinghua University.
  • 2022, Internship First-class Scholarship, SIGS, Tsinghua University. (15,000 CNY)
  • 2022, Excellent book's author for 2022 Q1th in PTP, China. [Picture]
  • 2021, China National Scholarship.
  • 2021, Datawhale Contributor.
  • 2020, National Second Prize in the 17th National Postgraduate Mathematical Modelling Competition.
  • 2020, Second-class Scholarship, Tsinghua University.
  • 2020, Kaggle Competitions Expert, Ranking Top 1,000 (0.67%).
  • 2019, Outstanding Graduate, Huazhong University of Science and Technology.
  • 2018, First Prize in the 13th National Student Smart Car Competition, Wireless Energy Saving Category (National Champion).
  • 2018, First-class (Grand prize) Goodix Scholarship （15,000 CNY）.
  • 2018, National Encouragement Scholarship, Ministry of Education in China.
  • 2017, First Prize in South China of the 12th National Student Smart Car Competition, Optoelectronic Balance Category.

Activities and Services
  • Program Committee Member of WWW 2025.
  • Program Committee Member of AAAI 2023, 2024 and 2025.
  • Program Committee Member of SIGKDD 2023 and 2024.
  • Program Committee Member of NeurIPS 2023 and 2024.
  • Program Committee Member of SDM 2024.
  • Program Committee Member of 9th&10th SIGKDD workshop on Mining and Learning from Time Series (MILETS).
  • Technical Program Committee Member of IJCNN2023.

  • Reviewer of IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
  • Reviewer of ACM Transactions on Multimedia Computing Communications and Applications (TOMM).
  • Reviewer of Journal of Medical Internet Research.
  • Reviewer of IEEE Transactions on Information Forensics & Security (TIFS).
  • Reviewer of IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Reviewer of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
  • Reviewer of IEEE/CAA Journal of Automatica Sinica.

  • 2024.04-06, Teaching Assistant of ”Machine Learning” lecture at Department of Computer Science Oxford.
  • 2024.04-06, Teaching Assistant of ”Artificial Intelligence” lecture at Department of Computer Science Oxford.
  • 2020, Teaching assistant of Nicholas Lane from University of Cambridge about 'Introduction to Deep Learning'.
  • 2020, Teaching assistant of Rakesh Kumar from UIUC about 'Artificial Intelligence for Undergraduate'.

  • 2023.03-2024.03, MCR Social Secretary in Merton College, University of Oxford.
  • 2020.06-Now, Datawhale member (an open-source AI organization), helped data science fans get involved in the AI community.
  • 2019-2022, Member of the Tsinghua University Shenzhen TAP Choir.
  • 2019, Debate chairman of the Shenzhen government-sponsored university debate tournament. [Picture]
  • 2017, Top 10 Singers of the School of Artificial Intelligence and Automation, HUST. [Link]
  • 2015-2019, Member of the College's hosting team and hosted two welcome parties and a graduation party.

Invited Talks and Lives