Yifan Zhu <br/> 朱一凡

Yifan Zhu
朱一凡

Assistant Professor @ BUPT

I currently work as an assistant professor with Beijing University of Posts and Telecommunications. Before that, I was a postdoc research fellow with Department of Computer Science and Technology, Tsinghua University from 2021 to 2023. I received the PhD degree at Beijing Institute of Technology in 2021, and received the bachelor degree at Beijing Information Science & Technology University, in 2016.

My research interests include datamining, recommendation systems, graph representation learning, etc. For my full (and timely) publication list, please refer to my Google scholar .

🔥 News

📚 Publications

2023

  • ICDM 2023 Z. Han, Z. Ou, Y. Zhu, X. Li, and M. Song. FM-IGNN: Interaction Graph Neural Network with Fine-grained Matching for Session-based Recommendation, In Proceedings of the IEEE International Conference on Data Mining (ICDM), 2023. Paper

  • ECML-PKDD 2023 M. Zhou, W. Feng, Y. Zhu, D. Zhang, Y. Dong and J. Tang. Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks, In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD), 2023. Paper (Runner-up best paper award)

  • KDD 2023 Y. Zhu, F. Cong, D. Zhang, W. Gong, Q. Lin, W. Feng, Y. Dong, and J. Tang. WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window, 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’23), 2023. Paper Code (CCF-A)

  • IEEE TKDE Y. Zhu, Q. Lin, H. Lu, K. Shi, D. Liu, J. Chambua, S. Wan, and Z. Niu, Recommending Learning Objects through Attentive Heterogeneous Graph Convolution and Operation-Aware Neural Network, IEEE Transactions on Knowledge and Data Engineering, 2023, 35(4):4178-4189. Paper (CCF-A)

  • IEEE TNNLS G. Shi, Y. Zhu, J. Liu, X. Li. HeGCL: Advance Self-Supervised Learning in Heterogeneous Graph-level Representation, IEEE Transactions on Neural Networks and Learning Systems, 2023. Paper (IF: 14.255)

  • WWW 2023 D. Zhang, Y. Zhu, Y. Dong, Y. Wang, W. Feng, E. Kharlamov, J. Tang. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation, In Proceedings of the Web Conference 2023 (WWW’23), 759–769. Paper Code (CCF-A)

2022

  • CIKM 2022 Z. Huai, Z. Wang, Y. Zhu, P. Zhang. AMinerGNN: Heterogeneous Graph Neural Network for Paper Click-through Rate Prediction with Fusion Query, Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM’22), 4039-4043. Paper

  • BIBM 2022 G. Shi, Y. Zhu, F. Zhang, W. Liu, Y. Yao, X. Li. Fusion Learning of Multimodal Neuroimaging with Weighted Graph AutoEncoder, In proceedings of the International Conference on Bioinformatics and Biomedicine (BIBM’2022), 2467-2473. Paper

  • SIGIR 2022 Q. Lin, J. Liu, F. Xu, Y. Pan, Y. Zhu, L. Zhang and T. Zhao. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’22), 893-903. (CCF-A). Paper

  • IEEE TCSS T. Wang, Y. Zhu, P. Ye, W. Gong, H. Lu, H. Mo, F.-Y. Wang, A New Perspective for Computational Systems:Fuzzy Modeling and Reasoning for Social Computing in CPSS, IEEE Transactions on Computational Social Systems, 2022. Paper

  • IEEE TCSS K. Shi, H. Lu, Y. Zhu, Z. Niu, Application of Social Sensors in Natural Disasters Emergency Management: A Review, IEEE Transactions on Computational Social Systems, 2022. Paper

  • IEEE TCSS D. Liu, Y. Yuan, R. Qin, Y. Zhu, C. Zhang, Z. Niu, A Local Self-Attention Sentence Model for Answer Selection Task in CQA Systems, IEEE Transactions on Computational Social Systems, 2022. Paper

  • IEEE TITS H. Lu, Y. Zhu, Q. Lin, T. Wang, Z. Niu, E. Herrera-Viedma. Heterogeneous knowledge learning of predictive academic intelligence in transportation, IEEE Transactions on Intelligent Transportation Systems, 2022, 23(4):3737-3755. Paper

  • IEEE TCDS G. Shi, Y. Zhu, Z. Chen, J. Liu, X. Li, Are Non-image Data Really Necessary for Disease Prediction with Graph Convolutional Networks?, IEEE Transactions on Cognitive and Developmental Systems, 2022, 15(1):252-260. Paper

2021

  • IEEE TCDS Y. Zhu, X. Li , Y. Sun, H. Wang, H. Guo, and J. Sui, Investigating Neural Substrates of Individual Independence and Interdependence Orientations via Efficiency-based Dynamic Functional Connectivity: A Machine Learning Approach, IEEE Transactions on Cognitive and Developmental Systems, 2022, 14(2):761-771. Paper

  • MIA Y. Zhu, X. Li, Y. Qiao, R. Shang, G. Shi, Y. Shang, and H. Guo, Widespread Plasticity of Cognition-Related Brain Networks in Single-Sided Deafness Revealed by Randomized Window-Based Dynamic Functional Connectivity, Medical Image Analysis, 2021, 73(474):102163. (IF:13.828) Paper

  • KBS Y. Zhu, Q. Lin, H. Lu, K. Shi, P. Qiu, and Z. Niu, Recommending scientific paper via heterogeneous knowledge embedding based attentive recurrent neural networks, Knowledge-Based Systems, 2021, 215: 106744. Paper

  • FGCS Lin, Q., Y. Zhu, H. Lu, K. Shi, and Z. Niu, Improving University Faculty Evaluations via multi-view Knowledge Graph, Future Generation Computer Systems, 2021, 117:181-192. Paper

  • NeuroImage G. Shi, X. Li, Y. Zhu, R. Shang, Y. Sun, H. Guo, J. Sui, The divided brain: Functional brain asymmetry underlying self-construal, NeuroImage, 2021, 240:118382. Paper

  • IP&M K. Shi, Y. Wang, H. Lu, Y. Zhu, Z. Niu, EKGTF: A knowledge-enhanced model for optimizing social network-based meteorological briefings, Information Processing & Management, 2021, 58(4):102564. Paper

  • TCSS H. Lu, Y. Zhu, Y. Yuan, W. Gong, J. Li, K. Shi, Y. Lv, Z. Niu, F.-Y. Wang, Social Signal-Driven Knowledge Automation: A Focus on Social Transportation, IEEE Transactions on Computational Social Systems, 2021, 8(3): 737-753. Paper

  • Y. Mao, Y. Zhu, Y. Liu, Q. Lin, H. Lu, F. Zhang, Classifying user connections through social media avatars and users social activities: a case study in identifying sellers on social media, Enterprise Information Systems, 2021, 16(8-9): 1856420. Paper

2020

  • Y. Zhu, H. Lu, P. Qiu, K. Shi, J. Chambua, Z. Niu, Heterogeneous teaching evaluation network based offline course recommendation with graph learning and tensor factorization, Neurocomputing 415, 84-95. Paper

  • Y. Zhu, S. Zhang, Y. Li, H. Lu, K. Shi, Z. Niu, Social weather: A review of crowdsourcing‐assisted meteorological knowledge services through social cyberspace, Geoscience Data Journal, 2020, 7(1): 61-79. Paper

  • KBS K. Shi, H. Lu, Y. Zhu, Z. Niu, Automatic generation of meteorological briefing by event knowledge guided summarization model, Knowledge-Based Systems, 2020, 192: 105379. Paper

2019

  • ISPA 2019 Y. Mao, Y. Zhu, S. Zhang, D. Zhang, F. Zhang, X. Fan, Detecting interest-factor influenced abnormal evaluation of teaching via multimodal embedding and priori knowledge based neural network, IEEE-ISPA 2019, 1201-1209. Paper

  • ISPA 2019 Y. Li, F. Zhang, Y. Zhu, S. Zhang, Y. Mao, Z. Niu, Chinese Lexical Based Sentiment Analysis Framework in Meteorology, IEEE-ISPA 2019, 1652-1658. Paper

  • Y. Zhu, J. Chambua, H. Lu, K. Shi, Z. Niu, An opinion based cross‐regional meteorological event detection model, Weather, 2019, 74(2): 51-55. Paper

  • FGCS K. Shi, C. Gong, H. Lu, Y. Zhu, Z. Niu. Wide-grained capsule network with sentence-level feature to detect meteorological event in social network, Future Generation Computer Systems, 2020, 102:323-332. Paper

  • ESWA J. Chambua, Z. Niu, Y. Zhu, User preferences prediction approach based on embedded deep summaries, Expert Systems with Applications, 2019, 132: 87-98. Paper

  • Y. Nie, Y. Zhu, Q. Lin, S. Zhang, P. Shi, Z. Niu, Academic rising star prediction via scholar’s evaluation model and machine learning techniques, Scientometrics, 2019, 120(2): 461-476. Paper

  • Q. Lin, Y. Zhu, S. Zhang, P. Shi, Q. Guo, Z. Niu, Lexical based automated teaching evaluation via students’ short reviews, Computer Applications in Engineering Education, 2019, 27(1): 194-205. Paper

🎖 Honors and Awards

  • 2023.10 Runner-up best paper award (ADS Track), ECML-PKDD 2023.

🔍 Educations & Work Experiences

  • 2023.09 - (now), Assistant professor at School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China.
  • 2021.10 - 2023.09, Postdoc research fellow at Department of Computer Science and Technology, Tsinghua University, Beijing, China. (Supervisor: Prof. Jie Tang )
  • 2016.09 - 2021.06, Ph.D. at School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China. (Supervisor: Prof. Zhendong Niu)
  • 2012.09 - 2016.06, B.E. at Computer School, Beijing Information Science & Technology University, Beijing, China.

🎤 Lecture, Talk, and Services

Invited Talks

  • 2023.10, 基础模型时代下隐私保护与可信数据要素流通, 第一届中国（成都）数智金融高峰论坛 Slides

Editor Service

Program Committee & Reviewer Service

  • Program committee member of WWW’24, AAAI’22-24, IJCAI’23-24, ECML-PKDD’22, ICWSM’24
  • Reviewer of IEEE TMC, IEEE TITS, ACM TKDD, IEEE TBD, IEEE TCSS, IEEE TNSE, IEEE TCDS, IEEE TALLIP, IEEE TLT, ACM TALLIP, IEEE TETCI, Expert System with Applications, Computational Intelligence, Scientometics, Neurocomputing, Network: Computation in Neural Systems, Frontiers of Computer Science.