Hello! I am a lecturer in the School of Computer and Electronic Information / School of Artificial Intelligence at Nanjing Normal University. As a member of the Natural Language Processing and Educational Intelligence Research Lab, which is led by Prof. Junsheng Zhou, I am currently working on medical recommendation systems, natural language processing and other directions. I graduated from the DUTIR Lab, Computer Science & Engineering Department at Dalian University of Technology in 2022, advised by Prof. Hongfei Lin. I’m broadly interested in the area of data mining, machine learning and recommender systems. Specifically, my research focuses on:
- Education Agent
- Recommender Systems
- Medical Recommendation
- Natural Language Processing
Research Interests
- Graph Representation Learning, Graph Neural Networks
- Recommender Systems
- Drug Discovery
Academic Service
- Reviewer: AAAI 2022, BIBM 2022, BIBM 2023, BIBM 2024, Journal of Big Data (IF: 10.835), Knowledge and Information Systems (CCF B), Information Science, Neural Computing and Applications
CIPS-IR Committee member (Corresponding)
- Session Chair: BIBM 2022
Selected Publications
- Haifeng Liu, Nan Zhao*, Junsheng Zhou, and Weiguang Qu. “Chiral Molecular Graph Encoder for Medication Recommendation”. BIBM2024. (*corresponding authors)(CCF B).
- Haifeng Liu, Qiuyu Long, and Nan Zhao*. “Dual-Branch Contrast Enhancement for Drug Repositioning”. BIBM2024. (*corresponding authors)(CCF B).
- Yunzhi Qiu, Xiaokun Zhang, Weiwei Wang, Youlin Wu, Bo Xu, Haifeng Liu, Hongfei Lin. “SEDGCN: Sentiment Enhanced Dual Graph Convolutional Networks for Detecting Adverse Drug Reactions”. BIBM 2023. (CCF B).
- Xiaokun Zhang, Bo Xu, Liang Yang, Chenliang Li, Fenglong Ma, Haifeng Liu, Hongfei Lin*(2022). “Price DOES Matter! Modeling Price and Interest Preferences in Session-based Recommendation”. SIGIR 2022. (CCF A).
- Xiaokun Zhang, Hongfei Lin, Bo Xu, Chenliang Li, Yuan Lin, Haifeng Liu, Fenglong Ma(2022). “Dynamic intent-aware iterative denoising network for session-based recommendation”. Information Processing & Management. (CCF B).
- Haifeng Liu, Hongfei Lin, Wenqi Fan, Yuqi Ren, Bo Xu, Xiaokun Zhang, Dongzhen Wen, Nan Zhao, Yuan Lin, Liang Yang*(2022). “Self-supervised learning for fair recommender systems”. Applied Soft Computing. (*corresponding authors)(IF: 8.263).
- Haifeng Liu, Hongfei Lin*, Bo Xu, Nan Zhao, Dongzhen Wen, Xiaokun Zhang, Yuan Lin(2022). “Perceived individual fairness with a molecular representation for medicine recommendations”. Knowledge-Based Systems. (*corresponding authors)(IF: 8.139)
- Haifeng Liu, Yukai Wang, Hongfei Lin*, Bo Xu, Nan Zhao. (2022). “Mitigating Sensitive Data Exposure with Adversarial Learning for Fairness Recommendation Systems”. Neural Computing & Applications. (*corresponding authors)(IF: 5.102)
- Haifeng Liu, Nan Zhao, Xiaokun Zhang, Hongfei Lin*, Liang Yang, Bo Xu, Yuan Lin, Wenqi Fan (2022). “Dual constraints and adversarial learning for fair recommenders”. Knowledge-Based Systems. (*corresponding authors)(IF: 8.139)
- Haifeng Liu, Hongfei Lin*, Chen Shen, Liang Yang, et al (2022). “A network representation approach for COVID-19 drug recommendation”. Methods. (*corresponding authors)(IF: 4.647)
- Haifeng Liu, Hongfei Lin, Chen Shen, Zhihao Yang, Jian Wang, Liang Yang* (2021). “Self-Supervised Learning with Heterogeneous Graph Neural Network for COVID-19 Drug Recommendation”. BIBM 2021 (CCF B). Code (*corresponding authors)
- Haifeng Liu, Hongfei Lin*, Chen Shen, Liang Yang, et al (2020). “Drug Repositioning for SARS-CoV-2 Based on Graph Neural Network”. BIBM 2020 (CCF B). (*corresponding authors)
- Haifeng Liu, Hongfei Lin*, Bo Xu, et al (2020). “Improving Social Recommendations with Item Relationships”. ICONIP 2020 (CCF C). (*corresponding authors)