Xihe Qiu

I am an Associate Professor at School of Electronic and Electrical Engineering, Shanghai University of Engineering Science. I completed my undergraduate studies in Biomedical Engineering at Northeastern University in 2014. Subsequently, I obtained my Ph.D. from the National University of Singapore in September 2018. My research interest is AI for Healthcare, such as artificial intelligence and its applications on healthcare.

Our Team

Key Achievements & Contributions

Academic Publications

In the past five years, I have published over 80 papers in top-tier international conferences and high-impact journals. These include CCF A-ranked conferences such as ICCV, WWW, ICML, KDD, SIGIR, EMNLP, and ICRA, as well as journals such as IEEE Transactions on Emerging Topics in Computational Intelligence and IEEE Transactions on Artificial Intelligence. I am the first or corresponding author on more than 50 of these publications.

Research Grants (as PI)

• National Natural Science Foundation of China (NSFC) - Young Scientists Fund
• Shanghai Natural Science Foundation - General Program
• Shanghai Soft Science Research Project - Young Scientists Program
• Shanghai Rising-Star Program for Young University Teachers
• Completed 5 industry-commissioned projects and internal university grants

Graduate Student Supervision

Supervised over 20 Master's students, with 12 graduates to date. Notable student achievements include:

• Shaojie Shi was admitted to Fudan University and Haoyu Wang was admitted to Tongji University for Ph.D. studies.
• One student was honored as a 'Shanghai Outstanding Graduate'.
• Two students received 'Outstanding Master's Thesis' awards.
• Three students awarded National Scholarships.

Leadership & Key Collaborations

• Leader for the 'Grand Health' initiative at the Shanghai Collaborative Innovation Center for Data Intelligence Technology and Its Applications.
• Overseeing industry-academia-research collaborations with leading medical institutions, including the Eye and ENT Hospital of Fudan University, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Zhongshan Hospital affiliated to Fudan University, and Songjiang District Central Hospital affiliated to Shanghai Jiao Tong University School of Medicine.

Academic & Professional Services

• Editorial Board Member, Complex & Intelligent Systems (CAS Q2 Journal).
• Program Chair for ECAI 2024 and ECAI 2025.
• Long-term reviewer for CCF Class A conferences including KDD, CVPR, ICCV, ICML, ACL, and AAAI.

Join Our Team!

*Opening!* My BIOAIT research group accepts 3-5 master's students annually. If you are interested in my research direction, please feel free to email me for further inquiries.

Recent Group News

*NEWS!* Our work is accepted by Pattern Recognition!(Author: Xihe Qiu,Yingchen Wei,et al.)

*NEWS!* 3 papers are accepted by MICCAI 2025!(Authors: Chen zhan/Teqihao/Bin Li)

*NEWS!* 1 paper is accepted by IROS 2025!(Authors:Haoyu Wang,et al.)

*NEWS!* Our work is accepted by IEEE Transactions on Emerging Topics in Computational Intelligence!(Author: Yongxin Deng,Xihe Qiu Xiaoyu Tan,Yaochu Jin)

*NEWS!* Our work is accepted by IEEE transactions on Artificial Intelligence!(Author: Xihe Qiu, Haoyu Wang, Xiaoyu Tan,Yaochu Jin )

*NEWS!* Our work is accepted by KDD 2025!(Author: Xiaoyu Tan,Haoyu Wang, Xihe Qiu,et al.)

*NEWS!* Our work is accepted by WWW 2025!(Author: Xiaoyu Tan,Bin Li, Xihe Qiu,et al.)

*NEWS!* Our work is accepted as oral by ICRA 2024!(Author: Haoyu Wang, Xiaoyu Tan, Xihe Qiu, Chao Qu)

*NEWS!* Our work is accepted by SIGIR 2024!(Author: Xiaoyu Tan, Leijun Cheng, Xihe Qiu, et. al)

*NEWS!* Our work is accepted as by ICCV 2023!(Author: Xihe Qiu, Shaojie Shi, et. al)

*UPDATES* For all publications, please check my Google Scholar.

Research Topics

Research on Comprehensive Personalized Assisted Diagnosis for Sleep Breathing Disorder Patients.

Participating group member: Yingchen Wei, Bin Li, Yue Zhang.

Collaborator: Eye&ENT hospital of Fudan University, Fudan University.

In response to the practical challenges in diagnosing Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) with invasive treatments and cumbersome examinations, this project focuses on researching an intelligent assisted diagnosis algorithm for OSAHS throughout the entire patient journey. It aims to address the complexities, time-consuming nature, and high manpower costs associated with monitoring multi-channel polysomnography in clinical settings. By constructing a time-series model with high accuracy and generalization performance, the project precisely analyzes and assesses patients' snoring patterns. Leveraging this snoring time-series model, it achieves an accurate classification of disease severity, enabling a streamlined, precise, and cost-effective progressive clinical assisted diagnosis. This advancement aids hospitals in improving diagnostic efficiency and accuracy.

Research on Video Nystagmography Classification for Benign Paroxysmal Positional Vertigo (BPPV).

Participating group member: Shaojie Shi

Collaborator: Eye&ENT hospital of Fudan University, Fudan University

The analysis of eye movement characteristics in BPPV patients is crucial for the diagnosis of BPPV. In clinical practice, eye movement information is typically obtained through positional tests. Video Nystagmography technology significantly enhances the detection rate of BPPV eye movements. In this study, we developed a computer-aided diagnostic method and compared it with manual diagnosis. The computer-aided diagnostic approach demonstrates objectivity, high efficiency, and considerable clinical value compared to traditional manual methods.

Research on Prediction Algorithms Based on Time-Series Models.

Participating group member: Haoyu Wang, Siyue Shao, Jiahui Qian, Yajun Ru

Collaborator: Eye&ENT hospital of Fudan University, Fudan University

Time-series models find extensive application across various domains, notably in the prediction of clinical events and energy-related forecasts. In the clinical domain, leveraging past observed clinical events (such as past medication instructions or previous laboratory measurements) or physiological signals enables the anticipation of a series of future events. This proactive approach enables healthcare practitioners to intervene in advance and prepare resources, thus enhancing the overall quality of patient care and preparedness for clinical events.

Research on Developing More Reliable Large Language Models (LLMs)

Participating group member: Leijun Cheng, Shaojie Shi, Teqi Hao, Haoyu Wang

Collaborator: INF Technology (Shanghai) Co. Ltd, Fudan University

Large Language Models (LLMs), such as ChatGPT, GPT-4, BARD, Claude, have made rapid and remarkable progress in the field of natural language processing. Our aim is to create, enhance, fine-tune, and conduct research by integrating existing LLMs with our medical applications.

Advancements in Image-Assisted Diagnostic Algorithms for Pulmonary Tumors.

Participating group member: Gengchen Ma, Yang Dai

Collaborator: Zhongshan Hospital of Fudan University

Numerous studies have shown that radiomics has significant advantages in the diagnosis and treatment of lung cancer. Radiomics has evolved into a valuable tool for assisting in the diagnosis, analysis, and prediction of lung cancer metastasis. Our objective is to research state-of-the-art algorithms to aid in the diagnostic process.

Research on Reliable and Intelligent Ventilator Systems and Data Analysis.

Participating group member: Teqi Hao, Weiyi Zhao, Sijia Li, Yuxuan Fu

Collaborator: Shanghai Jiao Tong University Affiliated Songjiang Hospital

This research focuses on developing advanced algorithms for respiratory machine control, data-driven optimization of ventilation parameters, and intelligent decision support systems for clinicians. We aim to enhance the efficacy of mechanical ventilation and improve patient outcomes through real-time data analysis and smart adjustments.

Fundings

Publications

Note: * denotes corresponding author. Within each category, conference papers are listed first, followed by journal articles. For a comprehensive list, please refer to my Google Scholar profile.

1. Multimodal Representation Learning and Alignment

1. Xihe Qiu, Shaojie Shi, Xiaoyu Tan, Chao Qu, Zhijun Fang, Hailing Wang, Yongbin Gao, Peixia Wu, and Huawei Li. "Gram-based attentive neural ordinary differential equations network for video nystagmography classification." In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 21339-21348. 2023. (CCF A, First Author)
2. Haoyu Wang, Xiaoyu Tan, Xihe Qiu*, and Chao Qu. "Subequivariant reinforcement learning framework for coordinated motion control." In 2024 IEEE International Conference on Robotics and Automation (ICRA), pp. 2112-2118. IEEE, 2024. (CAAI A , First Corresponding Author)
3. Xiaoyan Jiang, Hang Yang, Kaiying Zhu, Xihe Qiu*, Shibo Zhao, and Sifan Zhou. "PTQ4RIS: Post-Training Quantization for Referring Image Segmentation." In 2025 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2025. (CAAI A, Corresponding Author)
4. Xihe Qiu, Haoyu Wang, Xiaoyu Tan, and Yaochu Jin. "CVDLLM: Automated Cardiovascular Disease Diagnosis with Large-Language-Model-Assisted Graph Attentive Feature Interaction." IEEE Transactions on Artificial Intelligence (2025). DOI: 10.1109/TAI.2025.3527401. (IEEE Transactions, First Author)
5. Haoyu Wang, Xihe Qiu*, Yujie Xiong, and Xiaoyu Tan. "AutoGRN: An adaptive multi-channel graph recurrent joint optimization network with Copula-based dependency modeling for spatio-temporal fusion in electrical power systems." Information Fusion, 117 (2025): 102836. (SCI Q1 Top Journal, Corresponding Author)
6. Xihe Qiu, Jiahui Qian, Haoyu Wang, Xiaoyu Tan, and Yaochu Jin. "An attentive copula-based spatio-temporal graph model for multivariate time-series forecasting." Applied Soft Computing, 154 (2024): 111324. (SCI Q1 Journal, First Author)
7. Xihe Qiu, Siyue Shao, Haoyu Wang, and Xiaoyu Tan. "Bio-K-Transformer: A pre-trained transformer-based sequence-to-sequence model for adverse drug reactions prediction." Computer Methods and Programs in Biomedicine, 260 (2025): 108524. (SCI Q2 Journal, First Author)
8. Yajun Ru, Xihe Qiu*, Xiaoyu Tan, Bin Chen, Yongbin Gao, and Yaochu Jin. "Sparse-attentive meta temporal point process for clinical decision support." Neurocomputing, 485 (2022): 114-123. (SCI Q2 Journal, First Corresponding Author)
9. Gengchen Ma, Xihe Qiu*, and Xiaoyu Tan. "DMFusion: A dual-branch multi-scale feature fusion network for medical multi-modal image fusion." Biomedical Signal Processing and Control, 105 (2025): 107572. (SCI Q2 Journal, Corresponding Author)

2. Multimodal Robust Learning Research

10. Xiaoyu Tan, Shaojie Shi, Xihe Qiu*, Chao Qu, Zhenting Qi, Yinghui Xu, and Yuan Qi. "Self-Criticism: Aligning Large Language Models with their Understanding of Helpfulness, Honesty, and Harmlessness." In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP): Industry Track, pp. 650-662. 2023. (CAAI A, Corresponding Author)
11. Xihe Qiu, Teqi Hao, Shaojie Shi, Xiaoyu Tan, and Yujie Xiong. "Chain-of-LoRA: Enhancing the Instruction Fine-Tuning Performance of Low-Rank Adaptation on Diverse Instruction Set." IEEE Signal Processing Letters, 31 (2024): 875-879. (SCI Q2 Journal, First Author)

3. Large Language Model Logical Reasoning and Continual Learning

12. Xiaoyu Tan, Haoyu Wang, Xihe Qiu*, Yuan Cheng, Yinghui Xu, Wei Chu, and Yuan Qi. "Struct-X: Enhancing Large Language Models Reasoning with Structured Data." In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 2025. (CCF A , Corresponding Author, Accepted)
13. Xihe Qiu, Haoyu Wang, Xiaoyu Tan, and Chao Qu. "ILTS: Inducing Intention Propagation in Decentralized Multi-Agent Tasks with Large Language Models." In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), pp. 3989-3993. 2024. (CCF B Conference, First Author)
14. Xiaoyu Tan, Bin Li, Xihe Qiu*, Yuan Cheng, Yinghui Xu, Wei Chu, and Yuan Qi. "Meta-Agent-Workflow: Streamlining Tool Usage in LLMs through Workflow Construction, Retrieval, and Refinement." In Proceedings of The International Conference of World Wide Web (WWW). 2025. (CCF A Conference, Corresponding Author, Accepted)
15. Yongxin Deng, Xihe Qiu*, Xiaoyu Tan, Chao Qu, Jing Pan, Yuan Cheng, Yinghui Xu, and Wei Chu. "CogniDual Framework: Self-Training Large Language Models within a Dual-System Theoretical Framework for Improving Cognitive Tasks." In ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5. IEEE, 2025. (CCF B Conference, Corresponding Author)
16. Xiaoyu Tan, Leijun Cheng, Xihe Qiu*, Shaojie Shi, Yuan Cheng, Wei Chu, Yinghui Xu, and Yuan Qi. "Enhancing Task Performance in Continual Instruction Fine-tuning Through Format Uniformity." In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 2384-2389. 2024. (CCF A Conference, Corresponding Author)
17. Shaojie Shi, Xiaoyu Tan, Xihe Qiu*, Chao Qu, Kexin Nie, Yuan Cheng, Wei Chu, Xu Yinghui, and Yuan Qi. "ULMR: Unlearning Large Language Models via Negative Response and Model Parameter Average." In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP): Industry Track, pp. 755-762. 2024. (CAAI Class A, Corresponding Author)

4. Reinforcement Learning and Ventilator Decision Support Applications

18. Xiaoyu Tan, Leijun Cheng, Xihe Qiu*, Shaojie Shi, Yuan Cheng, Wei Chu, Yinghui Xu, and Yuan Qi. "Enhancing Personalized Headline Generation via Offline Goal-conditioned Reinforcement Learning with Large Language Models." In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 5762-5772. 2024. (CCF A, Corresponding Author)
19. Yongxin Deng, Xihe Qiu*, Xiaoyu Tan, Yaochu Jin. "FedSlate:A Federated Deep Reinforcement Learning Recommender System." IEEE Transactions on Emerging Topics in Computational Intelligence, pp. 5762-5772. 2024. (CCF A, Corresponding Author)
20. Xiaoyu Tan, Chao Qu, Junwu Xiong, James Zhang, Xihe Qiu*, and Yaochu Jin. "Model-Based Off-Policy Deep Reinforcement Learning with Model-Embedding." IEEE Transactions on Emerging Topics in Computational Intelligence, 8 (2024): 2974-2986. (IEEE Transactions, First Corresponding Author)
21. Xihe Qiu, Xiaoyu Tan, Qiong Li, Shaotao Chen, Yajun Ru, and Yaochu Jin. "A latent batch-constrained deep reinforcement learning approach for precision dosing clinical decision support." Knowledge-Based Systems, 237 (2022): 107689. (SCI Q1 Journal, First Author)
22. Shaotao Chen, Xihe Qiu*, Xiaoyu Tan, Zhijun Fang, and Yaochu Jin. "A model-based hybrid soft actor-critic deep reinforcement learning algorithm for optimal ventilator settings." Information Sciences, 611 (2022): 47-64. (SCI Q1 Journal, First Corresponding Author)
23. Bo Zhang, Xihe Qiu*, and Xiaoyu Tan. "Balancing therapeutic effect and safety in ventilator parameter recommendation: An offline reinforcement learning approach." Engineering Applications of Artificial Intelligence, 131 (2024): 107784. (SCI Q2 Journal, Corresponding Author)

5. Research on Intelligent Diagnostic Methods for Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS)

24. Xihe Qiu, Yingchen Wei, Xiaoyu Tan, Weidi Xu, Haodong Wang, Jingru Ma,Jingjing Huang, Zhijun Fang. "MIMAR-OSA: Enhancing Obstructive Sleep Apnea Diagnosis through Multimodal Data Integration and Missing Modality Reconstruction." In Pattern Recognition . 2025. (SCI Q1 Journal, First Author)
25. Xiaoyu Tan, Bin Li, Xihe Qiu*, Jingjing Huang, Yinghui Xu, and Wei Chu. "Robust Deep Hawkes Process under Label Noise of Both Event and Occurrence." In European Conference on Artificial Intelligence (ECAI). 2024. (CCF B, Corresponding Author)
26. Yingchen Wei, Xihe Qiu*, Xiaoyu Tan, Jingjing Huang, Wei Chu, Yinghui Xu, and Yuan Qi. "An Attentive Dual-Encoder Framework Leveraging Multimodal Visual and Semantic Information for Automatic OSAHS Diagnosis." In ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5. IEEE, 2025. (CCF B, Corresponding Author)
27. Haoyu Wang, Xihe Qiu*, Bin Li, Xiaoyu Tan, and Jingjing Huang. "Multimodal heterogeneous graph fusion for automated obstructive sleep apnea-hypopnea syndrome diagnosis." Complex & Intelligent Systems, 11(1) (2025): 44. (SCI Q2 Journal, First Corresponding Author)
28. Bin Li, Xihe Qiu*, Xiaoyu Tan, Long Yang, Jing Tao, Zhijun Fang, and Jingjing Huang. "An end-to-end audio classification framework with diverse features for obstructive sleep apnea-hypopnea syndrome diagnosis." Applied Intelligence, 55(6) (2025): 427. (SCI Q2 Journal, First Corresponding Author)

Teaching

• Artificial Intelligence Fundamentals (for Undergraduate)
• Artificial Intelligence Fundamentals (All-English) (for international students)
• Machine Learning (for Undergraduate)
• Comprehensive Laboratory on Big Data Architecture (for Undergraduate)
• Artificial Intelligence and Its Applications (for Master)