Kai He

Kai He

Saw Swee Hock School of Public Health

Dr. He Kai earned his Ph.D. from the School of Computer Science and Technology, Xi’an Jiaotong University, under the supervision of Prof. Li Chen (recipient of China’s Young Thousand Talents Award), and completed a research visit at Nanyang Technological University with Prof. Erik Cambria (IEEE Fellow). He is currently a postdoctoral researcher at the National University of Singapore, School of Public Health, specializing in medical artificial intelligence and natural language processing (NLP).

Dr. He has established himself as an independent researcher with a strong foundation in NLP and large language models, complemented by impactful applications in healthcare. He has published over 45 peer-reviewed papers, including articles in top-tier venues such as Nature Cancer, IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Affective Computing, and Information Fusion. His work includes two ESI Highly Cited Papers, a Best Paper Award in IEEE Transactions on Affective Computing. His leading projects, notably the Intelligent Telephone Triage in Pre-Hospital Emergency Care with the Singapore Civil Defence Force, have translated cutting-edge AI into practice, reducing triage error rates. The project received the Provost’s Innovation Chair Professor Award, was commended by Singapore’s Health Minister, showcased at national healthcare innovation events, and he was received by Deputy Prime Minister Mr. Gan Kim Yong as the project representative.

Beyond publications, Dr. He demonstrates leadership in both research and service. He serves as an Associate Editor for IEEE Transactions on Affective Computing, co-chairs the NLP-SIG workshop and Precision Medicine workshop of BIBM, Are-Chair of LREC 2026, and reviews for leading journals such as Information Fusion, TNNLS, and TAC. He also contributes to program committees of ACL, EMNLP, IJCAI, SIGIR, and WWW. As a mentor, he has supervised PhD students to co-author multiple publications.

For his full (and timely) publication list, please refer to my Google scholar.

🔥 News

  • 2026.04:  🎉🎉 Our paper on vision transformer quantization is accepted by Pattern Recognition. Congrats to Dr. Kang.
  • 2026.03:  🎉🎉 Our paper on multi-view brain network foundation model is released as an arXiv preprint. Congrats to Dr. Xu.
  • 2026.03:  🎉🎉 Our paper on interpretable medical deepfake detection is released as an arXiv preprint.
  • 2026.02:  🎉🎉 Our paper on recovering coherent affective patterns is accepted by AAAI 2026.
  • 2026.02:  🎉🎉 Our paper on meta-cognitive activation trajectory in R1-style LLMs is released as an arXiv preprint.
  • 2026.02:  🎉🎉 Our survey paper on LLM reasoning in healthcare and medicine is released as a TechRxiv preprint.
  • 2026.01:  🎉🎉 Our paper on multi-agent adaptive reasoning for automated prompt optimization is accepted by AAAI 2026.
  • 2026.01:  🎉🎉 Our paper on memory-driven scientific reasoning benchmark is released as an arXiv preprint.

📝 Publications

2026

  • Yan Kang, Shouhao Xu, Qika Lin, Kai He, Zhan Gao, Zhuangzhuang Chen, Bin Pu. MTLQ-ViT: Multi-Granularity Tail-Enhanced Logarithmic Quantization for Vision Transformers [J]. Pattern Recognition, 2026: 113769.

  • Huiting Huang, Tieliang Gong, Kai He, Wen Wen, Weizhan Zhang, Mengling Feng. Recovering Coherent Affective Patterns: Addressing Modality Missing in Multimodal Sentiment Analysis [C]. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2026: 21957–21965.

  • Jian Zhang, Zhangqi Wang, Haiping Zhu, Kangda Cheng, Kai He, Bo Li, Qika Lin, Jun Liu, Erik Cambria. MARS: Multi-Agent Adaptive Reasoning with Socratic Guidance for Automated Prompt Optimization [C]. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2026: 16307–16315.

  • BrainPrompt+: Multi-Level Brain Prompt Learning for Knowledge-Guided Neurological Disorder Identification [J]. Google Scholar, 2026.

  • Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction [J]. Google Scholar, 2026.

  • -Bench: Benchmarking Memory-Driven Scientific Reasoning via Anchor and Attractor Activation [J]. Google Scholar, 2026.

2025

  • Towards Unified Neurosymbolic Reasoning on Knowledge Graphs [J]. Google Scholar, 2025.

  • Exploring cognitive difference in poetry collection via large language models and metaphors: A case study of the book of songs [J]. Google Scholar, 2025.

  • DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole-Slide Image Survival Prediction [J]. Google Scholar, 2025.

  • Bridging whole slide images and large language model for slide-level question answering [J]. Google Scholar, 2025.

  • Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI [J]. Google Scholar, 2025.

  • Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint [J]. Google Scholar, 2025.

  • ALPaCA: Adapting Llama for Pathology Context Analysis to enable slide-level question answering [J]. Google Scholar, 2025.

  • A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models [J]. Google Scholar, 2025.

  • A foundation model for chest x-ray interpretation with grounded reasoning via online reinforcement learning [J]. Google Scholar, 2025.

  • Zeyu Gao, Anyu Mao, Yuxing Dong, Hannah Clayton, Jialun Wu, Jiashuai Liu, Chunbao Wang, Kai He, Tieliang Gong, Chen Li, Mireia Crispin-Ortuzar. SMMILe Enables Accurate Spatial Quantification in Digital Pathology Using Multiple-Instance Learning [J]. Nature Cancer, 2025, 6: 2025–2041.

  • Xiaobao Wang, Meng Ge, Lingshan Li, Di Jin, Kai He, Erik Cambria. Global Entity Relationship Enhancement Network for Multimodal Sarcasm Detection [J]. IEEE Transactions on Affective Computing, 2025, Online.

  • Jialun Wu, Xin Mei, Kai He, Jiaxing Xu, Qika Lin, Zeyu Gao, Rui Mao. Neuro-Symbolic AI in Healthcare [C]. 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025, Accepted.

  • Huiting Huang, Tieliang Gong, Kai He, Jialun Wu, Erik Cambria, Mengling Feng. Robust Multimodal Sentiment Analysis via Double Information Bottleneck [J]. Information Fusion, 2025: 103964.

  • Qika Lin, Yifan Zhu, Xin Mei, Ling Huang, Jingying Ma, Kai He, Zhen Peng, Erik Cambria, Mengling Feng. Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey [J]. Information Fusion, 2025, 116: 102795.

  • Xiang Lan, Feng Wu, Kai He, Qinghao Zhao, Shenda Hong, Mengling Feng. Gem: Empowering MLLM for Grounded ECG Understanding with Time Series and Images [C]. Advances in Neural Information Processing Systems (NeurIPS), 2025, Accepted.

  • Jiaxing Xu, Mengcheng Lan, Xia Dong, Kai He, Wei Zhang, Qingtian Bian, Yiping Ke. Multi-Atlas Brain Network Classification through Consistency Distillation and Complementary Information Fusion [J]. IEEE Journal of Biomedical and Health Informatics (JBHI), 2025, Online.

  • Jialun Wu, Kai He, Zeyu Gao, Xuequn Shang, Mengling Feng. Towards Smarter Clinical Predictions: Foundation Models for Integrating Multi-Source Domain Knowledge in EHRs [J]. IEEE Journal of Biomedical and Health Informatics (JBHI), 2025, Online.

  • Kai He, Qika Lin, Hao Fei, Eng Siong Chng, Dehan Hong, Marcus Eng Hock Ong, Mengling Feng. InTriage: Intelligent Telephone Triage in Pre-Hospital Emergency Care [C]. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025, Accepted.

  • Zeyu Gao, Kai He, Weiheng Su, Ines P. Machado, William McGough, Mercedes Jimenez-Linan, Brian Rous, Chunbao Wang, Chengzu Li, Xiaobo Pang, Tieliang Gong, Ming Y. Lu, Faisal Mahmood, Mengling Feng, Li Chen, Mireia Crispin-Ortuzar. ALPaCA: Adapting Llama for Pathology Context Analysis to Enable Slide-Level Question Answering [J]. Nature Cancer, 2025, Accepted.

  • Zhan Gao, Ling Huang, Qika Lin, Bin Pu, Kai He, Mengling Feng, Kenli Li. Domain-Continual Learning for Multi-Center Anatomical Detection via Prompt-Enhanced and Densely-Fused MedSAM [J]. Information Fusion, 2025: 103614.

  • Zhihui Chen, Kai He, Yucheng Huang, Yunxiao Zhu, Mengling Feng. DivScore: Zero-Shot Detection of LLM-Generated Text in Specialized Domains [C]. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025, Accepted.

  • Jialun Wu, Xin Mei, Rui Mao, Kai He, Erik Cambria. TAKECare: A Temporal-Hierarchical Framework with Knowledge Fusion for Personalized Clinical Predictive Modeling [J]. Information Fusion, 2025: 103620.

  • Wenhui Hou, Kai He, Rui Mao, Jianqiang Wang, Xiaokang Wang, Mengling Feng. Multi-Granularity Semantic Extraction and Multi-Task Fusion for Chinese Medical Entity Normalization [J]. Expert Systems with Applications, 2025: 129088.

  • Kai He, Jiaxing Xu, Qika Lin, Wenqing Wang, Zeyu Gao, Jialun Wu, Yucheng Huang, Mengling Feng. External Retrievals or Internal Priors? From RAG to Epitome-Augmented Generation by Fuzzy Selection [J]. IEEE Transactions on Fuzzy Systems, 2025.

  • Jialun Wu, Kai He, Rui Mao, Xuequn Shang, Erik Cambria. Harnessing the Potential of Multimodal EHR Data: A Comprehensive Survey of Clinical Predictive Modeling for Intelligent Healthcare [J]. Information Fusion, 2025: 103283.

  • Kai He, Yucheng Huang, Wenqing Wang, Delong Ran, Dongming Sheng, Junxuan Huang, Qika Lin, Jiaxing Xu, Wenqiang Liu, Mengling Feng. Crab: A Novel Configurable Role-Playing LLM with Assessing Benchmark [C]. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025: 15030–15052.

  • Qika Lin, Tianzhe Zhao, Kai He, Zhen Peng, Fangzhi Xu, Ling Huang, Jingying Ma, Mengling Feng. Self-Supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models [C]. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025: 13587–13602.

  • Jiaxing Xu, Kai He, Yue Tang, Wei Li, Mengcheng Lan, Xia Dong, Yiping Ke, Mengling Feng. BrainPrompt: Multi-Level Brain Prompt Enhancement for Neurological Condition Identification [C]. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025, Accepted.

  • Hui Bao, Kai He, Yige Wang, Zeyu Gao. Exploring Cognitive Difference in Poetry Collection via: A Case Study of the Book of Songs [J]. Cognitive Computation, 2025, 17(3): 106.

  • Zeyu Gao, Kai He, Weiheng Su, Ines P. Machado, William McGough, Mercedes Jimenez-Linan, Brian Rous, Chunbao Wang, Chengzu Li, Xiaobo Pang, Tieliang Gong, Ming Y. Lu, Faisal Mahmood, Mengling Feng, Li Chen, Mireia Crispin-Ortuzar. Bridging Whole Slide Images and Large Language Model for Slide-Level Question Answering [J]. Cancer Research, 2025, 85(8_Supplement_1): 2438–2438.

  • Qika Lin, Kai He, Yifan Zhu, Fangzhi Xu, Erik Cambria, Mengling Feng. Cross-Modal Knowledge Diffusion-Based Generation for Difference-Aware Medical VQA [J]. IEEE Transactions on Image Processing, 2025: 2421–2434.

  • Yuchen Zhang, Zeyu Gao, Kai He, Chen Li, Rui Mao. From Patches to WSIs: A Systematic Review of Deep Multiple Instance Learning in Computational Pathology [J]. Information Fusion, 2025: 103027.

  • Rui Mao, Mengshi Ge, Sooji Han, Wei Li, Kai He, Luyao Zhu, Erik Cambria. A Survey on Pragmatic Processing Techniques [J]. Information Fusion, 2025, 114: 102712.

  • Kai He, Rui Mao, Qika Lin, Yucheng Ruan, Xiang Lan, Mengling Feng, Erik Cambria. A Survey of Large Language Models for Healthcare: From Data, Technology, and Applications to Accountability and Ethics [J]. Information Fusion, 2025, 118: 102963.

2024

  • PROMISE: A pre-trained knowledge-infused multimodal representation learning framework for medication recommendation [J]. Google Scholar, 2024.

  • MetaPro 2.0: Computational metaphor processing on the effectiveness of anomalous language modeling [J]. Google Scholar, 2024.

  • Language modeling on tabular data: A survey of foundations, techniques and evolution [J]. Google Scholar, 2024.

  • Integrating K+ entities into coreference resolution on biomedical texts [J]. Google Scholar, 2024.

  • Contrasformer: a brain network contrastive transformer for neurodegenerative condition identification [J]. Google Scholar, 2024.

  • Accurate spatial quantification in computational pathology with multiple instance learning [J]. Google Scholar, 2024.

  • A survey on semantic processing techniques [J]. Google Scholar, 2024.

  • J. Xu, Kai He, M. Lan, et al. Contrasformer: a brain network contrastive transformer for neurodegenerative condition identification [C]. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024: 2671–2681.

  • Y. Li, X. Ma, X. Zhou, Kai He， et al. Integrating K+ Entities into Coreference Resolution on Biomedical Texts [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024.

  • R. Mao, Kai He, C. Ong, et al. MetaPro 2.0: Computational metaphor processing on the effectiveness of anomalous language modeling [C]. Findings of the Association for Computational Linguistics (ACL), 2024: 9891–9908.

  • J. Wu, X. Yu, Kai He, et al. Promise: A pre-trained knowledge-infused multimodal representation learning framework for medication recommendation [J]. Information Processing & Management, 2024, 61(4): 103758.

  • R. Mao, Kai He, X. Zhang, et al. A survey on semantic processing techniques [J]. Information Fusion, 2024, 101: 101988.

2023

  • Virtual prompt pre-training for prototype-based few-shot relation extraction [J]. Google Scholar, 2023.

  • The biases of pre-trained language models: An empirical study on prompt-based sentiment analysis and emotion detection [J]. Google Scholar, 2023.

  • Template-free prompting for few-shot named entity recognition via semantic-enhanced contrastive learning [J]. Google Scholar, 2023.

  • Neuro-symbolic sentiment analysis with dynamic word sense disambiguation [J]. Google Scholar, 2023.

  • MetaPro Online: A computational metaphor processing online system [J]. Google Scholar, 2023.

  • MEGACare: Knowledge-guided multi-view hypergraph predictive framework for healthcare [J]. Google Scholar, 2023.

  • X. Zhang, R. Mao, Kai He, et al. Neuro-symbolic sentiment analysis with dynamic word sense disambiguation [C]. Findings of the Association for Computational Linguistics: EMNLP, 2023: 8772–8783.

  • J. Wu, Kai He, R. Mao, et al. MEGACare: Knowledge-guided multi-view hypergraph predictive framework for healthcare [J]. Information Fusion, 2023, 100: 101939.

  • Kai He, R. Mao, Y. Huang, et al. Template-free prompting for few-shot named entity recognition via semantic-enhanced contrastive learning [J]. IEEE Transactions on Neural Networks and Learning Systems, 2023.

  • R. Mao, X. Li, Kai He, et al. MetaPro Online: A computational metaphor processing online system [C]. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023.

  • Kai He, Y. Huang, R. Mao, et al. Virtual prompt pre-training for prototype-based few-shot relation extraction [J]. Expert Systems with Applications, 2023, 213: 118927.

  • R. Mao, Q. Liu, Kai He, et al. The biases of pre-trained language models: An empirical study on prompt-based sentiment analysis and emotion detection [J]. IEEE Transactions on Affective Computing, 2022, 14(3): 1743–1753.

2022 and Before

  • Understanding the patient perspective of epilepsy treatment through text mining of online patient support groups [J]. Google Scholar, 2019.

  • Uncertainty-guided mutual consistency training for semi-supervised biomedical relation extraction [J]. Google Scholar, 2022.

  • Meta-based self-training and re-weighting for aspect-based sentiment analysis [J]. Google Scholar, 2022.

  • Knowledge enhanced lstm for coreference resolution on biomedical texts [J]. Google Scholar, 2021.

  • Knowledge enhanced coreference resolution via gated attention [J]. Google Scholar, 2022.

  • JCBIE: A joint continual learning neural network for biomedical information extraction [J]. Google Scholar, 2022.

  • Implementation of National Health Informatization in China: survey about the status quo [J]. Google Scholar, 2019.

  • Extracting kinship from obituary to enhance electronic health records for genetic research [J]. Google Scholar, 2019.

  • Copner: Contrastive learning with prompt guiding for few-shot named entity recognition [J]. Google Scholar, 2022.

  • Construction of genealogical knowledge graphs from obituaries: Multitask neural network extraction system [J]. Google Scholar, 2021.

  • Bert-based meta-learning approach with looking back for sentiment analysis of literary book reviews [J]. Google Scholar, 2021.

  • Kai He, Rui Mao, T. Gong, et al. JCBIE: A joint continual learning neural network for biomedical information extraction [J]. BMC Bioinformatics, 2022, 23(1): 549.

  • B. Mao, C. Jia, Y. Huang, et al. Uncertainty-guided mutual consistency training for semi-supervised biomedical relation extraction [C]. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022: 2318–2325.

  • Kai He, B. Mao, X. Zhou, et al. Knowledge enhanced coreference resolution via gated attention [C]. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022: 2287–2293.

  • Y. Huang, Kai He, Y. Wang, et al. CopNER: Contrastive learning with prompt guiding for few-shot named entity recognition [C]. Proceedings of the 29th International Conference on Computational Linguistics (COLING), 2022: 2515–2527.

  • Kai He, Rui Mao, T. Gong, et al. Meta-based self-training and re-weighting for aspect-based sentiment analysis [J]. IEEE Transactions on Affective Computing, 2022, 14(3): 1731–1742.

  • Y. Li, X. Ma, X. Zhou, et al. Knowledge-Enhanced LSTM for Coreference Resolution on Biomedical Texts [J]. Bioinformatics, 2021, 37(17): 2699–2705.

  • Kai He, L. Yao, J. W. Zhang, et al. Construction of Genealogical Knowledge Graphs from Obituaries: Multitask Neural Network Extraction System [J]. Journal of Medical Internet Research, 2021, 23(8): e25670.

  • H. Bao, Kai He, X. Yin, et al. BERT-Based Meta-Learning Approach with Looking Back for Sentiment Analysis of Literary Book Reviews [C]. Natural Language Processing and Chinese Computing (NLPCC), 2021: 235–247.

  • Kai He, J. Wu, X. Ma, et al. Extracting Kinship from Obituaries to Enhance Electronic Health Records for Genetic Research [C]. Proceedings of the Fourth Social Media Mining for Health Applications (SMM4H) Workshop & Shared Task, 2019: 1–10.

  • Kai He, N. Hong, S. Lapalme-Remis, et al. Understanding the Patient Perspective of Epilepsy Treatment through Text Mining of Online Patient Support Groups [J]. Epilepsy & Behavior, 2019, 94: 65–71.

  • C. Li, X. Xu, G. Zhou, Kai He， et al. Implementation of National Health Informatization in China: Survey about the Status Quo [J]. JMIR Medical Informatics, 2019, 7(1): e12238.

Preprints

  • Jiaxing Xu, Jingying Ma, Xin Lin, Yuxiao Liu, Kai He, Qika Lin, Yiping Ke, Yang Li, Dinggang Shen, Mengling Feng. Toward a Multi-View Brain Network Foundation Model: Cross-View Consistency Learning Across Arbitrary Atlases [Preprint]. arXiv:2603.20348, 2026.

  • Zhihui Chen, Kai He, Qingyuan Lei, Bin Pu, Jian Zhang, Yuling Xu, Mengling Feng. MedForge: Interpretable Medical Deepfake Detection via Forgery-Aware Reasoning [Preprint]. arXiv:2603.18577, 2026.

  • Yanrui Du, Yibo Gao, Sendong Zhao, Jiayun Li, Haochun Wang, Qika Lin, Kai He, Bing Qin, Mengling Feng. From Latent Signals to Reflection Behavior: Tracing Meta-Cognitive Activation Trajectory in R1-Style LLMs [Preprint]. arXiv:2602.01999, 2026.

  • Qika Lin, Luwei Xiao, Bin Pu, Kaize Shi, Yanrui Du, Jiaxing Xu, Kai He, Shuai Zhao, Erik Cambria, Swapnil Mishra, Mengling Feng. A Survey of LLM Reasoning in Healthcare and Medicine: From Individual Modeling to Collaborative Agents [Preprint]. TechRxiv, 2026.

  • Jian Zhang, Yu He, Zhiyuan Wang, Zhangqi Wang, Kai He, Fangzhi Xu, Qika Lin, Jun Liu. A3-Bench: Benchmarking Memory-Driven Scientific Reasoning via Anchor and Attractor Activation [Preprint]. arXiv:2601.09274, 2026.

  • Dilruk Perera, Gousia Habib, Qianyi Xu, Daniel J. Tan, Kai He, Erik Cambria, Mengling Feng. Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI [Preprint]. arXiv:2508.21101, 2025.

  • Zihao Huang, Rui Mao, Xiaobao Wu, Kai He, Xulang Zhang, Erik Cambria. Fundamental Algorithms for Retrieval-Augmented Generation: A Survey [Preprint]. 2025.

🎖 Honors and Awards

  • 2024.12 Best Paper Award, IEEE Transactions on Affective Computing.
  • 2024.12 Outstanding Meidcal AI Applications.
  • 2023.03 Outstanding Doctoral Graduate.
  • 2022.09 Outstanding Graduate Student.
  • 2022.09 First-Class Scholarship Award.

📖 Educations and Experiences

  • 2023.05 - present, Research Fellow at SSHSPH, National University of Singapore, Singapore. (Supervisor: Prof. Mengling Feng)
  • 2021.09 - 2022.09, Joint Ph.D. at CCDS, Nanyang Technological University, Singapore. (Supervisor: Prof. Erik Cambria)
  • 2017.09 - 2023.03, Ph.D. at School of Computer Science and Technology, Xi’an Jiaotong University, Shannxi, China. (Supervisor: Prof. Chen Li)

💬 Academic Projects

  • Project of An Empathetic LLMs system for Comprehensive Mental Health Support and Assessment, Talent Development Award Project, PI. SSHSPH, Grant 26-0065-A0001.
  • Project of Future-Ready Interventions for Survival After Cardiac Arrest (FRISCA), Grant A-8001902-00-00.
  • Project of Intelligent Telephone Triage in Pre-Hospital Emergency Care. AISG, Grant AISG2-TC-2022-004.
  • Project of National Natural Science Foundation of China, research on the construction of metabolic pathway model based on semantic analysis of biological text, project number 61772409.
  • National Key RD Project, Research on Effective Mining and Key Information Technology of Big Data of Precision Medicine, Project No. 2018YFC0910404HZ.
  • Project of Shaanxi Provincial Department of Science and Technology, full chain intelligent pathology diagnosis equipment, project number 2021GXLH-Z-095.
  • Ningxia Provincial Key RD Program, application demonstration of key technologies for medical big data management and services based on breast cancer, stomach cancer, coronary heart disease and other diseases, project number 2022BEG02025HZ.
  • Project of the Statistical Information Center of the National Health Commission, Research on the framework system of knowledge mapping for artificial intelligence diagnosis and treatment assistance, Project No. 20201076.
  • Project of Shanghai Children’s Medical Center affiliated with Shanghai Jiao Tong University School of Medicine, Application of pediatric graded diagnosis and treatment based on artificial intelligence, Project No. 20210506.
  • Project of Xi’an Jiaotong University, Construction of large-scale cross-modal medical knowledge graph, Project No. xzd012020008
  • Project of Application Analysis and Benchmarking System of Artificial Intelligence in Health Care, Grant 20190725.
  • Project of Knowledge mining, fusion and application of multimodal fragmentation, Grant 61721002.

💻 Services

  • Journal
    • Associate Editor : IEEE Transactions on Affective Computing （IF:9.6）； Health Data Science （IF:4.5, pending）
    • Guest Leading Editor: Special Issue on Can AI Care? Affective LLMs for the Future of Mental Health of TAC journal.
    • Reviewer (Selected): Nature Communcation, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Affective Computing, Information Fusion, Expert System with Applicatiopn, Neurocomputing, Bioinformastics, Information Processing and Management, Knowledge-Based Systems, Cognitive Computation.
  • Conference
    • Are-Chair of LREC 2026 (Psycholinguistics, Cognitive Linguistics and Linguistic Theories)
    • Co‑chair of The 7th International Workshop on Artificial Intelligence for Precision Medicine, 2025 (https://ai-precmed.github.io).
    • Co‑chair of NLP‑SIG workshop, 2023‑now
    • Program Committee Member: ACL’23-25, EMNLP’22-23, COLING’22-23, SIGIR’23, CIKM’24, IJCAI’23-24, IJCNN’25 etc.