Kai He

Kai He

Saw Swee Hock School of Public Health

He Kai, Ph.D., earned his doctorate from the School of Computer Science and Technology at Xi’an Jiaotong University under the supervision of Professor Li Chen (recipient of the Young Thousand Talents Plan in China). He also completed an academic visit at the School of Computer Science and Engineering, Nanyang Technological University, under the guidance of Professor Erik Cambria (IEEE Fellow), with whom he maintains an active academic collaboration. Currently, he is a postdoctoral researcher at the School of Public Health, National University of Singapore, focusing on research in Large Language Model, AI for Healthcare, Affective Computing, Information Extraction.

I currently work as a Research Fellow in NUS. For my full (and timely) publication list, please refer to my Google scholar.

🔥 News

  • 2025.04:  🎉🎉 Our paper of diffusion-based difference-aware medical VQA is accepted by IEEE TIP.
  • 2025.02:  🎉🎉 Our survey paper on Multiple Instance Learning in computational pathology is accepted by Information Fusion (IF 14.8).
  • 2024.12:  🎉🎉 Our paper reveives **Best Paper Award**, IEEE Transactions on Affective Computing, titled “The Biases of Pre-Trained Language Models: An Empirical Study on PromptBased Sentiment Analysis and Emotion Detection”

đź“ť Publications

2025

  • Qika Lin, Kai He, Yifan Zhu, et al. Cross-modal Knowledge Diffusion-based Generation for Difference-aware Medical VQA. IEEE TIP
  • Zhang Y, Gao Z, He K, et al. From patches to WSIs: A systematic REVIEW of deep Multiple Instance Learning in computational pathology[J]. Information Fusion, 2025: 103027. (IF:14.8) [Paper] [BibTeX]
  • Mao R, Ge M, Han S, et al. A survey on pragmatic processing techniques[J]. Information Fusion, 2025, 114: 102712. [Paper] [BibTeX]
  • He K, Mao R, Lin Q, et al. A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics[J]. Information Fusion, 2025: 102963. [Paper] [BibTeX]

2024

  • Lin Q, Zhu Y, Mei X, et al. Has multimodal learning delivered universal intelligence in healthcare? A comprehensive survey[J]. Information Fusion, 2024: 102795. [Paper] [BibTeX]
  • Xu J, He K, Lan M, 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. [Paper] [BibTeX]
  • Li Y, Ma X, Zhou X, et al. Integrating K+ Entities into Coreference Resolution on Biomedical Texts[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024. [Paper] [BibTeX]
  • Mao R, He K, Ong C, 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. 2024: 9891-9908. [Paper] [BibTeX]
  • Wu J, Yu X, He K, et al. Promise: A pre-trained knowledge-infused multimodal representation learning framework for medication recommendation[J]. Information Processing & Management, 2024, 61(4): 103758. [Paper] [BibTeX]
  • Mao R, He K, Zhang X, et al. A survey on semantic processing techniques[J]. Information Fusion, 2024, 101: 101988. [Paper] [BibTeX]

2023

  • Zhang X, Mao R, He K, et al. Neuro-symbolic sentiment analysis with dynamic word sense disambiguation[C]//Findings of the Association for Computational Linguistics: EMNLP 2023. 2023: 8772-8783. [Paper] [BibTeX]
  • Wu J, He K, Mao R, et al. MEGACare: Knowledge-guided multi-view hypergraph predictive framework for healthcare[J]. Information Fusion, 2023, 100: 101939. [Paper] [BibTeX]
  • He K, Mao R, Huang Y, 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. [Paper] [BibTeX]
  • Mao R, Li X, He K, et al. MetaPro Online: A computational metaphor processing online system[C]//Proceedings of the 61st annual meeting of the association for computational linguistics. Association for Computational Linguistics (ACL), 2023. [Paper] [BibTeX]
  • He K, Huang Y, Mao R, et al. Virtual prompt pre-training for prototype-based few-shot relation extraction[J]. Expert systems with applications, 2023, 213: 118927. [Paper] [BibTeX]
  • Mao R, Liu Q, He K, 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. [Paper] [BibTeX]

2022

  • He K, Mao R, Gong T, et al. JCBIE: a joint continual learning neural network for biomedical information extraction[J]. BMC bioinformatics, 2022, 23(1): 549. [Paper] [BibTeX]
  • Mao B, Jia C, Huang Y, et al. Uncertainty-guided mutual consistency training for semi-supervised biomedical relation extraction[C]//2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022: 2318-2325. [Paper] [BibTeX]
  • He K, Mao B, Zhou X, et al. Knowledge enhanced coreference resolution via gated attention[C]//2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022: 2287-2293. [Paper] [BibTeX]
  • Huang Y, He K, Wang Y, et al. Copner: Contrastive learning with prompt guiding for few-shot named entity recognition[C]//Proceedings of the 29th International conference on computational linguistics. 2022: 2515-2527. [Paper] [BibTeX]
  • He K, Mao R, Gong T, 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. [Paper] [BibTeX]

Before 2022

  • Li Y, Ma X, Zhou X, et al. Knowledge enhanced lstm for coreference resolution on biomedical texts[J]. Bioinformatics, 2021, 37(17): 2699-2705. [Paper] [BibTeX]
  • He K, Yao L, Zhang J W, et al. Construction of genealogical knowledge graphs from obituaries: Multitask neural network extraction system[J]. Journal of medical Internet research, 2021, 23(8): e25670. [Paper] [BibTeX]
  • Bao H, He K, Yin X, et al. Bert-based meta-learning approach with looking back for sentiment analysis of literary book REVIEWs[C]//Natural Language Processing and Chinese Computing: 10th CCF International Conference, NLPCC 2021, Qingdao, China, October 13–17, 2021, Proceedings, Part II 10. Springer International Publishing, 2021: 235-247. [Paper] [BibTeX]
  • He K, Wu J, Ma X, et al. Extracting kinship from obituary 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. [Paper] [BibTeX]
  • He K, Hong N, Lapalme-Remis S, et al. Understanding the patient perspective of epilepsy treatment through text mining of online patient support groups[J]. Epilepsy & Behavior, 2019, 94: 65-71. [Paper] [BibTeX]
  • Li C, Xu X, Zhou G, et al. Implementation of National Health Informatization in China: survey about the status quo[J]. JMIR medical informatics, 2019, 7(1): e12238. [Paper] [BibTeX]

Under REVIEW

  • ALPaCA: Adapting Llama for Pathology Context Analysis to enable slide‑level question answering GAO ZY, HE K, SU WH,ET. AL. NATURE COMMUNICATION, UNDER REVIEW.
  • Accurate spatial quantification in computational pathology with multiple instance learning GAO ZY, MAO AY, HE K, ET. AL. NATURE CANCER, UNDER REVIEW.
  • InTriage: Intelligent Telephone Triage in Pre‑Hospital Emergency Care HE K, LIN QK, FEi H, ET.AL. ACL 2025, UNDER REVIEW.
  • Crab: A Novel Configurable Role‑Playing LLM with Assessing Benchmark HE K, HUANG YC, WANG WQ, ET.AL. ACL 2025, UNDER REVIEW.
  • External Retrievals or Internal Priors? From RAG to Epitome‑Augmented Generation HE K, XU JX, LiN QK, ET.AL. ACL 2025, UNDER REVIEW.
  • Towards Smarter Clinical Predictions: Foundation Models for Integrating Multi‑Source Domain Knowledge in EHRs WU JL, MEI X, HE K, ET. AL. JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, UNDER REVIEW.
  • AKECare: A Temporal‑Hierarchical Framework with Knowledge Fusion for Personalized Clinical Predictive Modeling WU JL, MEi X, HE K, ET. AL. JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, UNDER REVIEW.
  • Harnessing the Potential of Multimodal EHR Data: A Comprehensive Survey of Clinical Predictive Modeling for Intelligent Healthcare WU JL, HE K, RUi MAO, ET. AL. INFORMATION FUSION, UNDER REVIEW.
  • Robust Multimodal Sentiment Analysis via Double Information Bottleneck HUANG, HT, GONG TLHE K, ET.AL. INFORMATION FUSION, UNDER REVIEW.
  • Self‑supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Modelsn LIN QK, ZHAO TZ, HE K, ET.AL. ACL 2025, UNDER REVIEW.
  • A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models LIN QK, PENG X, HE K, ET. AL. IJCAI, UNDER REVIEW.
  • Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution RUAN,YC, LAN X, HE K, ET. AL. ARTIFICIAL INTELLIGENCE REVIEW, UNDER REVIEW.
  • Unraveling the Evolution of Public Cognition of COVID‑19: A Concept Mapping Analysis through Metaphors in US Tweets MAO R, TAN Y, HE K, ET. AL. IJCAI 2025, UNDER REVIEW.
  • Multi‑Atlas Brain Network Classification through Consistency Distillation and Complementary Information Fusion XU JX, LAN MC, HE K, ET. AL. TMI, UNDER REVIEW.
  • Exploring Cognitive Difference in Poetry!Collection via Large Language Models andMetaphors: A Case Study of the Book ofSongs HUI B, HE K, WANG YG, GAO ZY, ET. AL. COGNITIVE COMPUTATION, UNDER REVIEW.
  • Towards Unified Neurosymbolic Reasoning on Knowledge Graphs LIN QK, XU FZ, HE K, ET. AL. AI, UNDER REVIEW.
  • Multi‑granularity Semantic Extraction and Multi‑task Fusion for Chinese Medical Entity Normalization HOU WH, HE K, MAO R, ET. AL. INFORMAITON FUSION, UNDER REVIEW.
  • Global Entity Relationship Enhancement Network for Multimodal Sarcasm Detection WANG XB, GE M, HE K, ET. AL. IEEE TRANSACTIONS ON AFFECTIVE COMPUTiNG, UNDER REVIEW

🎖 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.

đź“– 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)

đź’¬ Academic Projects

  • 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.

đź’» Services

  • Journal

    • Reviewer (Selected):

      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

    • 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.