Email KAI_HE@nus.edg.sg

Providing adequate medical care to everyone in the world remains a challenge, especially with many healthcare professionals already overworked. Training qualified doctors is a demanding task, and this contributes to the problem. One potential solution is the use of Artificial Intelligence (AI) to alleviate the workload of medical workers. AI has the potential to play a crucial role in the entire healthcare process, from predicting diseases, recommending medication, and providing prognosis.

He Kai and his colleagues are dedicated to researching medical AI, with the goal of effectively reducing the current pressure on medical workers. By integrating AI into healthcare, we can improve patient outcomes, enhance efficiency, and ultimately provide better medical care to people around the world.

• NUS Saw Swee Hock School of Public Health

• Natural Language Processing
• Healthcare with AI

• PhD. Xi’an Jiaotong University, 2023
• M.S. Lanzhou University of technology, 2017
• B.S. HeXi University, 2009

• Outstanding PhD graduates, 2023

• Research Fellow, National University of Singapore (2023-present)

• Virtual Prompt Pre‑training for Prototype‑based Few‑shot Relation Extraction, HE K, HUANG YC, RUI M, ET.AL. EXPERT SYSTEMS WITH APPLICATIONS, 2023.
• Meta‑based self‑training and re‑weighting for aspect‑based sentiment analysis, HE K, RUI M, GONG TL, ET.AL. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2022.
• Construction of Genealogical Knowledge Graphs From Obituaries: Multitask Neural Network Extraction System, HE K, YAO L, ZHANG J W, ET AL. JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23(8): E25670. (IMPACT FACTOR:7.0
• The Biases of Pre‑trained Language Models: An Empirical Study on Prompt‑based Sentiment Analysis and Emotion Detection, MAO R, LIU Q, HE K, ET. AL. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,
• COPNER: Contrastive Learning with Prompt guiding for Few Shot Named Entity Recognition, HUANG YC, HE K, WANG YG , ET. AL. COLING, 2