Huan Chen is a research associate in the Applied Innovations team at Insight, University of Galway. Her research focuses on bridging the gap between the generative power of LLMs and the need for computational efficiency, factual integrity and interpretability. By leveraging techniques like knowledge distillation and transfer learning to mitigate hallucinations, detect bias, and provide explainable AI solutions that make complex model decision-making transparent and accessible. She studied explainable recommendations based on KGs and automated machine learning, using a genetic algorithm to do hyperparameter optimisation and model selection.
Huan completed her BE in Software Engineering at Changchun University, and she graduated with an MSc in Computer Science from University College Dublin. Her MSc graduation dissertation research combines the traditional recommendation method with deep learning technology to build an accurate, efficient recommendation model. She currently has a particular interest in LLMs, information retrieval, recommender systems, automated machine learning processes, the semantic web and natural language processing.
