Contact Xiangqi Kong
- Email: Xiangqi.Kong@cranfield.ac.uk
Areas of expertise
- Human Factors
- Systems Engineering
Background
Xiangqi Kong is a research student of PhD in Aerospace at Cranfield University.
She obtained her BEng from the School of Mechano-Electronic Engineering at Xidian University in Xi'an, China in 2017, and completed her MSc in Mechanical Engineering in 2020.
Research opportunities
Enhancing Machine Learning Transparency: Concentrating on enhancing the interpretability and robustness of machine learning models.
Improving Human-AI Interaction: Focusing on data-centric AI to optimize the collaboration between humans and AI.
Developing Trustworthy AI Interfaces: Creating reliable interfaces for AI systems considering human factors.
Current activities
Explainable Time Series Forecasting
Explainabel Interface Framework
Publications
Conference Papers
- Xing Y, Kong X & Tsourdos A. (2024). RGANFormer: Relativistic Generative Adversarial Transformer for time-series signal forecasting on intelligent vehicles
- Kong X, Xing Y, Liu Z, Tsourdos A & Wikander A. (2024). Enhancing performance and interpretability of multivariate time-series model through sparse saliency
- Liu Z, Kong X, Chen Y, Wang Z, Jia H, .... (2024). Mitigating no fault found phenomena through ensemble learning: a mixture of experts approach