معرفی
Mengjia Xu is an Assistant Professor in the Data Science department at New Jersey Institute of Technology (NJIT). Her research focuses on interdisciplinary areas including machine learning, biomedical informatics, and graph embedding techniques applied to healthcare and neuroscience challenges.
Research Interests:
- Development of hyperbolic neural networks for studying aging trajectories and brain networks
- Graph embedding methods for temporal and biomedical data analysis
- Automated assessment of sickle cell disease using computer vision and microfluidics
- Quantum cognition and intrinsic dimension estimation in machine learning
Recent Research Contributions:
Recent work includes applying hyperbolic neural networks to analyze brain networks in cognitive decline, developing stochastic graph embedding algorithms for temporal data, and creating frameworks for automated sickle cell analysis. These efforts bridge computational methods with biomedical applications.
Media Highlights:
- Featured in discussions on AI limitations and generative AI trends
- Presented research on physics-informed neural networks and scalable machine learning algorithms
Professional Activities:
Active in academic collaborations with institutions like MIT and Brown University, focusing on interdisciplinary projects in data science and biomedical engineering.
