Xiaohang Xu

ORCID: 0000-0003-1266-9943
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About
Contact & Profiles
Research Areas
  • Mental Health Research Topics
  • Digital Mental Health Interventions
  • Machine Learning in Healthcare
  • Human Mobility and Location-Based Analysis
  • Surface Roughness and Optical Measurements
  • Recommender Systems and Techniques
  • Traffic Prediction and Management Techniques
  • Liquid Crystal Research Advancements
  • advanced mathematical theories
  • Metallic Glasses and Amorphous Alloys
  • Functional Brain Connectivity Studies
  • Data Management and Algorithms
  • Transportation and Mobility Innovations

The University of Tokyo
2023-2024

Beihang University
2008-2021

Guizhou University
2021

Depression is one of the most common mental illnesses, and symptoms shown by patients are different, making it difficult to diagnose in process clinical practice pathological research. Although researchers hope that artificial intelligence can contribute diagnosis treatment depression, traditional centralized machine learning methods need aggregate patient data, data privacy with illness needs be strictly confidential, which hinders algorithms' application. To solve problem medical this...

10.1109/tii.2021.3113708 article EN IEEE Transactions on Industrial Informatics 2021-09-20

Depression is one of the most common mental illness problems, and symptoms shown by patients are not consistent, making it difficult to diagnose in process clinical practice pathological research. Although researchers hope that artificial intelligence can contribute diagnosis treatment depression, traditional centralized machine learning needs aggregate patient data, data privacy with be strictly confidential, which hinders algorithms application. To solve problem medical history we...

10.48550/arxiv.2102.09342 preprint EN other-oa arXiv (Cornell University) 2021-01-01

Next Point-of-Interest (POI) recommendation plays a crucial role in urban mobility applications. Recently, POI models based on Graph Neural Networks (GNN) have been extensively studied and achieved, however, the effective incorporation of both spatial temporal information into such GNN-based remains challenging. Temporal is extracted from users' trajectories, while obtained POIs. Extracting distinct fine-grained features unique to each piece difficult since often includes information, as...

10.1145/3589132.3625644 preprint EN 2023-11-13

We report the observation of a shear direction alternatively changed crack path in thin Fe78Si9B13 metallic glassy sheet with high strength and elasticity. This configuration under tension is discussed framework elastic strength. The reason for this attributed to interaction between shrinkage small wavelength wrinkle propagating bending energy while low stretching energy.

10.1063/1.2993976 article EN Journal of Applied Physics 2008-10-01
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