Recent Projects

AI-based Sensing in Healthcare 

We collaborate with various PIs in the UC Davis Health Systems on machine learning applications in healthcare using sensing technologies, including neural muscular disease identification, ICU patient monitoring, hospitalization readmission prediction, and healthy aging. [more info in the UC-DASH project page]

Machine Learning Algorithm Development

Our effort on ML algorithm development focuses on reinforcement learning algorithms, including multi-armed bandits. We study how to bring RL to real-world applications by addressing challenges such as constraints, data efficiency, and explainability. We also study security and privacy issues of machine learning algorithms. 

Data-Driven Networking

We focus on deep DDN uses network measurement and user behavior data, based on machine learning techniques, and control/optimization mechanisms, to solve network control and management challenges. We study various issues in wireless networks, including cellular network configuration, network slicing, resource management, 360-degree video transmission, user experience improvement, and encrypted network traffic classification.

Machine Learning Applications in Animal Health

We collaborate with Prof. Beatriz Martinez Lopes from UC Davis Veterinarian Medicine and Prof. Maria Clavijo from Iowa State Univ. on veterinarian health. We use machine learning methods to develop effective surveillance and control mechanisms for infectious disease and antibiotic resistence in the swine industry. The work is currently supported by two NSF grants.


Past Projects

Industrial Collaborators

  • AT&T - Data-driving Networking; Cellular Traffic Scheduling
  • Fujitsu Laboratories of America, Inc. - Hetnet
  • Intel - Mesh Networks

Network Research Lab