Space Intelligence Evolution with Autonomic Preference Learning

Scalable learning by distributed autonomous IoTs based on user feedbacks and rich representation of IoT big data

Placeness Inference using Cyber-Physical Data Convergence

Faster unsupervised inference on placeness (user perception on a given space) with smaller urban dataset which is made up of cyber-physical convergence data

Elastic Collaboration of Edge IoTs for QoS Optimization

Application- and context-aware reconfiguration of edge IoT collaborations and reinforcement learning-based policy evolution

Interested in CDSN?

We are looking for highly talented and self-motivated graduate students.