Data-driven QoE Prediction for Cellular Networks

2020-2021 Summer
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 

The student will use Python ML libraries to devise and implement a method for data-driven QoE prediction and anomaly detection in cellular networks.  The student will do this research in collaboration with a MS student and a major cell phone operator.

Related Areas of Project: 
Computer Science and Engineering
Electronics Engineering

About Project Supervisors

Özgür Erçetin
Faculty of Engineering and Natural Science