Location of Research: Remote
Live Video Analytics on IoT Edge provides a platform to build intelligent video applications that span the edge and the cloud. Edge computing is an emerging paradigm that distributes computing resources closer to end-users. The need for timely response arises in both human and machine to machine applications (e.g., gaming AR, VR, autonomous drones, and industrial machinery). The goal is to develop a platform that offers the capability to capture, record, and analyze live video along with publishing the results (video and/or video analytics) in real-time. Students will explore online adaptation of video analytics pipeline where the objective is to maximize accuracy under bandwidth and computational power constraints.
Lab: Wireless and Mobile Networking (WiMNet) Lab
Direct Supervisor: Mahshid Ghasemi Dehkordi
Position Dates: Spring 2021 & Summer 2021
Hours per Week: 10 - 20 hours
Paid Position: Yes
Credit: Yes
Number of positions: 1
Qualifications
- Knowledge of networking
- Programming knowledge: C/C++, Shell, Python
- Deep learning, Computer vision, Reinforcement learning
Eligibility
- Freshman, Sophomore, Junior, Senior, Master's
Gil Zussman, Professor of Electrical Engineering, Columbia University
[email protected]