Research Groups

In the Communication and Machine Learning Laboratory, we research deep learning, machine learning, reinforcement learning, energy harvesting and distributed computing. 1) In the deep learning area, we research unsupervised learning, natural language processing, and Bayesian learning. 2) In the reinforcement learning area, we research reinforcement learning based energy harvesting, imitation learning, multiagent learning. 3) In the distributed computing area, we research the optimization between computing power and communication bandwidth, the failure of storage system, and coded caching.

▶ Research
Machine Learning
Deep Learning
Reinforcement Learning
Distributed Computing & Storage
Energy Harvesting

- "An Outer Bound on the Storage-Bandwidth Tradeoff of Exact-Repair Cooperative Regenerating Codes," in IEEE Transactions on Information Theory in Nov. 2017
- "Coordinated Beamformig for Multi-cell MIMO-NOMA," in IEEE Communications Letters, vol. 21, no. 1, pp. 84-87, Jan. 2017.
- "Non-Orthogonal Multiple Access in Multi-Cell Networks: Theory, Performance, and Practical Challenges," in IEEE Communcation Magazine, Oct. 2017
- "A Scalable Framework for Secure Distributed Computing," 2018 Information Theory and Applications Workshop