Broadly in statistical data processing and inference, and the physical layer issues of communication theory. Specifically,
Statistical learning and inference in large-scale wireless networks, Distributed machine learning (federated learning), Sparse signal processing, Design and analysis of transceiver algorithms, Optimal modulation and coding schemes, Distributed detection and estimation, Wireless sensor networks, Visible light communication, Information and coding theory.
Courses taught:
1. Information theory and coding
2. Wireless communications
3. Analog and digital communication systems
4. Probability, stochastic process and statistics
5. Information theory and statistics
Labs handled:
1. Communications and microwave systems laboratory
2. Computer aided design and simulation laboratory
3. Digital systems design laboratory
4. Electrical engineering workshop practice
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