This research group focusses primarily on PHY and MAC layer issues of wireless networks. Current focus of his research group is on Millimeter wave communications for 5G wireless, waveforms for 5G and anti-jamming techniques for LTE-A cellular wireless networks. "Learning for Wireless Networks" is another exciting research topic that the research group started working on in the recent past. Regression and/or classification framework developed in the machine learning community might help designing more efficient wireless receivers. With regard to MAC layer, learning the dynamics of a multi-user network (either through reinforcement learning or supervised learning) can help wireless engineers in achieving optimal radio resource management. Srinivas's research group is highly enthusiastic and aspires to learn the state-of-the-art learning concepts in order to learn how to communicate better.

• Wireless Communication
• Nano-Communication Networks
• Optical communication: Non-traditional optical fibers, FBG based optical filters
• Microwave Communications