Recent Posts

I just got notified that our submission to DySPAN 2018, Opportunistic Channel Access Using Reinforcement Learning in Tiered CBRS Networks, was accepted. Matthew Tonnemacher from SMU and Samsung Research America led this paper which focuses on using machine learning to help overcome the hidden terminal problem in the emerging CBRS band. Machine learning has been getting extensive attention throughout the world over the last few years. Much of the buzz surrounds the achievements in classification tasks such as image recognition or the ability to outperform humans in complicated games such Go.

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Recent Publications

. Digital Predistortion with Low-precision ADCs. In ACSSC, 2018.

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. Parallel Digital Predistortion Design on Mobile GPU and Embedded Multicore CPU for Mobile Transmitters. In JSPS, 2017.

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. Low-Complexity, Sub-Band DPD with Sequential Learning: Novel Algorithms and WARPLab Implementation. In SiPS, 2016.

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. Low-Complexity Subband Digital Predistortion for Spurious Emission Suppression in Noncontiguous Spectrum Access. In TMTT, 2016.

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Industry Expierence

  • Samsung Research America, Dallas, TX, Standards and Mobility Inovvation Lab, RF and PoC Team. May 2017 – Dec 2017.

  • Lockheed Martin, Hanover, MD, May 2016 – Aug 2016.

Teaching

While at Rice, I helped develop a new curriculum for the ELEC 220, Fundamentals of Computer Architecture course. We focused on making a course that would enforce learning through hands on activities in a lab environment. Check out this link for more info.