September 2016

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News and Resources for Members of the IEEE Signal Processing Society

September 2016

Research in artificial intelligence (AI) has made great progress in recent years including Google's Go-playing AI AlphaGo beating world-class player Lee Se-dol in a 4-1 victory. While AI surpasses human intelligence in many tasks, the way it works is very different from the human brain. Dr. Dhruv Batra from Virginia Tech gave a presentation on whether humans and AI look at the same regions when answering visual questions, at Data Science Summit 2016, in San Francisco, CA. https://www.arxiv-vanity.com/papers/1606.03556/

Please visit the Conferences and Events page on the IEEE Signal Processing Society website for upcoming Lectures by Distinguished Lecturers.

You may have received an email from Howard E. Michel, IEEE 2015 President and CEO, instructing you to vote FOR the IEEE Constitutional Amendment on this year’s member ballot. As you know, the Board of Governors of our Signal Processing Society has unanimously voted against the amendment. Actually, the governing bodies of the majority of IEEE societies are against it, including the largest ones such as Computer, Communications, and Power and Engineering.

The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 8 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest.

Please refer to the following webpage for the latest updates on upcoming conferences in Signal Processing.

Listing of all conferences

Zhu, Yu (West Virginia University), “Multi-Modality Human Action Recognition” (2016) Advisor: Guo, Guodong

Kong, Long, (University of California, Los Angeles), “RF Synthesis without Inductors” (2016) Advisor: Razavi, Behzad

Recent developments in RF receiver design have eliminated all on-chip inductors except for that used in the local oscillator. This dissertation addresses the “last inductor” problem and proposes both integer-N and fractional-N synthesizer architectures that achieve a phase noise and figure of merit (FOM) comparable to those of LC-VCO-based realizations.

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