Shaswar Baban

Shaswar Baban was born in the Kurdistan region of Iraq, 1985. He attended Electrical Engineering College at Salahaddin University in 2003 to specialise in Electronics and Communications later on. In 2007, he graduated as he was ranked in the top 3 among his colleagues. In summer 2004 he participated in the Middle East Partnership Initiative (MEPI) leadership program at Georgetown University, Washington DC. During his undergraduate studies he also took two summer on-job trainings at Huawei Technologies Co., Ltd. and Asiacell Telecommunication LLC.He won the prestigious Mohammed Bin Isa Al-Jaber scholarship in 2007 to complete his masters studies in “Mobile, Personal and Satellite Communications” at Westminster University, London, UK. His masters project was titled “Designing and Implementation of a Scheduling Algorithm for the IEEE 802.16e (Mobile WiMAX) networks”.

In 2009, he was employed as “WiMAX Project Technical Adviser” at Fanoos Telecom until he was awarded the FPI Scholarship from the Spanish Ministry of Science and Innovation to become a researcher at the University of the Balearic Islands in Palma de Mallorca, Spain (October 2009), where he researched in Radio Resource Management (RRM) of OFDMA-based, Relay-enhanced Next Generation Mobile Networks.

Since 2011 he is a PhD student at the Centre for Telecommunications Research (CTR) at King’s College London under the supervision of Prof. Aghvami.

Meanwhile, Shaswar is serving on several various committee at the School of Natural and Mathematical Sciences at King’s, as well as being a reviewer for the IEEE Potentials Magazine, SigComm, PIMRC, WInnComm, etc.

My research interests are broad, however, I am most interested in the interconnection of Telecommunications and Artificial Intelligence. More precisely, I am very excited about the application of Machine Learning techniques in the context of Cognitive Radio Networking. Applications of my research are, but not limited to, the following areas:

• Radio Access Technology recognition to facilitate Cognitive Radio communications.
• Spectrum efficiency enhancement – using TV White Spaces.
• Applying learning techniques to improve spectrum sensing and awareness.
• Big Data Analytics in cognitive radio networking.

          In general, researching intelligence for cognitive radios.