Mo is a member of the Pervasive Systems team at Nokia Bell Labs, Cambridge, where he contributes to the wireless sensing research activities. Mo obtained an MSc in Electronics from The University of Manchester and a PhD in Computing and Communications from Lancaster University, respectively in 2005 and 2011. His PhD was jointly funded by Research Councils UK through a Dorothy Hodgkin postgraduate award and by a Microsoft Research Cambridge Scholarship. Since 2006, he has been conducting research and development in multiple industrial settings in areas spanning wireless signal processing, ultra-low power medical wearables, automotive radar, and most recently channel sensing.
I am particularly interested in wireless sensing, millimetre-wave sensing and communications, and generally in the application of machine learning techniques in wireless.
Mohammed Alloulah, Zoran Radivojevic, Howard Huang, and Fahim Kawsar, "Apparatus for Reflecting Electromagnetic Waves and Method of Operating such Apparatus," Application PCT/EP2018/079863, 31 Oct. 2018.
Mohammed Alloulah, Anton Isopoussu, Chulhong Min, and Fahim Kawsar, "Signal Subspace Extent Determination For Wi-Fi Sensing," Application EP181945999, 14 Sep. 2018.
Mohammed Alloulah, Alison Burdett, and Mark Dawkins, "System and method for radio communication," GB Grant GB2550413B, 26 June 2018.
Mohammed Alloulah, Paul Murrin, and Alamo Spaargaren, "Minimizing inter-symbol interference in OFDM signals," CN EP GB US Grant US9954713B2, 24 Apr. 2018.
Mohammed Alloulah, Chulhong Min, Fahim Kawsar, "Occupany Detection Using The MIMO Structured Model for Minimising Environmental Effects," Application EP172751489A, 22 Sep. 2017.
Mohammed Alloulah, Mark Dawkins, and Alison Burdett, "Pre-distortion compensation for voltage controlled oscillators," Application GB2552212A, 14 Jul. 2016.