Savvas Papaioannou

I am a PhD candidate at the Department of Computer Science, University of Oxford under the supervision of Prof. Niki Trigoni and Prof. Andrew Markham. My research is focused on the development of accurate, robust and cost-effecting positioning systems. I am also interested in multi-modal multi-target tracking algorithms suitable for highly dynamic environments and industrial settings.

Before joining Oxford, I was a graduate student at Yale University and member of the Embedded Networks & Applications Laboratory (ENALAB), led by Dr. Andreas Savvides. At Yale, I worked mainly on the Intelligent Buildings Project i.e. identifying anomalies on a building's power consumption behaviour. I have obtained my M.S. degree in Electrical Engineering in 2013.

I graduated from Technical University of Crete in 2011 with a B.S. degree in Electronic and Computer Engineering. During that time I worked on hardware design, embedded systems and machine vision under the supervision of Prof. Ioannis Papaefstathiou.

My research interests are in mobile and context aware applications and systems, distributed computing, cyber-physical systems, sensing platforms and architectures, sensor networks, sensor fusion and networked embedded systems, indoor/outdoor localisation, intelligent camera sensor networks, computer vision, multiple-target tracking, software/hardware co-design, computer architecture and hardware implementation using FPGAs.

• Accurate Positioning via Cross-Modality Training.
  Savvas Papaioannou, Hongkai Wen, Zhuoling Xiao, Andrew Markham and Niki Trigoni.
  In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems (SenSys'15), pp. 239-251. ACM, 2015.
  (acceptance rate: 20%)


• Opportunistic Radio Assisted Navigation for Autonomous Ground Vehicles.
  Hongkai Wen, Yiran Shen, Savvas Papaioannou, Winston Churchill, Niki Trigoni and Paul Newman.
  In Proceedings of the 11th International Conference on Distributed Computing in Sensor Systems (DCOSS'15), pp. 21-30. IEEE, 2015.
  (acceptance rate: 23%)


• Fusion of Radio and Camera Sensor Data for Accurate Indoor Positioning.
  Savvas Papaioannou, Hongkai Wen, Andrew Markham and Niki Trigoni.
  In Proceedings of the 11th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS'14), pp. 109-117. IEEE, 2014.
  (acceptance rate: 26%)


• A Novel Low-power Embedded Object Recognition System Working at Multi-frames Per Second.
  Antonis Nikitakis, Savvas Papaioannou and Ioannis Papaefstathiou.
  In ACM Transactions on Embedded Computing Systems (TECS), Mar. 2013.


• WiFi Sensors Meet Visual Tracking For An Accurate Positioning System (Poster).
  Savvas Papaioannou, Hongkai Wen, Zhuoling Xiao, Andrew Markham and Niki Trigoni.
  In the 11th European Conference on Wireless Sensor Networks (EWSN'14), 2014


• Efficient Visual Positioning with Adaptive Parameter Learning (Poster).
  Hongkai Wen, Sen Wang, Ronnie Clark, Savvas Papaioannou and Niki Trigoni
  In the 15th International Conference on Information Processing in Sensor Network (IPSN'16), 2016


• A Novel Low-power Embedded Object Recognition System Working at Multi-frames Per Second.
  Antonis Nikitakis, Savvas Papaioannou and Ioannis Papaefstathiou.
  In Proceedings of the 10th IEEE Symposium on Embedded Systems for Real-time Multimedia (ESTIMedia'12), pp. 85-85. IEEE, 2012
  ( Best Paper Award )


• SIPE: A Sensor Information Processing Engine for Wellness Management Applications.
  Savvides, A., Papaioannou, S., Kartakis, S., Kohler, B., Demiris, G. and Thompson, H.
  In Proceedings of the 5th ACM International Conference on Pervasive Technologies Related to Assistive Environments (PETRA'12), 2012