Banafshe Arbab-Zavar

Dr Banafshe Arbab-Zavar

  • Lecturer in Data Science & AI
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Biography

Banafshe is a lecturer in data science at the department of Computing and Informatics. She has a PhD from the University of Southampton in biometric recognition and specializes in image processing and pattern recognition. She has previously worked as a research engineer at the University of Southampton and has a track record of research in computer vision, visual surveillance, and feature extraction for pattern recognition. She has led and contributed to many EU projects in data science ranging from human and crowd behaviour analysis; tsunami detection and warning; and disease progression modelling to name a few.

Journal Articles

Chapters

  • Arbab-Zavar, B., Wei, X., Bustard, J.D., Nixon, M.S. and Li, C.-T., 2015. On Forensic Use of Biometrics. Handbook of Digital Forensics of Multimedia Data and Devices. John Wiley & Sons.
  • Hurley, D.J., Arbab-Zavar, B. and Nixon, M.S., 2008. The ear as a biometric. Handbook of Biometrics. Springer US.

Conferences

  • Sabeur, Z., Zlatev, Z., Melas, P., Veres, G., Arbab-Zavar, B., Middleton, L. and Museux, N., 2017. Large scale surveillance, detection and alerts information management system for critical infrastructure. IFIP Advances in Information and Communication Technology, 507, 237-246.
  • Sabeur, Z.A., Correndo, G., Veres, G., Arbab-Zavar, B., Lorenzo, J., Habib, T., Haugommard, A., Martin, F., Zigna, J.M. and Weller, G., 2017. EO big data connectors and analytics for understanding the effects of climate change on migratory trends of marine wildlife. IFIP Advances in Information and Communication Technology, 507, 85-94.
  • Sabeur, Z., Doulamis, N., Middleton, L., Arbab-Zavar, B., Correndo, G. and Amditis, A., 2015. Multi-modal computer vision for the detection of multi-scale crowd physical motions and behavior in confined spaces. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9474, 162-173.
  • Correndo, G., Arbab-Zavar, B., Zlatev, Z. and Sabeur, Z.A., 2015. Context ontology modelling for improving situation awareness and crowd evacuation from confined spaces. IFIP Advances in Information and Communication Technology, 448, 407-416.
  • Sabeur, Z., Arbab-Zavar, B., Wächter, J., Hammitzsch, M., Löwe, P., Lendholdt, M., Armigliato, A., Pagnoni, G., Tinti, S. and Omira, R., 2013. Modeling and detection of hydrodynamic trends for advancing early-tsunami warnings. Proceedings of the International Offshore and Polar Engineering Conference, 40-47.
  • Mörzinger, R., Sabeur, Z., Arbab-Zavar, B. et al., 2010. Tools for semi-automatic monitoring of industrial workflows. ARTEMIS'10 - Proceedings of the 1st ACM Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams, Co-located with ACM Multimedia 2010, 81-86.
  • Arbab-Zavar, B., Bouchrika, I., Carter, J.N. and Nixon, M.S., 2010. On supervised human activity analysis for structured environments. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6455 LNCS (PART 3), 625-634.
  • Nixon, M.S., Bouchrika, I., Arbab-Zavar, B. and Carter, J.N., 2010. On use of biometrics in forensics: Gait and ear. European Signal Processing Conference, 1655-1659.
  • Arbab-Zavar, B. and Nixon, M.S., 2008. Robust log-Gabor filter for ear biometrics. Proceedings - International Conference on Pattern Recognition.
  • Hurley, D.J., Arbab-Zavar, B. and Nixon, M.S., 2007. The ear as a biometric. European Signal Processing Conference, 25-29.
  • Arbab-Zavar, B., Nixon, M.S. and Hurley, D.J., 2007. On model-based analysis of ear biometrics. IEEE Conference on Biometrics: Theory, Applications and Systems, BTAS'07.
  • Arbab-Zavar, B. and Nixon, M.S., 2007. On shape-mediated enrolment in ear biometrics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4842 LNCS (PART 2), 549-558.

Profile of Teaching UG

  • Tools & Technologies of Data Science
  • Data Visualisation and Visual Analytics