Dr Silvia Cirstea

Silvia Cirstea For media enquiries please contact the Press Team
Deputy Head of School

Medical Technology Research Centre; Vision and Eye Research Institute

Faculty:
Faculty of Science and Engineering
School:
Computing and Information Science
Location:
Cambridge
Areas of Expertise:
Vision and eye research , Computer Science , Artificial Intelligence
Research Supervision:
Yes

Silvia carries out cross-faculty research in the areas of computer modelling, simulation and optimization for medical and engineering applications. She leads the Biomedical Informatics Research Group, part of ARU's Medical Technology Research Centre (MTRC), and is also a member of the Computing, Informatics and Applications Research Group.

[email protected]

Background

Silvia’s areas of expertise include data, signal and image processing, statistical, machine learning and AI methods, neural networks, numerical modelling and optimization of physical and industrial processes (electromagnetics, acoustics, quantum mechanics, workflows). Since 2010, she has worked with the Vision and Eye Research Institute (VERI) on the role of acoustic cues, like level and reverberation, as conveyors of information about the environment and to facilitate better navigation of the visually impaired. She has a keen interest in digital healthcare and, in particular, assisted living for the visually impaired using acoustic cues and smart technologies.

She has worked on research projects funded by Innovate UK, the EU, UK Central Laboratory of the Research Councils, Radiocommunications Agency, Medical Research Council and British industry.

Research interests
  • Computer modelling and simulation
  • Artificial Intelligence
  • Virtual environments
  • Acoustic modelling and echolocation
  • Assisted living for the visually impaired and the elderly
  • Signal processing techniques for multimodal data fusion
  • Navigation aids for the visually impaired
Areas of research supervision
  • Modelling for engineering or medical applications
  • Applications of AI (medical imaging, forensic chemistry, digital healthcare)

Find out more about our Computing and Information Science PhD and exciting PhD project opportunities.

Teaching

Modules:

  • Introduction to Mathematical Techniques for AI
  • Advanced Analytical Techniques for AI
  • Digital Signal Processing

Courses:

Qualifications
  • PhD Imaging Technologies, De Montfort University
  • BSc and MSc Mathematics, University of Bucharest, Romania
  • PGCE Learning & Teaching in Higher Education, Anglia Ruskin University
Memberships, editorial boards
  • Member, Institute of Electrical & Electronics Engineers (IEEE)
  • Member, Institute of Electrical & Electronics Engineers (MIEEE)
  • Fellow, Higher Education Academy (FHEA)
Research grants, consultancy, knowledge exchange
  • Innovate UK 'Adaptive Learning for Zero Defects in Building Construction', TR Control Solution Ltd (2019-2020)
  • ERDF Innovation Bridge 'Investigate technical requirements to deploy Ophta software into a standalone portable diagnostic tool for diabetic retinopathy', Effective Solutions Ltd (2018) 
  • ERDF Innovation Bridge 'Investigate DSP (Digital Signal Processing) solutions to the triboelectric effect, and apply the chosen solution to a non-contact infrared temperature sensor', Irisense Ltd (2018)
  • EU FP7 Capacities Research for SMEs project ‘Echo2eco’ (FP7-SME-2011-286155, 'A novel sound absorption technology to enable energy efficient construction techniques and promote the health and wellbeing of occupants'), 2012-2014

Patent
US Patent  US10190312B2: Sound absorbing material, a method for production of the same and device for cutting apertures in the sound absorbing material; Inventors: Bjorn Andre Flotre, Silvia Cirstea, Edwin Robert Toulson: https://patents.google.com/patent/US10190312B2/en.

Selected recent publications

Ray, J., Wijesekera, L., Cirstea, S., 2022. Machine learning and clinical neurophysiology. J Neurology, doi: https://doi.org/10.1007/s00415-022-11283-9.

Kolarik, A. J., Moore, B. C. J., Cirstea, S., Raman, R., Gopalakrishnan, S., Pardhan, S., 2022. Partial visual loss disrupts the relationship between judged room size and sound source distance. Experimental Brain Research, 240:81–96, doi: https://doi.org/10.1007/s00221-021-06235-0.

Hameed, N., Shabut, A., Hameed, F., Cirstea, S., Hossain, A., 2021. Achievements of neural network in skin lesions classification, in State of the Art in Neural Networks and Their Applications, Elsevier Academic Press, London, ISBN: 978-0-12-819740-0.

Aggius-Vella, E., Kolarik, A.J., Gori, M., Cirstea, S., Campus, C., Moore, B.C.J., Pardhan, S., 2020. Comparison of auditory spatial bisection and minimum audible angle in front, lateral, and back space. Scientific Reports 10:6279, doi: https://doi.org/10.1038/s41598-020-62983-z.

Kolarik, A.J., Raman, R., Moore, B.C.J., Cirstea, S., Gopalakrishnan, S., Pardhan, S., 2020. The accuracy of auditory spatial judgments in the visually impaired is dependent on sound source distance. Scientific Reports 10:7169, doi: https://doi.org/10.1038/s41598-020-64306-8.

Hameed, N., Shabut, A., Hameed, F., Cirstea, S., Harriet, S., Hossain, A., 2020. Mobile-based Skin Lesions Classification Using Convolution Neural Network. Annals of Emerging Technologies in Computing (AETiC), 4(2):26-37, doi: 10.33166/AETiC.2020.02.003.

Hameed N., Hameed F., Shabut A., Khan S., Cirstea S., Hossain A., 2019. An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions. Computers, 8(3), 62; https://doi.org/10.3390/computers8030062.

Sadeghi Esfahlani, S., Thompson, T., Davod Parsa, A., Brown I., Cirstea, S., 2018. ReHabgame: A non-immersive virtual reality rehabilitation system with applications in neuroscience. Heliyon 4 e00526. doi: 10.1016 /j .heliyon .2018 .e00526.

Kolarik, A. J., Pardhan, S., Cirstea, S., Moore, B. C. J., 2017. Auditory spatial representations of the world are compressed in blind humans. Experimental Brain Research, 235(2), 597-606. doi: 10.1007/s00221-016-4823-1.

Kolarik, A. J., Moore, B. C. J., Zahorik, P., Cirstea, S., Pardhan, S., 2016. Auditory distance perception in humans: a review of cues, development, neuronal bases, and effects of sensory loss. Attention, Perception, and Psychophysics, 78(2), 373-395. doi: 10.3758/s13414-015-1015-1.

Kolarik, A. J., Cirstea, S., Pardhan, S., Moore, B. C. J., 2014. A summary of research investigating echolocation abilities of blind and sighted humans. Hearing Research, 310, 60-68. doi: 10.1016/j.heares.2014.01.010.

Kolarik, A., Cirstea, S., & Pardhan, S. (2013). Discrimination of virtual auditory distance using level and direct-to-reverberant ratio cues. Journal of the Acoustical Society of America, 134(5), 3395-3398. doi: 10.1121/1.4824395.

Recent presentations and conferences

Kolarik. A. J., Moore, B. C. J., Raman, R., Cirstea, S., Gopalakrishnan, S., Pardhan, S., 2020. Greater severity of visual loss is associated with larger auditory distance judgments, with poorer accuracy for closer sounds, J. Investigative Ophthalmology & Visual Science, 61(7), 4268, ARVO.

O’Reilly, J., Cirstea, S., Zhang, J., Cirstea, M., 2019. A novel development of acoustic SLAM, Proceedings of 2019 Joint International Conference OPTIM-ACEMP, p. 525-531, IEEE.

Hameed, N., Shabut, A., Hameed, F., Cirstea, S., Hossain, A., 2019. An Intelligent Inflammatory Skin Lesions Classification Scheme for Mobile Devices, International Conference on Computing, Electronics and Communications Engineering (iCCECE), p. 83-88, London, UK.

Sadeghi Esfahlani, S., Cirstea, S., Sanaei, A., Cirstea, M., 2018. Fire detection of Unmanned Aerial Vehicle in a Mixed Reality-based System, Proc of IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, Washington DC, USA, p. 2757-2762, http://dx.doi.org/10.1109/IECON.2018.8592764.

Bagnoli, M., Cirstea, S., 2017. Dynamic geometry- and material-dependent simulation of room impulse responses in a virtual gaming environment. Joint International Conference OPTIM-ACEMP, IEEE. doi: 10.1109/OPTIM.2017.7975118.