Anastasia Tsifouti® | Founder, Lead Scientist & Artist
I am a scientist, artist, and director operating at the intersection of imaging science and human experience. Based in London, my work redefines “image quality” not just as a technical metric, but as a bridge to human connection, support, and growth.
I am expanding the understanding of Quality of Experience (QoE) into existential and perceptual territories. My current work involves “transmuting” original analogue archives through a custom algorithm to explore how memory can be restructured into refined, physical forms. As a creative rationalist, I thrive on synthesising complex data into soulful, innovative solutions.
With 20 years’ experience in imaging science, I have reached a point of deeper understanding regarding the essence of image quality. This has been achieved through rigorous introspection and the production of my own inner qualities, identifying ‘sweet spots’ of inner alignment.
Previously, I served as a UK Civil Servant Scientist, where I defined image quality standards and established testing methodologies (incorporating detailed objective technical and psychophysical methods) for law enforcement tasks involving both algorithms and human observers. One of my most significant professional achievements resulted in the standardisation of CCTV recording quality across the entire London bus network (TfL); a landmark feat accomplished as a self-funded, independent researcher during my PhD and in my capacity as a Civil Service Lead Scientist.
My research remains the technical foundation of the TfL CCTV Build Specification; a standard that currently governs the recording parameters and evidentiary quality for the entire 9,000-strong London bus network.
My career in the Civil Service trained me to solve problems holistically, by meticulously examining specific applications and their inherent complexities. My experience also includes roles as an Image Quality Lead and Researcher on Image Signal Processing (ISP) pipeline algorithms for three major technology companies. Additionally, I was the Image Quality Lead for a startup, where the algorithm I co-developed led to a successful acquisition by a global tech leader.
I believe in the power of connection. Whether narrowing a technical process or expanding a creative narrative, my intention is to produce work that is both deeply personal and universally understood.
Science Foundation
PhD Thesis
- Tsifouti, A. (2015). An Investigation into the Effects of Image Quality on the Performance of Human and Automated Face Recognition in Video Surveillance. PhD Thesis. University of Westminster.
Journal Papers
- Tsifouti, A., et al. (2015). ‘A case study in identifying acceptable bitrates for human face recognition tasks.’ Signal Processing: Image Communication, Vol. 34, pp. 58–71.
Conference Proceedings & Awards
- Tsifouti, A., et al. (2015). ‘The effects of scene content parameters, compression, and frame rate on the performance of analytics systems.’ Proc. SPIE 9396, Image Quality and System Performance XII, 93960X.
- Tsifouti, A., et al. (2015). ‘Comparative performance between human and automated face recognition systems, using CCTV imagery, different compression levels and scene parameters.’ Proc. SPIE 9396, Image Quality and System Performance XII, 93960M.
- Tsifouti, A., et al. (2013). ‘Acceptable bitrates for human face identification from CCTV imagery.’ Proc. SPIE 8653, Image Quality and System Performance X, 865305. [Best Student Paper Award].
- Tsifouti, A., et al. (2012). ‘A methodology to evaluate the effect of video compression on the performance of analytics systems.’ Proc. SPIE 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII.