Anastasia Mozhaeva
PhD (Research in Computer Vision,
Machine Learning & Electronics)

Senior Lecturer / Researcher

School of Computing
Faculty of Commerce and Technology
Eastern Institute of Technology

Office: PD104
290 Palmerston Road, Gisborne 4010
Email: amozhaeva@eit.ac.nz
I am a Senior Lecturer specialising in visual AI, video processing and mechatronics. With over 10 years in the tech industry and more than 7 years in academia, I bridge applied innovation with research excellence. My work integrates academic research with industry partnerships, focusing on AI for aerospace. I explore how human visual perception can enhance visual AI, aiming to develop systems that perceive the world like humans do. My recent work focuses on designing human-vision-based visibility models to optimise deep learning, bandwidth, and computational efficiency in resource-limited environments.
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Biography

Research Committee Member, Eastern Institute of Technology, School of Computing (from 2024)

Senior Lecturer, Eastern Institute of Technology, School of Computing (from 2024)

PhD (Visual AI & Electronics), The University of Waikato, New Zealand (2024)

Editorial Board Member, Computer Vision, Synchroinfo journal (from 2024)

Senior Lecturer, Moscow Technical University of Communications and Informatics, School of Television and Sound Broadcasting, Russia (2020-2023)

Researcher, Moscow Technical University of Communications and Informatics, School of Television and Sound Broadcasting, Russia (2019-2023)

Technical Lead (Embedded Video Analytics & Signal Processing), (2013-2018)

MEng (Information and Communication Technology), Moscow Technical University of Communications and Informatics, Russia (2009)


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Recent projects
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A contrast sensitivity model of the human visual system in modern conditions for presenting video content

In this paper, the 27840 thresholds of the visibility of spatio-temporal sinusoidal variations necessary to determine the artefacts that a human perceives were measured by a new method using different spatial sizes and temporal modulation rates.
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Video quality metric compatible with PSNR considering recent knowledge of peripheral characteristics of human vision

The work analyses existing data on human perception of temporal frequencies in the central and peripheral areas of vision. A new method for measuring quality is presented, built on new models of human contrast sensitivity.
Research Grants / Funding

Feasibility funding: "Real-time 180° video processing drone project", Trust Tairāwhiti, Principal Investigator (2025).

Research grant: "Human vision-based technology for real-time processing of wide-angle video signals", Eastern Institute of Technology, Principal Investigator (2024).

Research grant: "Research the spatio-temporal parameters of the human visual system", Science Foundation, Key Researcher (2023).

Research grant: "Research and development of methods for the integrated control of the parameters and characteristics of video cameras with built-in adaptive processing and compression of the generated signals", Science Foundation, Key Researcher (2023).

Research grant: "Development and application of a psycho-visual model of the effect of masking distortions during the movement of objects in video sequences based on laboratory-subjective-statistical tests ", Moscow Technical University of Communications and Informatics, Key Researcher (2022).

Research grant: "Development of a method for objectively assessing the quality of video sequences, considering the results of subjective-static examinations and using psycho-visual models", Ministry of Digital development, communications and mass communications, Key Researcher (2021).

Research grant: "Development of methods for monitoring the parameters and characteristics of adaptive light-signal converters for applied television systems", Moscow Technical University of Communications and Informatics, Key Researcher (2020).

Honours / Prizes

"The Best BEing Supervisor" in the competition of innovative projects in the field of digital transformation, International Public Academy of Telecommunications (2023).

The best startup
of artificial intelligence Startuphouse Universities 400k Rub (2022).

The best paper in the nomination “Technology advancements in IOT devices & Artificial Intelligence” EMCTECH International Conference Austria (2021).

The best paper of the international scientific conference “2021 Systems of signals generating and processing in the field of onboard communications” (2021).

The University of Waikato
Doctoral Scholarship.

Moscow Technical University of Communications and Informatics
Master Scholarship.

Moscow Technical University of Communications and Informatics
Bachelor Scholarship.