Curriculum Vitae

Introducing a novel taxonomy and concept in perceptual and visual scene grammar called microviolation, and also cognitive models, and Markers of detecting early development in language by scene perception using Virtual Reality, EEG, and Eye tracking.

Collaboration on the role of emotion, emotional regulation, and mental health in visual search, bridging practical and fundamental science in visual search and visual attention. Developing a computational model in visual search investigating the role of emotion in daily life, including visual attention and visual search.

Thesis Title: Applying Alertness Training to Improve Visual Processing Speed in Patients with neurodegenerative disorders and brain Injury – Supervisor: Prof. Luca Battaglini

Prestigious three-year research fellowship awarded based on an outstanding record and proposal by the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant and from the European Union – NextGenerationEU. The fellowship focuses on improving visual processing speed in visual deficit patients and the aged population, as well as methodological and technical improvement in current methodologies through innovative methods or technologies for assessment, intervention, or enhancement of psychological functions (cognitive and emotional).

The research is funded based on a proposal from the Marie Skłodowska-Curie grant (€43K) and involves implementing psychophysical and perceptual learning training to enhance visual processing speed in patients with visual deficits. The work examines indicators of successful treatment and utilises advanced machine learning to understand outcomes, while investigating the role of cognitive load and emotion in the outcomes of training in cases of visual deficits.

Additionally, the research has improved current methodology for application of EEG/eye tracking, including developing a novel method for detecting blinks and eye tracking that is device-independent, noise-resistant, and model-agnostic. The work has enhanced the existing method of pupil reconstruction by using psychologically inspired noise to more accurately simulate real pupil size in eye-tracking data, and developed a new single-case analysis approach that tackles autocorrelation and phase-specific variability.

Invited collaborator on LinguaMed, a collaboration project of the Russian Academy of Science and Ural Medical University. The role focused on establishing a foundational basis of science-based applications for medical doctors and psychologists.

Responsibilities included teaching programming languages (Python, Java, R) for statistical analysis, experimental curation, and data collection. Additionally, provided instruction on practical applications of eye tracking and EEG, co-registration experimental designs in science.

The position also involved teaching common practices in scientific laboratories rather than medical laboratories, including protocols, conducting studies, debugging, and process tracking to bridge the gap between scientific and medical research methodologies.

Research position focused on working with advanced EEG systems, Eye tracking, computational modelling, and research in neuroscience and computational modelling. The role involved hands-on experience with cutting-edge neurotechnology equipment and methodologies.

Gained extensive practical experience in neurotechnology applications, contributing to research projects that combined neurophysiological measurements with computational approaches to understand brain function and behavior.

Prestigious fully funded Master's program (tuition waived of ~$6,200 / 490,000 Rubles) and stipend for 2 years (~$4500 / 360,000 Rubles) awarded based on winning the International Open-doors organized by the Association of Global Universities, a consortium of leading Russian universities, and is supported by the Ministry of Science and Higher Education of the Russian Federation.

Graduated with a GPA of 4.78/5 (top 10% of the whole department) and completed 648 Academic hours of teaching and research internship, including 432 hours of supervised teaching modules in English and 108 Academic hours of supervised teaching in Russian. Additionally completed 432 academic hours of fully independent teaching in English.

Chosen twice (September 2020 and June 2021) as the teacher of the semester by student feedback, both undergraduate and graduate teaching, demonstrating exceptional teaching abilities and student engagement across multiple academic levels.