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Hire Dr. Anna P.

Czech Republic

USD 70 /hr

Researcher in Complex Systems (PhD) | MedTech Data Analysis | Bio-Signal Processing | Mental Health Research Expert

Profile Summary

I am a researcher at the Czech Academy of Sciences (Institute of Computer Science) and the National Institute of Mental Health (NUDZ). My work focuses on the intersection of complex systems, data analysis, and mental health. With a PhD and a background in mathematics and statistics, I enjoy bridging the gap between scientific theory and practical data applications. I am looking to apply my academic experience to projects in the MedTech and Mental Health sectors, helping teams handle complex datasets with a thoughtful, research-oriented approach. How I can support your project: * Analysis of "Noisy" Medical Data: I have extensive experience in cleaning, preprocessing, and extracting features from high-dimensional bio-signals (including fMRI, EEG, and iEEG). I focus on finding reliable patterns in data where standard automated tools might struggle. * Methodological & Statistical Review: I can help review your data processing pipelines to ensure that the chosen statistical methods are appropriate for your specific goals. I act as a "second pair of eyes" to help ensure that the findings are consistent and well-grounded in scientific logic. * Network Science & Graph Theory for Mental Health: My core research involves applying network analysis including graph theory and Topological Data Analysis (TDA) to brain connectivity. I can help translate these methods into insights for digital health tools, particularly in the context of mental health research. I am available for part-time consulting, methodological support, or specialized data analysis projects where a careful, scientific perspective is valued.

Subject Matter Expertise

• ★ Data Analysis
• ☆ Biostatistics
• ☆ Signal Processing
• ☆ Statistics
• ☆ Health Data Analysis
• ☆ Graph Theory
• ☆ Python
• ☆ Matlab

Services

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Technical Writing

Research Scientific and Technical Research

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Data Cleaning, Data Processing, Data Insights

Product Development Prototyping

Work Experience

National Institute of Mental Health

2017 - Present

Institute of Computer Science of the Czech Academy of Sciences

2015 - Present

Data Analysts

StarLightMedia

July 2013 - February 2014

Data Analysts

Mobilochka

November 2012 - June 2013

Data Analysts

SMD

July 2011 - October 2012

Education

Ph.D.

Czech Technical University in Prague

2014 - 2020

Masters of Science

Taras Shevchenko National University of Kyiv

September 2006 - May 2012

Certifications

• Certification details not provided.

Publications

BOOK CHAPTER

Anna Pidnebesna, David Hartman, Jaroslav Hlinka, František Szczepanik (2026). Local Iterative Algorithms for Approximate Symmetry Guided by Network Centralities .

JOURNAL ARTICLE

I. Dallmer-Zerbe, J. Kopal, A. Pidnebesna, J. Curot, M. Denuelle, A.De Barros, J.C. Sol, L. Valton, E.J. Barbeau, J. Hlinka (2025). Pro-ictal, rather than pre-ictal, brain state marked by global critical slowing and local gamma power increase . Clinical Neurophysiology.

Anna Pidnebesna, Jakub Kopal, David Tomeček, Jaroslav Tintěra, Jaroslav Hlinka(2020). Typicality of functional connectivity robustly captures motion artifacts in rs‐fMRI across datasets, atlases, and preprocessing pipelines . Human Brain Mapping. 41. (18). p. 5325--5340. Wiley

Pidnebesna, A., Tomeček, D., Hlinka, J.(2018). BRAD: Software for BRain Activity Detection from hemodynamic response . Computer Methods and Programs in Biomedicine. 156. p. 113-119.

PREPRINT

I. Dallmer-Zerbe, J. Kopal, A. Pidnebesna, J. Curot, M. Denuelle, A. De Barros, J.C. Sol, L. Valton, E.J. Barbeau, J. Hlinka (2024). Pro-ictal, rather than pre-ictal, brain state marked by global critical slowing and local gamma power increase .

Anna Pidnebesna, Jakub Kopal, David Tomeček, Jaroslav Tintěra, Jaroslav Hlinka (2020). Typicality of Functional Connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases and preprocessing pipelines .

OTHER

Anna Pidnebesna, Jakub Kopal, David Tomeček, Jaroslav Tintěra, Jaroslav Hlinka(2020). Typicality of Functional Connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases and preprocessing pipelines . Cold Spring Harbor Laboratory

CONFERENCE PAPER

Pidnebesna, A.(2017). Autoregressive models of submissions to municipalities in Czech Republic . Proceedings of the 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2017. 1. p. 485-487.