Polina Pshonkovskaya
About Polina Pshonkovskaya
Polina Pshonkovskaya is a researcher known for her contributions to studies on EEG data, including data leakage issues, age prediction using deep learning, and seizure detection optimization.
Work at Brainify.AI
Polina Pshonkovskaya holds the position of researcher at Brainify.AI. In this role, she engages in advanced studies focused on EEG data analysis and neural network optimization. Her work contributes to the understanding of brain activity and its implications for various applications, including seizure detection and demographic predictions.
Research Contributions
Polina Pshonkovskaya has co-authored multiple studies that address significant issues in EEG research. One notable study tackles the data leakage problem in large multi-site EEG datasets, which is crucial for ensuring data integrity. Additionally, she has worked on predicting age from resting-state scalp EEG signals using deep convolutional neural networks, enhancing the predictive capabilities of EEG analysis.
Deep Neural Networks and Seizure Detection
Pshonkovskaya is involved in research aimed at optimizing deep neural networks specifically for seizure detection. This work is essential for developing more accurate and efficient methods for identifying seizure events, which can improve patient outcomes in clinical settings.
Studies on Brain Sex Prediction
Polina Pshonkovskaya has contributed to research focused on predicting brain sex from EEG data. She co-authored a study utilizing a large-scale heterogeneous dataset, which enhances the understanding of sex differences in brain activity. Furthermore, she has explored the use of tree-based algorithms for this prediction, showcasing her versatility in applying different methodologies in EEG research.