Bridging the gap between academic research and practical data science solutions. Passionate about creating innovative software tools and contributing to scientific knowledge.
PhD Scholar
Institute of Fundamental and Technological Research, POLISH ACADEMY OF SCIENCES
Learn more about my academic journey and expertise
I am a dedicated PhD scholar with a passion for advancing knowledge through rigorous research and innovative methodologies. My academic journey has been driven by curiosity and a desire to make meaningful contributions to my field.
Beyond academic research, I am deeply involved in data science. I create custom Python solutions to assist in my research work and develop tools that can benefit the broader scientific community.
Explore my academic contributions and research publications
Custom tools and data science projects I've developed
A professional GUI application for processing microscopy timeframe images, developed to streamline research workflows. Features interactive ROI selection, batch processing of timeframe sequences, and professional animation export capabilities. This tool bridges the gap between raw microscopy data and publication-ready figures, saving valuable research time.
Step-by-step guides for academic research and technical tools
A comprehensive guide to getting started with Mendeley for managing your research references.
Learn to insert and manage equations, figures, and tables with proper linkable captions in Microsoft Word.
Guide on accessing thesis and research papers at UESTC and other academic institutions.
Exploring the intersection of research, technology, and data science
A comprehensive end-to-end project demonstrating how to develop, tune, and deploy a Random Forest classifier for medical diagnosis using the Wisconsin Breast Cancer dataset. Achieved 97.37% accuracy with complete code walkthrough.
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From data understanding to deployment - A comprehensive 5-phase approach to machine learning with the classic Titanic survival prediction challenge, including feature engineering, model comparison, and Tkinter application deployment.
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A complete guide to implementing a Convolutional Neural Network for image classification using PyTorch, featuring data augmentation, TensorBoard visualization, and desktop deployment.
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Institute of Fundamental Technological Research, POLISH ACADEMY OF SCIENCES
Biosystems and Soft Matter, Laboratory of Modeling in Biology and Medicine (PMBM),Warsaw, Poland
Monday - Friday
08:00 AM - 045:00 PM