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Achievement: Pull Shark

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Achievement: Pull Shark

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AntekIwa/README.md

Hi, I'm Antek!

I'm a dual-degree student pursuing a B.Sc. in Computer Science at the University of Warsaw and a B.Eng. in Data Engineering and Analysis at Warsaw University of Technology. My passion lies at the intersection of complex algorithms and machine learning.

About Me

  • Double Degree: Studying CS at the University of Warsaw (2025–2028) and Data Engineering at Warsaw University of Technology (2025–2029).
  • Competitive Programmer & Quant: Global Finalist in the IMC Prosperity Trading Challenge (Top 7% worldwide, 13th in Poland). Finalist of ICPC CERC (High Honor)[cite: 1], AMPPZ (2023, 2025)[cite: 1], and the Polish Olympiad in Informatics (OI).
  • Jury OI & Educator: Jury member for the Polish Olympiad in Informatics (OI), where I prepare solves, tests, and verify tasks for contests. Also an experienced instructor in Competitive Programming and Mathematics.
  • ML Enthusiast: Completed the Machine Learning Specialization by Stanford Online & Coursera.

Tech Stack

  • Languages: Python, C++, C, Java.
  • Libraries & Tools: NumPy, scikit-learn, Whisper, Ollama/Llama 3, Git, JUnit, CustomTkinter, ElevenLabs API.

Featured Projects

Below is a curated selection of my most notable projects categorized by their context. For a complete list of all my repositories, feel free to visit my GitHub Profile.

Research & University Projects

  • Sentinel-2 PCA: Research project at Warsaw University of Technology.
  • Ski Resort Simulation (wyciagi): Object-Oriented Programming project at the University of Warsaw. Event-driven simulation of a ski resort modeled as a directed graph in Java using JUnit[cite: 1]. Implemented custom data structures like circular buffers and event queues from scratch.
  • CitiBike Data Analysis: Data Engineering passing project at Warsaw University of Technology.

Personal Projects

  • DocFlow: Privacy-first desktop application for automated file organization using Python and CustomTkinter. Leverages local LLMs (Ollama/Llama 3) for semantic document analysis and implements a hybrid (Rules + AI) architecture.
  • VoiceToDo: Voice-controlled to-do list application integrating Whisper (speech-to-text) and ElevenLabs (text-to-speech) for natural interaction.
  • FlappyBirdGeneticNN: Neural network agent trained with a genetic algorithm to play Flappy Bird, utilizing NumPy for selection, crossover, and mutation.

Competitive Programming Stats

Codeforces Stats

Contact & Socials

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  1. FlappyBirdGeneticNN FlappyBirdGeneticNN Public

    Python

  2. geneticNN geneticNN Public

    A simple, fully custom neural network trained with a genetic algorithm. No ML libraries – just pure Python and NumPy. Forward pass, selection, crossover, and mutation all implemented from scratch.

    Python

  3. VoiceToDo VoiceToDo Public

    Voice-controlled to-do list app using Python, Whisper, and ElevenLabs for speech recognition and text-to-speech.

    Python

  4. Heart-Disease-Predictor Heart-Disease-Predictor Public

    Predicting heart disease using machine learning models with evaluation via accuracy, F1, recall, and ROC AUC.

    Jupyter Notebook

  5. citibike-data-analysis citibike-data-analysis Public

    Jupyter Notebook

  6. sentinel2-segmentation sentinel2-segmentation Public

    TeX