Oleh

Email: [открыть контакты](см. выше в блоке «контактная информация»)

Oleh Yarosh
LinkedIn: [открыть контакты](см. выше в блоке «контактная информация»)
GitHub: https://github.com/oleh-26-01
Junior C#/.NET Developer Telegram: https://t.me/P15485863
Phone: [открыть контакты](см. выше в блоке «контактная информация»)
Birthday: January 26, 2004
Location: Lviv, Ukraine

SUMMARY

● Result-oriented, highly motivated student with a strong passion for AI and ML technologies.
Experienced in implementing pet-projects to apply theoretical knowledge and gain practical
skills.

● Key area of technical expertise includes C# (WPF) for desktop application development,
showcasing expertise in implementing genetic algorithms and executing performance
optimization techniques to enhance code efficiency. Proficient in utilizing Python for computer
vision, data parsing, scripting, and automation applications.

● Deep theoretical understanding of the principles of artificial intelligence, demonstrated
through projects such as face detection and predicting people's reactions to news, with
theoretical knowledge extending to generative models.

● Fast learner, adaptable to new technologies, adept at problem-solving, with a proactive
approach to continuous learning.

Hard Skills:

● C#: proficient in C# programming language, with a strong foundation in application
development using .NET framework.

● Object-Oriented Programming (OOP): strong knowledge and application of OOP principles in
both Python and C#.

● Windows Presentation Foundation (WPF): knowledgeable in creating desktop applications
using WPF, enhancing user interface and overall user experience.

● Python: proficient in Python programming language for various applications. Extensive
experience with libraries and frameworks such as numpy, OpenCV, TensorFlow (Keras),
matplotlib, scikit-learn, pygame, PIL.

● C/C++: familiar with C/C++ and have hands-on experience in writing small programs

● Performance Optimization: proficient in analyzing code for performance bottlenecks,
employing strategies to optimize time and memory usage. Experienced in enhancing the
efficiency of algorithms and overall program execution

● Machine Learning: familiarity with popular CNN architectures for image classification,
practical understanding of genetic algorithms for optimization;

● Linux System Administration: proficient in Linux system administration tasks, including
installation, configuration, and troubleshooting. Active use of Ubuntu for personal projects.

● Version Control: Git, Subversion;

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 ● Relational Databases: MySQL;

Soft Skills:

● Project Management: Trello, Hive;

● English Language: B1 in writing, listening, speaking; B2 in reading;

● Adaptability: quick learner, flexible, and able to adapt to changing environments;

● Critical Thinking and Mental Toughness: skilled in evaluating information, making logical
decisions, and maintaining resilience in challenging situations.

EXPERIENCE

Nov-2023 - Dec-2023 - university Project: Sklady
GitHub: https://github.com/TarasKoliada/SyllablesProject
Description: Collaborated on the Sklady project, a text processing initiative working with files and
strings, optimizing its performance and memory usage significantly.
Technologies: C#, .NET, dotTrace, Visual Studio.
Achievements:

● Implemented substantial performance enhancements, reducing processing time in x8-30 times,
with improvements scaling as more data was processed.

● Optimized memory usage, achieving a x1.5-2 times reduction in memory requirements.

● Gained extensive knowledge and practical experience in contributing to a .NET 4.0 project,
enhancing existing optimization through parallelization, and applying various optimization
techniques.

May-2023 - Jun-2023 - Personal Project: Face Recognition
GitHub: https://github.com/oleh-26-01/face-recognition
Description: Developed a comprehensive Jupyter Notebook that serves as a guide for performing face
recognition task. The project covers various steps, including dataset preprocessing, data loading,
model creating and training, evaluation, and more.
Project Highlights:

● Developed a comprehensive Jupyter notebook for face recognition task.

● Implemented dataset preprocessing techniques, such as cleaning, normalization, and
augmentation.

● Created and trained face recognition models using Convolutional Neural Networks architecture.

● Conducted evaluation and analysis of models to ensure accuracy and performance.

● Organized the project repository, including pre-trained models and result visualizations.
Technologies: Python, CNN, OpenCV, TensorFlow, NumPy, Jupyter Notebook, PyCharm.

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Achievements:

● Achieved high accuracy in face recognition, demonstrating the effectiveness of the developed
models.

● Gained extensive knowledge and practical experience in deep learning, CNNs, and image
recognition techniques.

Nov-2022 - Jul-2023 - Personal Project: Autonomous Driving Simulation
GitHub: https://github.com/oleh-26-01/Project-One
Description: Developing a 2D autonomous driving simulation as a personal project, focusing on
implementing genetic algorithm, neural network and applying object-oriented programming principles.
Project Highlights:

● Designed and implemented a user-friendly curve editor and testing environment.

● Applied object-oriented programming principles for clean code organization and maintainability.

● Developed a genetic algorithm to find optimal solutions.
Technologies: C#, .NET, WPF, Visual Studio, Git
Achievements:

● Successfully demonstrated autonomous driving capabilities within the simulation.

● Gained hands-on experience in implementing genetic algorithms and utilizing OOP principles
effectively.

CERTIFICATE

Mar-2024 - Mar-2027 - TensorFlow Developer Certificate - https://www.credential.net/8bb681d0-
d86f-4f1b-b46b-8bca33190de7

EDUCATION

Sep-2021 - present - Bachelors Degree in Information Systems and Technologies - Ivan Franko
National University of Lviv, Faculty of Electronics and Computer Technologies.

COURSEWORK

Apr-2023 - May-2023 - Creation of a neural network for recognition and classification of road signs
(Grade: A+)
Nov-2022 - Dec-2022 - Implementation of Spotify listening history tracker to store and manage data
in a MySQL database (Grade: A)

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