Особисті дані приховані

Vitaliia Homovych
[відкрити контакти](див. вище в блоці «контактна інформація») [відкрити контакти](див. вище в блоці «контактна інформація»)
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Third-year Computer Science student with a previous Doctor of Medicine degree
and a strong interest in healthcare technologies. Familiar with Linux/Unix
environments, along with a solid foundation in object-oriented programming,
data analysis, and machine learning concepts. Experienced in working effectively
within team settings. A fast learner who thrives on new challenges and is eager
to contribute to innovative projects that create real-world value.

Education
Uzhhorod specialized school № 5 with in-depth study of foreign languages 2005-2016
GPA: 4.6/5.0
Faculty of Medicine , Uzhhorod National University 2016-2022
Doctor of Medicine
GPA: 4.7/5.0
University of Debrecen 2023-2027
Bachelor of Computer Science
GPA: 4.2/5.0

Projects
Reinforcement Learning-Based Autonomous Agent
Unity, C#, Unity ML-Agents
Built and trained an agent using Unity ML-Agents.
Implemented raycast-based sensing and action systems for environment interaction and target detection.
Designed a reward/penalty system to encourage efficient navigation and successful target engagement.
Evaluated and refined agent behavior through iterative training and testing.
Multilingual Sentiment Analysis Application
Python, PyTorch, TensorFlow, Hugging Face Transformers, Flask, HTML, CSS, JavaScript
Developed a multilingual sentiment analysis system for English, Spanish, and German text classification.
Implemented and compared TF-IDF-based neural network models with fine-tuned transformer
architectures (RoBERTa and XLM-RoBERTa).
Trained and evaluated models on a class-balanced multilingual sentiment dataset using predefined
training, validation, and test splits.
Deployed the solution as an interactive application with a Flask backend and frontend interface.
Deep Learning-Based Classification of Respiratory Sounds for Medical Diagnosis (Ongoing
Bachelor's Thesis)
Python, PyTorch, Signal Processing, Medical Audio Analysis
Developing a deep learning model for the classification of respiratory sound recordings.
Processing lung sound data through signal resempling, filtering, normalization and augmentation.
Converting audio recordings into Mel spectrogram representations to enable visual-based analysis by
neural networks.

Skills
Technical Soft
Languages: Problem-solving
Proficient: Python, HTML/CSS, Java Creativity
Familiar: JavaScript, C#, C++, MATLAB Attention to detail
Databases: SQL, Redis
Tools & Technologies: Linux/Unix, Unity, Git, GitHub, Additional
PyTorch, TensorFlow, OpenCV Driving License (Category B)
Office Tools: Microsoft Excel, Word, PowerPoint
Experience
Team member, Student Research Groups, Uzhhorod National University 2017 - 2022
Responsible for collecting, analyzing, interpreting and presenting medical data
Enhanced analytical, statistical, problem-solving and IT skills

Local Exchange Officer, Ukrainian Medical Students’ Association (Uzhhorod) 2020 - 2022
Organized internships for international students in local hospitals
Developed strong organizational and interpersonal skills

English teacher, Englishdom 2023 - 2024
Conducted individual English lessons for students of various age groups

Certifications & Awards
Information Technology Specialist in JavaScript - Certiport, 2026
Information Technology Specialist in Cybersecurity - Certiport, 2026
Information Technology Specialist in HTML and CSS - Certiport, 2025
Information Technology Specialist in Python - Certiport, 2025
Scholarship Holder - Stipendium Hungaricum Scholarship Program, 2023 - Present
Second Place, Scientific Research Presentation (Neurosurgery) - Uzhhorod Medical Students
Conference, 2021

Language
Ukrainian (C2) English (C1) Hungarian (A1)
Russian (C1) Spanish (A1)