• 🎓 Computer Science student (B.Sc.) with strong interest in software engineering and machine learning

• 💻 Experienced with Python, Java, C++, backend systems and ML models, feature engineering and data analysis

• 🔬 Completed a research seminar in Computational Learning

• 📊 Built ML models for prediction, feature engineering and model evaluation

• 🚀 Developed projects in machine learning, AI security research, and software systems

• 💬 Ask me about Python, Java, Machine Learning, Software Design

• 📫 How to reach me dolfinvarshev@gmail.com

Titanic Survival Prediction

Machine learning project predicting passenger survival on the Titanic dataset.

Key work:

• Built a baseline classification pipeline
• Feature engineering and preprocessing
• Model comparison and validation

Models used:

• Logistic Regression (baseline)
• LDA / KNN (improved)

Focus areas:

• feature engineering
• feature selection
• model evaluation

House Pricing – Advanced Regression

Predicting housing prices using the Ames Housing dataset.

Baseline models:

• Linear Regression
• SGDRegressor

Improved models:

• Random Forest Regressor
• KNN Regressor
• Bagging / AdaBoost experiments
• PCA dimensionality reduction

Focus areas:

• regression modeling
• ensemble methods
• feature engineering
• model comparison

Financial IPI Benchmark

Research project exploring Indirect Prompt Injection vulnerabilities in financial AI assistants.

Includes:

• benchmark dataset of adversarial prompts
• framework for evaluating LLM robustness
• analysis of model responses to adversarial prompts

Repository:
https://github.com/dolfinvarshev/financial-ipi-benchmark

Electronic Commerce System

Full software engineering project implementing an e-commerce platform.

Key components:

• backend architecture
• database integration
• product and order management
• API-based system design

Repository:
https://github.com/dolfinvarshev/Electronic-commerce