Mihail Dobroslavski

Data Scientist

https://talent.gravityer.com/mihail-dobroslavski

Sofia University "St. Kliment Ohridski"

Key Strengths

Demonstrated interest in Data Science through the 'Pneumonia-Detection-XAI' project, which includes deep learning, imbalanced data handling, and Explainable AI (XAI).
Experience with Python, a core language for Data Science.
Exposure to C++ and web technologies (JavaScript, HTML, CSS) indicates a broad technical foundation, though not directly aligned with Data Scientist role.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic, indicating a self-driven learning approach. The 'Pneumonia-Detection-XAI' project shows initiative in a relevant domain. However, the overall project diversity is skewed towards academic coursework, and the single professional experience listed as 'Data Scientist' at Sofia University has a future start date, making it difficult to assess current cultural fit or practical experience.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, providing no insights.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

Management-software

June 12, 2026 – Present

Management-software — GitHub repository

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CourseFlow

February 12, 2026 – Present

A dynamic course management system with drag-and-drop functionality for organizing lessons, modules, and topics. Built with React and Node.js for seamless user experience and backend integration.

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fmi-si-web-2025-2026

February 9, 2026 – Present

fmi-si-web-2025-2026 — GitHub repository

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fmi-is-fp-2025-2026

February 9, 2026 – Present

fmi-is-fp-2025-2026 — GitHub repository

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fmi-kn-4-oop-2025-2026

February 9, 2026 – Present

fmi-kn-4-oop-2025-2026 — GitHub repository

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Pneumonia-Detection-XAI

January 18, 2026 – Present

This repository contains an end-to-end deep learning pipeline for detecting pneumonia from chest X-ray images. Key features include an optimized VGG16 architecture, handling of imbalanced medical data, and Explainable AI (XAI) integration using Grad-CAM to visualize diagnostic regions. Achieved 99.74% Recall to ensure clinical reliability.

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fmi-kn-4-up-2025-2026

October 2, 2025 – December 18, 2025

fmi-kn-4-up-2025-2026 — GitHub repository

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fmi-kn-4-oop-2024-2025

February 20, 2025 – August 7, 2025

fmi-kn-4-oop-2024-2025 — GitHub repository

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fmi-kn-4-up-2024-2025

October 2, 2024 – January 17, 2025

Материали за курса по УП-практикум за специалност "Компютърни науки", първи поток, към ФМИ, група 4

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FMI-SDP-2024

October 1, 2024 – January 18, 2025

Материали за курсът СДП и СДП-практикум във ФМИ за учебната 2024/25 година

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Key Strengths

Demonstrated interest in Data Science through the 'Pneumonia-Detection-XAI' project, which includes deep learning, imbalanced data handling, and Explainable AI (XAI).
Experience with Python, a core language for Data Science.
Exposure to C++ and web technologies (JavaScript, HTML, CSS) indicates a broad technical foundation, though not directly aligned with Data Scientist role.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, providing no insights.

Mihail Dobroslavski

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit