Yasmin Sobrinho

Data Scientist

https://talent.gravityer.com/yasmin-sobrinho

Researcher in Quantum Machine Learning | Pursuing a Bachelor's in Information Systems

Recogna Laboratory | UNESP

Key Strengths

Demonstrated interest and practical experience in Data Science, particularly in quantum-classical hybrid models for medical diagnosis (Breast Cancer).
Experience with Python and Jupyter Notebook for data science projects.
Active involvement in research-oriented projects, including paper implementations and hackathons, indicating a proactive learning approach.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards research and academic contributions, particularly in emerging fields like quantum computing applied to healthcare. This suggests a fit for roles that value innovation, continuous learning, and problem-solving in complex domains. The personal projects indicate self-motivation and initiative. However, the lack of diverse project types beyond academic/research might suggest a narrower exposure to different industry applications or team structures.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, providing no insights.

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Projects

trabalho-ia

November 26, 2025 – December 1, 2025

Trabalho final da disciplina de Inteligência Artificial

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HybridFeatureFusionForBreastCancer

March 13, 2025 – Present

This repository contains the official implementation of the paper: "On the Complementarity of Quantum and Classical Features: Adaptive Hybrid Quantum-Classical Feature Fusion for Breast Cancer Classification", under review at the Artificial Intelligence in Medicine.

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Pasqal_Hackathon_Feb25_Team_01

February 12, 2025 – March 10, 2025

Pasqal_Hackathon_Feb25_Team_01 — GitHub repository

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yrsobrinho

January 20, 2025 – November 14, 2025

yrsobrinho — GitHub repository

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trabalho-estrategias-si

October 21, 2024 – November 10, 2024

trabalho-estrategias-si — GitHub repository

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BreastCancerQuanvolution

August 29, 2024 – July 19, 2025

This repository contains the official implementation of the paper: “A Hybrid Quantum-Classical Model for Breast Cancer Diagnosis with Quanvolutions”, accepted at the IEEE CBMS 2025. Our approach integrates quantum convolutional layers into a classical pipeline to enhance the detection of malignant and benign breast cancer patterns.

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clinic

September 1, 2023 – September 27, 2023

clinic — GitHub repository

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Key Strengths

Demonstrated interest and practical experience in Data Science, particularly in quantum-classical hybrid models for medical diagnosis (Breast Cancer).
Experience with Python and Jupyter Notebook for data science projects.
Active involvement in research-oriented projects, including paper implementations and hackathons, indicating a proactive learning approach.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, providing no insights.

Yasmin Sobrinho

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit