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Biomedical Data Scientist | Expert in Deep Learning, Medical Imaging & Computational Pathology

Profile Summary

I am a Biomedical Data Science Engineer and PhD candidate specializing in Information and Knowledge Engineering, with a focus on Artificial Intelligence applied to healthcare. My expertise lies at the intersection of deep learning, medical imaging, and clinical data integration, aimed at improving diagnostic accuracy and patient stratification.  Core Expertise & Technical Skills • Deep Learning & Computer Vision: Extensive experience in developing and training neural networks, specifically U-Net and ResNet architectures for semantic segmentation and 3D reconstruction.  • Computational Pathology: Currently researching Foundation Models for digital histopathology at IRYCIS, focusing on representation learning and interpretable tissue classification.  • Biomedical Signal Processing: Expert in analyzing and automatically labeling concurrent signals (PPG and PCG) using CNNs.  • Technical Proficiency: Advanced programming in Python, C/C++, Matlab, SQL, and R-studio, with hands-on experience in tools like CVAT, QuPath, and ITK-SNAP.  Ongoing & Notable Research Projects • TechConnect (Horizon Europe): As a Data Science Researcher, I implement advanced machine learning methods for digital histopathological image analysis, including feature extraction and patient stratification.  • BIONET Project: Developed a multi-organ semantic segmentation tool using 2D-Unet for abdominal CT images.  • 3D Neural Reconstruction: Conducted research at Universidad Autónoma de Madrid on reconstructing 3D digital models of single neuron morphologies from experimental neuroscientific data.  • Cardiac Signal Analysis: Developed an award-winning system for automatic labeling of PPG and PCG signals detected by wearable sensors.  Academic Foundation & Publications • PhD in progress: Strategic collaboration between UAH and IRYCIS.  • Master’s Degree: Biomedical Engineering (Technologies for Electronics) from Politecnico di Milano.  • Published Researcher: Co-author of peer-reviewed articles in high-impact journals such as Sensors and IEEE EMBC, covering Electrical Impedance Tomography and optimized U-Net for multi-organ segmentation.

Subject Matter Expertise

• ☆ Biotechnology & Bioengineering
• ☆ Biomedical Engineering
• ☆ Data Analysis
• ☆ Data Processing
• ☆ Machine Learning
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Computer Vision
• ☆ Python
• ☆ Matlab
• ☆ SQL
• ☆ Tensorflow
• ☆ R

Services

• Data & AI

Data & AI Predictive Modeling, Image Processing, Image Analysis, Algorithm Design-ML, Big Data Analytics, Data Processing

Work Experience

Data Science Researcher

Irycis

March 2025 - Present

Data Science Researcher

Hospital Universitario Ramón y Cajal

March 2025 - Present

Internship for Master Thesis in Neuroengineering

Universidad Autónoma de Madrid

April 2024 - December 2024

Education

Information and Knowing Engineering (Artificial Intelligence)

Universidad de Alcalá

December 2025 - Present

PhD Candidate, Artificial Intelligence in Real-Time Medical Imaging

Universidad de Alcalá de Henares - Spain

November 2025 - Present

MS Biomedical Engineering

Polytechnic Institute of Milan - Italy

September 2021 - December 2024

Biotechnologies for Electronics of Biomedical Engineering

Politecnico di Milano

September 2021 - December 2024

Biomedical Engineering

Politecnico di Milano

April 2018 - July 2021

Certifications

• TOEFL

  Toefl

  September 2025 - Present

Publications

JOURNAL ARTICLE

Antonello Conelli, Francesca Pennati, Alessandra Angelucci, Letizia Morelli, Susanna Bardini, Elena Barzanti, Federico Cavallini, Gaia Di Federico, Chiara Paganelli, Andrea Aliverti (2023). Electrical Impedance Tomography: From the Traditional Design to the Novel Frontier of Wearables . Sensors.

CONFERENCE PAPER

Antonello Conelli, Raffaele Berzoini, Aurora A. Colombo, Susanna Bardini, Eleonora D'Arnese, Marco D. Santambrogio (2022). An Optimized U-Net for Unbalanced Multi-Organ Segmentation . 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).