Alessio Gallucci

Senior Data Scientist at Philips with a PhD in computer vision and AI. I work at the intersection of machine learning, 3D body modelling, and responsible AI — translating research into real products. Outside of work: chess, writing, and the occasional illogical cause.

Work Experience

Apr 2026 – Present · Full-time · Eindhoven, Netherlands

Aug 2023 – May 2026 · Full-time · Eindhoven, Netherlands

Mar 2022 – Aug 2023 · Full-time · Eindhoven, Netherlands

Created SkinAI technology for Lumea IPL 9900 Series, improving the hair removal experience.
Collected, cleaned, and preprocessed large datasets of high-resolution skin images, 3D heads, and bodies.
Conducted exploratory data analysis to identify trends, patterns, and anomalies.
Supported annotators and labeling teams using statistical analysis and data mining techniques.
Developed machine learning algorithms and models for predictive analytics and pattern recognition.
Designed and executed experiments to validate hypotheses and improve model performance.
Collaborated with cross-functional teams to deliver on business KPIs and deploy models.
Presented findings and insights to both technical and non-technical stakeholders.

Aug 2017 – Mar 2022 · Full-time · Eindhoven, Netherlands

Applied computer vision, statistics, and deep learning to model and analyze 3D body and face data.
Applied machine and deep learning techniques to analyze and parameterize skin.
Performed image segmentation, statistical analysis, and causal inference methods.
Mentored and supervised master students on: 3D head reconstruction, skin patch localization, 3D scientific visualization, and 2D–3D full-body mapping.
Actively served as a board member in the Philips Interns and Philips PhD Communities.

Aug 2020 – Present · Volunteer · Remote

Analyzed existing AI systems and algorithms to identify potential ethical and bias-related issues.
Collaborated with heterogeneous experts to integrate ethical considerations into the AI development lifecycle.
Conducted literature reviews and contributed to academic publications on Trustworthy AI.

2018 – 2022 · Full-time · Eindhoven, Netherlands

Sep 2016 – Jun 2017 · Internship · Eindhoven, Netherlands

Derived a 3D parametric model of the human body from a collection of 3D scans (CAESAR dataset).
Morphed a high-resolution template (>50k vertices) into all target scans using non-rigid registration techniques.
Encoded the linear class via PCA, reaching a compact parametric space balancing precision and generalization.
Demonstrated the model captures time-varying phenomena (ageing, weight change) with significant efficiency.
Model used in downstream tasks including skin surface and subcutaneous fat estimation.
Tools: Matlab, Bash, Git, SourceTree, Torque/Maui, SQL, Java.

Nov 2015 – May 2016 · Internship · Rome, Italy

Developed two NLP models for predicting Turin and Milan's voting preferences and economic growth trends.
Input data provided by TIM (major Italian telco): geo-referenced web traffic from those areas.
Validated models using previous election results and market indexes from open databases.
Visualized and interpreted results to support client decision-making.

Education

2017 – 2022

Certifications

Python for Everybody Specialization

Coursera / University of Michigan · Apr 2023 ID: 999R2BDHXT9K

Programming for Everybody (Getting Started with Python)
Python Data Structures
Using Python to Access Web Data
Using Databases with Python
Capstone: Retrieving, Processing, and Visualizing Data with Python

Deep Learning Specialization

Coursera / DeepLearning.AI · May 2020 ID: JT9EBGN8AN4F

Neural Networks and Deep Learning
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Structuring Machine Learning Projects
Convolutional Neural Networks
Sequence Models