Simone Amoroso
Head of Technology & CISO
Experience
Head of Technology & CISO
AI Quality and Testing Hub
- Lead developer of Prof. Valmed, the first LLM-powered medical device (utilising RAG on a medical corpus of 2.5M+ documents) to receive a CE certification.
- Designed and implemented cloud-native MLOps infrastructure for ENBW’s energy trading analytics division, enabling scalable deployment and monitoring of predictive models.
- Architected end-to-end testing and validation frameworks for AI/ML systems, ensuring quality, compliance, and robustness in critical and regulated applications.
- Conducted professional training on AI testing, EU regulatory frameworks, and quality assurance for production AI systems.
Staff Scientist in the CMS experiment and Lecturer at Uni. Wuppertal
DESY (Deutsches Elektronen-Synchrotron)
- Led a 50 people group in the development of ten python data analyses for peer-reviewed publications using a variety of statistical (classification, regression, hypothesis testing) and machine learning (BDT, Random Forest, DNN) techniques.
- Introduced and optimised Deep Neural Network machine learning algorithms in tensorflow to reweight Monte Carlo simulation parameters, reducing by up to a factor of five the need for (expensive) simulated events in the collaboration.
- Trained generative AI models in pytorch to accurately reproduce expensive Monte Carlo simulations.
- Spearheaded the development of the xFitter open-source C++ code for non-linear regression analyses.
- Lecturer in particle physics and data analysis at university courses and physics schools.
- Mentored and supervised over 20 students (from B.Sc. to PostDoc) in data analysis projects.
Senior Research Fellow in the ATLAS experiment
DESY (Deutsches Elektronen-Synchrotron)
- Lead a statistical combination of W-boson mass measurements for which I developed a python tool to study uncertainty models and correlations.
- Head of the Physics Modeling Group, liaised between data analysis teams and upper management for the optimal and efficient distribution of computing cloud and HPC resources (∼300K CPU cores).
- Defined the long-term computing strategy of the experiment (CPU and GPU needs).
- Steered the 150-member strong team to commission, validate, and bring to production novel theoretical models and Monte Carlo simulation.
Senior Research Fellow in the ATLAS experiment
CERN (European Organization for Nuclear Research)
- Head of a 4 people strong team which I steered to timely complete two data analysis publications using python and C++.
- Improved the efficiency of the real-time C++ data selection algorithms of the ATLAS experiment leading to a 30% performance enhancement.
- Optimised theoretical model parameters through a linear regression analyses optimising 100 parameters using over 50 input datasets (over 10000 measurements) and documented the results in several peer-reviewed publications.
Dr.Rer.Nat. (Ph.D.) in Physics working in the ATLAS experiment
Albert-Ludwigs Universität Freiburg
- Developed a novel model-independent global search, an unsupervised approach to classify and simultaneously analyse all high-energy events produced by the Large Hadron Collider (105 regions in over 700 distributions) to test for possible deviations from the theoretical models.
- Developed Professor, a python program for hyperparameter tuning of problems with expensive to evaluate objective functions, extended the code to deal with systematic uncertainties and correlations, and implemented a Support Vector Regressor for parameter optimisation.
Industries Experience
See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.
Experienced in Education (14 years), Energy (2 years), Healthcare (2 years), and Information Technology (2 years).
Business Areas Experience
The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.
Experienced in Research and Development (14 years), Information Technology (5 years), Business Intelligence (2 years), and Quality Assurance (2 years).
Summary
Physics Ph.D. with a decade of hands-on experience in data science, AI, and scientific computing. I’ve worked on everything from statistical modeling and simulation to machine learning and large-scale data processing across high-stakes, large-scale settings; from the big particle detectors at CERN to critical applications in healthcare and the energy sector. I’ve taken on both technical leadership and deeply hands-on roles, with end-to-end experience from early design and prototyping to implementation and large-scale production deployment. I thrive working on hard problems in fast-paced environments, especially when the stakes are high and the work demands both focus and creativity.
Skills
- Programming: Python (Numpy, Scipy, Pandas, Matplotlib), C++, Sql, Fortran, Bash
- Machine Learning: Pytorch, Tensorflow, Keras, Pymc, Scikit-learn, Langchain
- Applications: Ms Office, Ms Excel/vba, Ms Power Bi
- Tools: Aws/azure, Github/gitlab, Cmake, Jupyter, Jira, Docker
- Soft Skills: Problem Solving, Project Management, Strategic Thinking, Communication
Languages
Education
Albert-Ludwigs Universität Freiburg
Dr.rer.nat. in Physics, working in the ATLAS experiment · Physics · Freiburg im Breisgau, Germany
University of Rome Tor Vergata
M.Sc. in Physics · Physics · Rome, Italy · 110/110 cum laude
University of Rome Tor Vergata
B.Sc. in Physics · Physics · Rome, Italy · 110/110 cum laude
Certifications & licenses
CE certification
Profile
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