University of Eastern Finland · Center for Photonics Sciences
I am a Postdoctoral Researcher at the University of Eastern Finland (UEF), Center for Photonics Sciences. I work at the intersection of machine learning, spectroscopy, computational photonics, inverse problems, and uncertainty-aware AI.
My current research includes THz and Raman data analysis, transfer-matrix-model optimisation, inverse reconstruction, spectral modelling, uncertainty quantification, and TEM image analysis. I also develop reproducible research software for machine-learning and HPC workflows.
During my PhD, I investigated handwriting-based biomarkers for neurological screening, combining deep learning, Bayesian classifier fusion, evolutionary computation, multimodal learning, and explainable AI.
Research goal: build machine-learning systems that are not only accurate, but measurable, reproducible, and useful in scientific practice.
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Horizon Europe · MSCA Staff Exchanges Machine learning for THz and optical data, transfer-matrix-model optimisation, inverse reconstruction, Raman analysis, and spectral data processing. |
Horizon Europe · EIC Pathfinder Open Machine-learning research, THz fingerprint e-library development, data curation, spectral analysis, and software for THz measurement data. |
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Rome · 2026 THz-based non-invasive glucose sensing, signal-processing pipelines, feasibility analysis, and work with industrial measurement requirements. |
HPC · optimisation · reproducibility Machine-learning and optimisation experiments on CINECA systems, numerical studies, reproducible ingestion pipelines, and containerised research software. |
| 15 Peer-reviewed publications |
7 First-author papers |
1 Best paper award |
2 Horizon Europe projects |
Toward Reliable Uncertainty Quantification in Surrogate-Assisted Evolutionary Algorithms via Temporal Conformal Prediction.
- Nardone E., D'Alessandro T., Cilia N.D., Fontanella F. (2025). Handwriting strokes as biomarkers for Alzheimer's disease prediction. Computers in Biology and Medicine, 190:110039.
- Nardone E., D'Alessandro T., De Stefano C., Fontanella F., Scotto di Freca A. (2025). A Bayesian network combiner for multimodal handwriting analysis in Alzheimer's detection. Pattern Recognition Letters, 190:177–184.
- Nardone E., D'Alessandro T., De Stefano C., Fontanella F. (2025). How Data Augmentation Affects Evolutionary Algorithms in Feature Selection. SN Computer Science, 6(5):536.
- Nardone E. et al. (2026). Toward Reliable Uncertainty Quantification in Surrogate-Assisted Evolutionary Algorithms via Temporal Conformal Prediction. EvoApplications 2026, LNCS, 384–401. Best EvoApps Paper Award.
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Fractal, lacunarity, multifractal, directional, topological, and morphological measurements from handwriting images.
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Bayesian-network model stacking, feature-importance analysis, and hyperparameter optimisation.
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Deep-learning models for handwriting classification, including recurrent, Transformer, and attention-based architectures.
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Machine learning & scientific computing
Methods: evolutionary computation · genetic programming · Bayesian networks · conformal prediction · uncertainty quantification · explainable AI · multimodal learning
Programming & research computing
Systems: CINECA HPC · GPU computing · containers · Linux · reproducible machine-learning workflows
timeline
title Academic and Professional Path
2021 : MSc Software Engineering
: 110/110 summa cum laude
: University of Cassino and Southern Lazio
2021-2022 : Research Fellow
: Handwriting ML and acquisition software
2022-2026 : PhD in Artificial Intelligence
: University of Cassino and Southern Lazio
2024 : Visiting PhD Researcher
: NOVA IMS, Universidade NOVA de Lisboa
2024-2025 : Adjunct Assistant Professor in AI
: MSc Software Engineering
2026-now : Postdoctoral Researcher
: University of Eastern Finland
: HERMES and THz-Skin
Awards, academic service & teaching
| Role | Activity |
|---|---|
| 🏆 Award | Best EvoApps Paper Award — EvoStar 2026 |
| 🎤 Workshop Chair | BIOMAP @ ICPR 2026 |
| 🌐 Conference organisation | International Conference on Nano-, Tera-, and Bio-Photonics 2026, Joensuu |
| 📝 Journal reviewing | Springer Nature AI journal · Intelligence-Based Medicine · Engineering Applications of Artificial Intelligence · Applied Soft Computing · Scientific Reports |
| 🔍 Conference reviewing | GECCO 2026 · PPSN 2026 · BIOMAP/AHIA @ ICPR 2026 · MCMI @ ICPR 2024 |
| 👨🏫 Teaching | Adjunct Assistant Professor in Artificial Intelligence |
| 🎓 Training | IEEE Trainer for Europe · Generative AI Tutor |
| 🧑🔬 Mentoring | UEF Summer Internship Supervisor — 2026 |
I am interested in joint research on AI for spectroscopy, computational photonics, uncertainty-aware machine learning, inverse problems, evolutionary computation, biomedical AI, explainable AI, and scientific software.
AI research · scientific software · reproducible machine learning