Emanuele Donno
Computer EngineerML/AI EngineerPhD StudentQuantum Computing & Quantum ML
Lecce, Italy
emanuele.donno@gmail.com
shtazzo.github.io
linkedin.com/in/emanuele-donno
github.com/Shtazzo
0009-0006-2126-4816
Professional Summary
Licensed Computer Engineer (Order of Engineers, Lecce – Sec. A, Sector C, since 06/2024) and PhD Student in Engineering of Complex Systems at Università del Salento, working on Quantum Computing and Quantum Machine Learning for Climate Science. About 18 months as Post-Degree Researcher at the Euro-Mediterranean Centre on Climate Change (CMCC), working on end-to-end ML/DL pipelines on multidimensional NetCDF climate datasets and on ML4Fires, the wildfire-forecasting thematic module of the EU InterTwin Digital Twin project, on HPC infrastructure. Full-stack engineering background from MSc projects and thesis work, covering Python, Java/Spring Boot REST, Angular/Ionic, Docker, Git and MPI/HPC. First author of a preprint on quantum data assimilation under review at FGCS; co-author of peer-reviewed and preprint contributions on Digital Twins and ML for extreme weather events.
Technical Skills
- Languages
- Python, Java, TypeScript, C, SQL, Shell/Bash, Matlab, LaTeX
- AI & ML
- PyTorch, TensorFlow, Keras, Scikit-Learn, Computer Vision, end-to-end ML pipelines, distributed training
- LLM & GenAI (personal projects)
- Ollama (local LLMs), Hugging Face, RAG, prompt engineering, LLM-assisted dev workflow (Claude Code, ChatGPT, Gemini)
- Quantum (learning during PhD)
- Qiskit, PennyLane, Quantum Computing, Quantum Machine Learning, Quantum Circuits, Quantum Data Assimilation
- Backend & Infra
- Spring Boot, REST APIs, Docker, Git, MPI/MPICH, HPC, Linux/Unix
- Frontend
- Angular, Ionic, TypeScript, HTML5/CSS, Firebase
- Data & Storage
- NumPy, Pandas, NetCDF, Xarray, Cartopy, MySQL, MongoDB, SQLite
Professional Experience
Post-Degree Researcher|CMCC Foundation – ADIC Division (Lecce, Italy)
06/2023 – 11/2024
Advanced Scientific Computing for Climate Change
- Worked on ML4Fires (github.com/CMCC-Foundation/ML4Fires), the wildfire-forecasting thematic module of the EU InterTwin project (Grant Agreement 101058386), within the Environmental Digital Twin Engine for wildfire propagation and projection at global scale.
- Worked on end-to-end ML/DL pipelines (data preparation, feature engineering, training, evaluation) for CNN, U-Net and U-Net++ architectures on a global multi-source climate datacube called SeasFire Cube v3 (NetCDF/Xarray) and CMIP6 SSP projections in inference.
- Helped migrate the training stack from TensorFlow to PyTorch and run it in multi-node, multi-GPU distributed training on HPC infrastructure; ran containerized inference on HPC.
- Adopted MLflow for experiment tracking and reproducibility of training runs.
Education
PhD in Engineering of Complex Systems2024 – Present
Università del Salento – Lecce, Italy
Research project: Quantum Computing and Quantum Machine Learning approaches for Climate Change applications.
M.Sc. in Computer Engineering|Grade: 105/1102019 – 2023
Università del Salento – Lecce, Italy
Thesis: Global downscaling of remotely sensed soil-moisture retrievals using Machine Learning.
Relevant coursework: Big Data Management, High Performance Computing, Computer Vision, Software Engineering, Internet of Things, Parallel & Sequential Algorithms, Network Technologies.
B.Sc. in Information Engineering|Grade: 97/1102016 – 2019
Università del Salento – Lecce, Italy
Thesis: Design and development of a back-end subsystem for an event-management service (Spring Boot REST).
Publications & Preprints
Full list and metrics: orcid.org/0009-0006-2126-4816
- interTwin: Advancing Scientific Digital Twins through AI, Federated Computing and Data.
Future Generation Computer Systems (FGCS) – The International Journal of eScience, 2026. Journal article.
DOI: 10.1016/j.future.2025.108312 (WOS:001651938800001)
- From Classical to Quantum-Mechanical Data Assimilation: A Comparison between DATO and QMDA.
E. Donno, G. Conti, P. Oddo, S. Gualdi, L. Mainetti, G. Aloisio.
Submitted to Future Generation Computer Systems (FGCS), Special Collection on Advances in Quantum Computing: Methods, Algorithms, and Systems. Vol. III (Under review)
Preprint (arXiv), May 2026. arXiv: 2605.04881
- Facilitating the development of Machine Learning-based Digital Twin applications for extreme weather events.
D. Elia, E. Donno, M. Bunino, M. Fronza, D. Donno, G. Padovani, S. Fiore, A. Manzi.
EGU General Assembly 2025 – Preprint, March 2025.
DOI: 10.5194/egusphere-egu25-13888
- A Data Space environment for Big Data and ML-based Climate applications in the European Open Science Cloud.
D. Elia, F. Antonio, S. Fiore, E. Donno, G. Accarino, P. Nassisi, G. Aloisio.
EGU General Assembly 2024 – Preprint, January 2025.
DOI: 10.5194/egusphere-egu24-17472
Selected Projects
- ML4Fires – InterTwin Digital Twin Engine
Core ML/DL component of an Environmental Digital Twin for global wildfire propagation, integrated into the EU InterTwin platform; reproducible training pipeline distributed on HPC. github.com/CMCC-Foundation/ML4Fires
- Global Soil-Moisture Downscaling
ML-based downscaling of satellite-derived soil-moisture products on the EASE 2.0 grid; pipelines for multidimensional Earth-observation datasets.
- Social Tech Platform – Full-Stack
LinkedIn-style multi-user platform: Angular + Ionic frontend, Spring Boot REST backend, Firebase for push and bulk notifications; end-to-end ownership from architecture to deployment.
- Drupal CMS Plugin for Remote Learning
Drupal content-management plugin backed by a Spring Boot service over a Materialized-Table relational schema; Angular web client; stored procedures for config/data exchange between backends.
- MAD – My Accessible Data
Multi-user system for secure personal-data management using IOTA’s Masked Authenticated Messaging (MAM) protocol over the Tangle blockchain; Angular/Ionic frontend, Spring Boot REST backend.
- Parallel Fast Hartley Transform (FHT)
Parallel design and implementation of the Fast Hartley Transform (FHT) in the one-dimensional case, using the message passing C library MPICH.
- COVID-19 Spread Modeling
Polynomial and multivariate regression, and Kalman filtering applied to Covid-19 spread modeled with the SIR compartmental model.
Certifications & Awards
- Samsung Innovation Camp – Diploma in Innovation & Technology, Business Strategy, Digital Marketing (Mar. 2019).
- IELTS Academic – English proficiency, Overall 6.0/9.0, CEFR B2 (Jul. 2019).
- ICIAP 2021 – 21st International Conference on Image Analysis and Processing (May 2022).
- Professional Engineering License – Order of Engineers of Lecce (Sec. A, Sector C, N° 4507), since 25/06/2024.
- JUNIQ-EPIQ Summer School on Quantum Computing – Forschungszentrum Jülich; gate-based algorithms and quantum annealing (Sep. 2025).
- Quantum Machine Learning with Python & Qiskit – IBM SkillsBuild; building basic and advanced models, implementing algorithms, challenges and future prospects (May 2026).
- Introduction to FastAPI – DataCamp (Jun. 2026).
- Introduction to Power BI – DataCamp (Jun. 2026).
- Large Language Models (LLMs) Concepts – DataCamp (Jun. 2026).
Languages. Italian (native), English (CEFR B2 – IELTS Academic 6.0/9.0).