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DavideDeplano/README.md

👋 Hi, I'm Davide Deplano

Machine Learning · AI Security · Data Analytics on real-world data

🎓 BSc Applied Computer Science & Data Analytics — UniCa · Jul 2026
🎯 MSc Computer Engineering, Cybersecurity & AI — UniCa · from Sep 2026
📍 Cagliari, Sardinia 🇮🇹 · 🌍 Open to remote & international roles


🚧 Currently building

RAG agent over course PDFs with page-level citations. e5-base embeddings, ChromaDB, Gemini 2.5 Flash.


🧩 Selected Projects

Multi-stage anomaly-detection pipeline for SETI-like signals on real Sardinia Radio Telescope data — 9-month INAF internship. NCC-max cross-correlation extractor, UMAP + KDE pre-filter, bagged-GMM scoring, memory-mapped training on 1.28M synthetic cadences.

PM10 across Sardinia's monitoring network vs EU limit values — 6M measurements from the EEA archive. One station over the daily limit in five years out of ten; the industrial sites come out cleaner than background. Python pipeline + Power BI dashboard.

wav2vec2 + classification head, served via FastAPI / Docker with CI. Measures the generalisation gap: EER 3.66% in-studio · 8.52% unseen attacks · 29.66% in-the-wild.

CNN deepfake detector under PGD white-box and transfer attacks, hardened with adversarial training (Madry et al., 2018). Recovers ~26 points at ε=0.01 at negligible clean-accuracy cost.

Supervised vs unsupervised NIDS on KDD Cup 1999. RF F1 ≈ 0.999 · One-Class SVM 0.994 · MLP 0.990 · VAE 0.969.

Hands-on SIEM detection engineering on Wazuh. Attacked with Atomic Red Team, wrote custom rules mapped to MITRE ATT&CK for gaps the default ruleset missed — credential access, cron persistence, defense evasion. FIM tuning + rule authoring, validated against each attack.

Credit-card default prediction on UCI dataset. Random Forest: accuracy 0.82, ROC-AUC 0.76. SMOTE lifts minority-class recall 0.37 → 0.47.

Production-style Python data pipeline: uv · pytest · mypy · ruff · GitHub Actions CI. Hot path JIT-compiled with Numba + parallelised with Joblib after Scalene profiling.


🛠️ Tech Stack

Languages

ML & Data

Engineering

Databases & Viz


🔧 What I work on

  • Machine Learning & Deep Learning — CNNs, autoencoders, VAEs, GMMs, manifold learning, tree-based & kernel methods
  • AI Security — Adversarial robustness, evasion attacks (PGD, transfer), adversarial training defenses
  • Blue Team / SOC — SIEM detection engineering on Wazuh, MITRE ATT&CK mapping, adversary emulation with Atomic Red Team
  • Data Analytics & BI — Open data pipelines, regulatory thresholds, Power BI dashboards
  • Data Science — End-to-end pipelines on real, imbalanced data
  • Software Engineering — Modular Python, testing, static typing, CI, FastAPI, Docker, profiling

⭐ Explore my pinned repositories or reach out on LinkedIn.

Pinned Loading

  1. srt-anomaly-detectionsrt-anomaly-detectionPublic

    Modular anomaly-detection pipeline for SETI-like radio signals from the Sardinia Radio Telescope (SRT). Implementation and adaptation of Pardo et al. (AJ 2025): density filter (UMAP + KDE on cross-…

    Python 1

  2. audio-deepfake-detectionaudio-deepfake-detectionPublic

    Synthetic speech detection with a frozen wav2vec2 encoder and a trained classification head. Measures the generalisation gap between studio and real-world audio: 8.5% EER on ASVspoof, 29.7% In-the-…

    Jupyter Notebook 6

  3. wazuh-detection-labwazuh-detection-labPublic

    Wazuh SIEM home lab: attacked with Atomic Red Team, custom detection rules mapped to MITRE ATT&CK for gaps the default ruleset missed.

  4. deepfake-detection-cnn-adversarialdeepfake-detection-cnn-adversarialPublic

    Binary CNN deepfake detector comparing RGB vs grayscale inputs; adversarial robustness evaluation under PGD (white-box) and transfer (black-box) attacks, with PGD adversarial training (Madry et al.…

    Jupyter Notebook 1

  5. cyberai-study-agentcyberai-study-agentPublic

    AI study companion agent for LM Cybersecurity & AI coursework

    Python 2

  6. sardinia-air-qualitysardinia-air-qualityPublic

    PM10 across Sardinia's monitoring network, checked against EU limit values. Python + Power BI.

    Python