I’m a Data Scientist specialized in Artificial Intelligence (AI) and Cybersecurity. I build production-ready AI systems that are secure, privacy-preserving, and designed for real-world impact across multiple industries. I’ve worked with public-sector authorities on GDPR-compliant AI, privacy-preserving techniques, and secure handling of sensitive data, combining hands-on engineering with regulatory and risk awareness.
A core part of my work is failure-mode thinking: understanding how AI systems break through data leakage, weak access controls, insecure integrations, or poorly governed pipelines, and designing architectures that reduce those risks.
Educational project demonstrating image-based malware family classification: classifying malware from pre-rendered grayscale byteplots, training a CNN from scratch, fine-tuning pretrained architectures (ResNet-50, ResNeXt-50, Inception-v3), and evaluating them.
Features:
- 25 malware families - 9,339 pre-rendered grayscale byteplot images.
- How malware can be represented as images — what byteplot layout and texture encode.
- How convolutional networks learn family-specific structure from byte sequences.
A curated collection of 12 cybersecurity projects spanning operational security, defense evasion, steganography, network security, system hardening, and hardware-based EDR evasion.
Features:
- MITRE ATT&CK defense evasion - 14 documented techniques with detection strategies and working tools.
- File-level steganography - JPEG/MP3 data hiding, polyglot files, and AES-256-GCM encrypted payloads.
- WiFi WPA2/WPA3 attack lab - Virtual and hardware-based pentesting with Aircrack-ng and Hashcat.
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Project Foresight
Try it out →
Note: since this is a WIP, it may not be accessible at all times.
Predicts weather temperature using machine learning and automated workflows.
Features:
- Integrates real-time weather and traffic data.
- Outputs weather temperature predictions based on real-time data.
- Automates data ingestion, processing, and ML predictions.
