Phone:

Hidden from the page source until you click: friction against scrapers, not a guarantee.

Email:

[email protected]

Qualifications

Fifteen certificates, each verifiable at source.

Three specialisations and twelve individual courses completed between late 2024 and 2026 alongside full-time work, mostly to put a formal footing under things I was already doing on the job: ethical hacking for the security assessments, applied cryptography for Fury, Go for both Fury and Squish, and explainable AI for the statistical work behind DAS. Every entry links to the issuer's own verification page rather than a copy hosted here, so nothing has to be taken on trust.

Specialisations

  • University of Colorado System
    Applied Cryptography: Specialization
    Completed 5 September 2026

    Four courses that walk from Shannon's information theory to the primitives that protect real systems: block and stream ciphers, public-key cryptography, key management, hash functions, message authentication and digital signatures. The complete grounding behind Fury's hybrid key agreement, its ChaCha20-Poly1305 payload and the header MAC that binds the format together.

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  • University of California, Irvine
    Programming with Google Go: Specialization
    Completed 5 September 2026

    Three courses taught by UC Irvine's Ian Harris, covering the language from its type system to its scheduler: Getting Started with Go; Functions, Methods, and Interfaces in Go; Concurrency in Go. A formal footing under the language behind Fury, Squish and the tooling that publishes this blog every morning.

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  • Duke University: Pratt School of Engineering
    Explainable AI (XAI): Specialization
    Completed 15 July 2026

    Three courses (Developing Explainable AI, Interpretable Machine Learning, Explainable Machine Learning) on making model output something a person can question and defend: when to reach for an inherently interpretable model, when to explain a black box after the fact, and how to judge whether an explanation is faithful or merely plausible. The reason every DAS anomaly score comes with a reason.

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Courses

  • Johns Hopkins University
    A Crash Course in Data Science
    Completed 29 June 2026

    The whole discipline in one sweep: what separates a statistical question from a machine-learning one, how experiments and observational studies differ, what makes an analysis reproducible and how to tell a convincing result from a lucky one. The thinking that stops a pretty graph being mistaken for evidence, and the foundation DAS's scoring rests on.

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  • University of Colorado System
    Cryptography and Information Theory
    Completed 3 September 2026

    Why some secrets are mathematically unbreakable and most are merely expensive to break. Entropy, perfect secrecy and the one-time pad, computational security, brute-force cost and Kerckhoffs's principle: the vocabulary for reasoning honestly about what an encryption scheme actually promises. Part of the Applied Cryptography specialisation.

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  • University of Colorado System
    Symmetric Cryptography
    Completed 3 September 2026

    The workhorses of modern encryption from the inside: how block ciphers such as AES are built, why ECB leaks and CBC, CTR and authenticated modes do not, how stream ciphers generate keystreams and where padding, IVs and nonces go wrong in practice. Directly informs the STREAM-style ChaCha20-Poly1305 payload encryption in Fury. Part of the Applied Cryptography specialisation.

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  • University of Colorado System
    Asymmetric Cryptography and Key Management
    Completed 3 September 2026

    RSA, Diffie-Hellman and elliptic-curve key exchange taken apart, then the harder problem nobody demos: distributing, rotating, escrowing and revoking keys at scale, and what certificates and a PKI really certify. Underpins Fury's hybrid FrodoKEM-640 and ML-KEM-768 key agreement and its fingerprint-based recipient resolution. Part of the Applied Cryptography specialisation.

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  • University of Colorado System
    Cryptographic Hash and Integrity Protection
    Completed 5 September 2026

    How SHA-2 and its relatives turn arbitrary data into fixed fingerprints, what collision and preimage resistance guarantee, how HMAC turns a hash into an authentication tag and how digital signatures deliver non-repudiation. The integrity half of Fury's format, where a header MAC binds the encrypted recipient blocks to the payload. Part of the Applied Cryptography specialisation.

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  • University of California, Irvine
    Getting Started with Go
    Completed 4 September 2026

    The language from first principles: types, slices, maps and structs, JSON encoding, file handling and the conventions (gofmt, packages, error values) that make Go code look the same in every codebase. The idiom Fury and Squish are written in. Part of the Programming with Google Go specialisation.

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  • University of California, Irvine
    Functions, Methods, and Interfaces in Go
    Completed 4 September 2026

    How Go does object orientation without classes: first-class functions and closures, methods on any type, interfaces satisfied implicitly, embedding instead of inheritance and polymorphism without a hierarchy. The design vocabulary behind Fury's versioned suites and Squish's pipeline stages. Part of the Programming with Google Go specialisation.

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  • University of California, Irvine
    Concurrency in Go
    Completed 5 September 2026

    Goroutines, channels and the select statement, mutexes and the sync package, the memory model, and the race conditions, deadlocks and livelocks that follow from getting any of them wrong. The material behind the blog's worker-pool, sync.Once and context cancellation posts. Part of the Programming with Google Go specialisation.

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  • Duke University
    Developing Explainable AI (XAI)
    Completed 29 June 2026

    The foundations: interpretability versus explainability, who an explanation is for (a regulator, an engineer, the person the decision affects), the taxonomy of methods, and how to evaluate an explanation rather than take it on trust. Part of the Explainable AI specialisation.

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  • Duke University
    Interpretable Machine Learning
    Completed 13 July 2026

    Models that explain themselves by construction: linear and logistic regression, generalised additive models, decision trees and rule lists, monotonic constraints and the trade-offs against accuracy. The approach DAS takes wherever a transparent detector will do the job. Part of the Explainable AI specialisation.

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  • DeepLearning.AI
    AI For Everyone
    Completed 4 September 2026

    Andrew Ng's plain-language account of what current AI can and cannot do, how to scope and run an AI project, how to build an AI strategy that survives contact with real data and the ethical and societal questions that come with it. Useful framing when deciding what AI should be pointed at, and what it should be kept away from.

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  • Cisco Networking Academy Ethical Hacker badge, verified on Credly
    Cisco Networking Academy
    Ethical Hacker
    Issued 16 December 2024

    Penetration testing as a discipline rather than a bag of tricks: scoping and the engagement paperwork, reconnaissance and vulnerability scanning, social engineering, exploiting wired and wireless networks, applications, cloud, mobile and IoT, post-exploitation, and writing the report a client can actually act on. The offensive half of the security work: knowing exactly how systems fall is what makes the defensive assessments credible.

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