The Rapid Evolution of AI Music Generation
Exploring the rapid advancements in generative audio and how sequence modeling has solved long-range dependencies in AI music generation.
Field Notes
Field notes on ML security, distributed systems, and high-reliability software, written for researchers and engineering leaders. For longer-form parables, see the Essays; for interactive demos, visit the Lab.
Flight Simulators Are Becoming the AI Proving Ground
What if flight simulators are the AI proving ground nobody is talking about? Three years inside Avion.
How to Recognize Advice That Actually Helps
Entrepreneurs, researchers, and engineers live in a torrent of guidance. Podcasts, newsletters, and mentors offer conflicting prescriptions, each delivered w…
The Real Test for Making Something People Want
Scaling conversations dominate startup culture, yet the first question any product must answer is painfully small: will even one person use it when given the…
Why Great Engineering Teams Run on Curiosity
Working on simulator software, defensive cybersecurity platforms, and doctoral research has taught me that durable progress rarely starts with a perfect road…
The Myth of the Quick Fix
Every engineer knows the temptation of the “five-minute hack.” A bug appears, the schedule is tight, and a clever shortcut promises to save the day. Weeks la…
Documentation as the First User Interface
Before a developer ever sees your landing page, they might encounter your README. For many technical products, documentation is the first user interface. It …
Hiring Generalists: The Small Team’s Secret Weapon
Why early-stage engineering teams should hire for breadth and learning rate, and how generalists become the connective tissue that later scales into specialists.
The Invisible Cost of Shiny Tools
Engineering teams love new tools. The promise of faster development, cleaner abstractions, or a more elegant stack is hard to resist. Yet every adoption deci…
Why Early Beta Feedback Matters More Than Launch Day
Product launches often steal the spotlight, but the feedback gathered during early beta testing quietly determines whether launch day is a victory lap or a s…
Y Combinator and DNA: Fixed Points in Code and Biology
It started while I was nursing a Saturday-morning coffee and catching up on YouTube. Around the 11:20 mark of this talk, the speaker described the choreograp…
Proof of Learning: Building Trust in Future Machine Learning
Proof of Learning (PoL) verifies that a model was genuinely trained on claimed data by providing verifiable evidence of the training process. I first felt th…
Model Watermarking and the Future of Trustworthy AI
Model watermarking embeds identifiable patterns into a model’s parameters or outputs so that ownership can be demonstrated without access to the original tra…
ML-Enhanced Blockchain: Toward Intelligent, Adaptive Ledgers
Machine learning (ML) is increasingly used to make blockchain networks more secure, efficient, and user-friendly. When I co-authored our survey on blockchain…
Blockchain Oracles and Smart Contracts: The World’s Agile Board
Traditional agile boards depend on centralized tools and manual updates. As projects span multiple organizations and trust boundaries, these boards struggle …
Blockchain-Enhanced Machine Learning: Linking Trust, Data, and Incentives
How blockchain’s immutable ledgers and decentralized governance address auditability, provenance, and incentive-alignment challenges in machine-learning pipelines.
Autonomous Drones and Their Future Importance
Consider this your two-minute hangar brief. Between February 2019 and November 2020, I served as an Expert Software Engineer at STM Defence Technologies in A…
Adversarial Examples for Proof of Learning
Code for paper ‘Adversary examples’ for Proof of Learning
SecurePoL with Watermarking
Official code & experiments for my PhD dissertation: ‘Enhancing Security of Proof-of-Learning Against Spoofing Attacks Using Advanced Model Watermarking.’
Image Measurement with PyQt5: A Cardiology Aid
Python’s versatility allows it to create tools for a broad spectrum of professional fields. In this post I walk through building an image measurement to…
Presenting at ICISSP 2021: rare-event detection in a low-resource language
The conference talk behind the ICISSP 2021 paper: what an agglutinative language does to keyword detection, and why the false-positive rate is the number that decides whether a rare-event detector is usable.
MS Thesis
My Master of Science Thesis Project related researches, projects and documents.
Secure Proxy on Cloud Paper Demonstration
Video demonstration of the Secure Proxy on Cloud paper, covering architecture motivation, implementation details, and development roadmap.