About Me
I'm a founder and AI Security Engineer with a passion for understanding complex systems and making them work better. This curiosity started early, with a fascination for how everything from machines to software operated. That same hands-on interest shows up in my personal life as a car enthusiast with a love for muscle cars and trucks, and as someone who spends as much time outdoors as possible.
Studying fluid mechanics gave me a rigorous way to model and analyze real-world systems. Later, while improving manufacturing processes at Mercedes-Benz using lean production principles, I saw how software was becoming an increasingly powerful driver of value. Working directly with production data showed me how impactful data can be when used effectively, sparking my focus on software development and machine learning.
To share my technical learnings, I started NeuralCeption where I built early experiments on adversarial examples in computer vision. I later launched DeconvoluteAI to explore NLP, RAG, and AI security. My work on these projects has been cited in academic literature including ICCIS 2023 (Springer) and arXiv. They remain my go-to space for research and taught me that the hardest problems in AI aren't just about capability, but about robustness.
This foundation drives my current focus on developing security infrastructure to protect RAG systems from adversarial attacks and supply chain vulnerabilities. DeconvoluteAI serves as the primary platform for this work, bridging theory with production-grade defensive tooling.
I'm always open to meaningful conversations with people exploring the intersection of AI Security, robust engineering, and product development. If you want to talk about cars too, I won't say no.