Explorations in aerospace engineering, AI/ML, computational fluid dynamics, and the future of technology.
A fluids engineer directing an LLM through natural-language conversation produced a complete OpenFOAM simulation, parametric shape optimisation, and automated ParaView visualisation — on a bear geometry.
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Physics-informed neural networks trained on 1959 wind tunnel data capture missing physics that traditional CFD simulations miss entirely — on a single-board computer.
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How AI-powered development enabled the creation of SkyView Pro, a comprehensive real-time geospatial platform using only open-source data.
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On the fusion of young engineers' energy with deep, battle-tested wisdom of senior experts — and why the elegance of method matters more than brute-force computing.
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Smoke flow visualization, optical flow velocity vectors, and SINDy analysis on a 1:64 scale car model — all from a small wind tunnel at home.
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Why specialized tools developed by engineering firms over decades often outperform modern flashy alternatives that deviate from real-world physics.
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A tool for precise analysis of movement in video using Dlib — for loading videos, calibrating measurements, selecting regions of interest, and deriving velocity and displacement data.
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Integrating advanced computer vision (Optical Flow) with data-driven modeling (SINDy) to understand and predict fluid dynamics from video data.
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How a tiny energy-efficient powerhouse became the brain of a home automation system with Home Assistant, AI vision, and media serving.
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