Videographer

His body of work extends from the deployment of second-order Lumion derivative logic (jerk analysis) in actual real-time market scenarios, through ADX, choppiness indicators, and Bollinger Bandwidth dynamics to the design of high-frequency volatility-tracking algorithms. He has built fully modular automation pipelines featuring conditional logic trees, noise filters, and normalization for time-series optimization.

Having experience in legal transcript QA and metadata structuring, Joel is proficient in semantic pattern detection and linguistic entropy reduction in high-noise text corpora. He employs rule-based heuristics and NLP tokenization models to ensure maximal parsing correctness in legal corpora.

His automation activities are extended to blueprint-based 3D model generation as well, where he employs geometric parsing algorithms and object classification models to generate Lumion-compatible architectural models with programmatic camera routing and material rendering presets.