My breakthrough: I asked what an mp3 is. An array of numbers that pushes air, every second.
Then I asked what the eye sees. Only 2D. The brain guesses the shadows and the shapes.
Telemetry is the world read as numbers. Sound, images and text all arrive as arrays, and I build
the systems that turn them into decisions. Music and OCR are my passions, so most of this started as a challenge I
set myself, and the best of it went to production.
Lane 01Sound
audio, voice and music as feature spaces
in production
Lane 02Vision · OCR
pixels into text, text into structure
challenges · projects next
Lane 03Language · NLP
raw text into retrieval and agents
in production
Lane 01 · Sound
Air pressure, sampled. Everything else is features.
A song, a voice or a full room is one long array. I cut it into frames, extract what the ear and
the room care about, compress it and let the structure show itself.
01wave
the raw array, live or recorded
02frames
short windows, noise filtered
03features
100+ DSP features per frame
04PCA
the few directions that matter
05KMeans
moments that sound alike
06decide
similarity scored, acted on, evaluated
productionlive venue
A room that listens
Real-time crowd detection in a live venue, by filtering for voice frequencies, then 100+ features through PCA
and KMeans into similarity scoring. It adapts while people are in the room, and a continuous evaluation loop
checks it in production.
passionmusic
The DJ booth as a recommender
Python systems that turn tracks into structured feature spaces for real-time, context-aware music decisions,
with cover art alongside the signal for a richer picture of a song. Behind the decks it runs live: sequencing,
energy progression, and the floor as the feedback loop.
Lane 02 · Vision · OCR
We only see 2D. The rest is a guess, so I teach the machine to guess well.
An image is a grid of numbers, the same way a song is a line of them. OCR is where vision meets
language: find the text, read it, and give it back a shape a database can hold. It is a passion of mine, and the
projects are coming to this page.
01pixels
the grid, as the camera gave it
02clean
light, angle and noise fixed
03find
where the text lives
04read
characters into words
05structure
words into rows and fields
Lane 03 · Language · NLP
Text is the messiest signal of all.
Scraped pages, spreadsheets and documents come in broken. I clean them, cut them into pieces a
model can quote, and build retrieval and agents on top, with telemetry on every step so I can see what it did.
01scrape
the web and the files
02clean
one shape, no junk
03chunk
passages worth quoting
04retrieve
RAG over their own records
05agents
do the work, logged
06measure
evaluated, every step
In production in the financial decision-support RAG and the M&A Training Hub (see Portfolio).
The sound playground
Twenty tracks. Every one a challenge I set myself.
Where sound goes once you can read it. I built each of these to learn the edge of it, not for a
client. Press play anywhere.
Side A
A1Voice authenticationsecure logins for banking apps