2021 — present
I like math and I like software, so naturally I ended up in quantitative
finance as a hobby. What started as curiosity turned into Lumin, a
systematic signal model for crypto futures. It mines statistically robust
price patterns from historical data, validates them out-of-sample, and
deploys them across four timeframes (1d, 8h, 4h, 2h) on Binance perpetual
futures. The current database holds 3,854 validated signatures. The 2026
out-of-sample results so far: +41.7% return, 84.5% win rate, 11.37 Sharpe,
on four symbols starting from $500K simulated capital.
I built a terminal interface to explore the live model results.
LUMIN> open terminal
LUMIN> white paper
2015 — present
I joined SYLVAC SA in Crissier, Switzerland, as an applied optics
engineer building vision metrology systems — optics, illumination,
cameras, image processing, motion control. In 2018 I moved to project
management, owning end-to-end delivery of optical measurement machines:
specs, industrialisation, production handoff. Since 2021 I lead the R&D
team, making machines more intelligent and more autonomous —
embedded agents, adaptive workflows, UX for robots. Machines should and
will interact with humans better and more naturally.
Watch the testimonial →
Machine vision · optical metrology · quality control ·
robotic guidance · automation
2012 — 2015
Before SYLVAC, I was an applied optics engineer at Hexagon
Manufacturing Intelligence. I worked on metrological machines, optical
sensor development, and image processing for precision measurement systems.
2022 — 2024
Applied Data Science: Machine Learning program at the EPFL
Extension School. This is where the quantitative finance rabbit hole
started.
2010 — 2012
MSc in Microengineering — Photonics and Applied Optics at
École Polytechnique Fédérale de Lausanne (EPFL).
Photonics (light guides and lasers), advanced image processing, optical
system design.
2007 — 2010
BSc in Microengineering at
École Polytechnique Fédérale de Lausanne (EPFL).
Optics, vision systems, mechanics, electronics, software engineering.
I cross domains. Precision metrology, machine learning, quantitative
finance — the work is always the same: understand the physics, build
the math, write the code, ship it. My training is in applied optics,
computer vision and robotics, and I’m detail-obsessed by nature — I tend to stay on
problems longer than most people think is reasonable.
