About

    I’m a researcher and systems engineer working on machine learning, robotics and space technology. What I’m building toward is my own lab in that space: autonomous spacecraft, ML-driven scientific instruments, and the flight software that connects them. The work I do now points that way. I train models for science, put LLMs into real systems, and spend a lot of time on how computation behaves under the physical limits of space.

    I currently work at the SETI Institute as an Intelligence Engineer, applying machine learning to radio and astrophysical data in the search for non-human technosignatures. I train models, write inference code, and build the data and ML tooling that scientists rely on, work that also goes into upcoming publications. Alongside that, I’m finishing a master’s in aerospace engineering focused on ML-based CubeSat design and LLM-based satellite and ground-station orchestration, built on a computer science background in computer vision and embedded systems. My research interests run across exoplanet detection, SETI, technosignatures, biosignatures and exobiology.

    Behind the research is more than 2 decades of building systems that can’t afford to fail. I think of it as mission assurance. Decades of backend, infrastructure and security work across power, payments, gaming and healthcare add up, in aerospace terms, to high-reliability software architecture, fault-tolerant and onboard-autonomy design, and real-time systems. The robust pipelines and fault-tolerant services of industry come from the same discipline that keeps a flight computer running in orbit.

    What I care about most is where the hardware and software actually meet: how an ML model or LLM behaves under real power, thermal and timing budgets instead of in a notebook. My embedded background means I think about inference running on a flight computer under FreeRTOS, power draw measured through an INA219, reverse engineering, industrial communication protocols and real hardware integration. I’m also a licensed radio amateur (PU7OLV), and RF is still one of the things that keeps pulling me back.

    I write mostly in Python, C, C++, Go, Erlang, Clojure, Ruby and assembly(z80, x86, arm64), depending on what the problem needs. I like working close to the hardware, but I also enjoy building the data pipelines, tools and models that make raw signals useful.

    I love coffee, it’s my addiction. I’ve been traveling around the world working from coffeeshops.

    I have 3 crazy dogs that were rescued and they are always close by.

    I love classical computers and tech from the 1980’s and 1990’s, especially the Z80 and m68k based ones, to enhance and modernize. I’ve been writing games and general software for Sega Genesis, MSX, C64 and NES. It’s a wonderful experience.