My name is Jose Garcia. I design and architect complex ecosystems where technical, scientific, and organizational systems converge.
I was drawn to complex systems long before I had a name for them.
As a child, I was fascinated by inventors, eccentric scientists, and the idea that you could understand the world well enough to build new versions of it. Robots, machines, and imagined systems were never just gadgets to me; they were expressions of how parts interact, adapt, and create behavior together.
That curiosity eventually became formal training. I studied Industrial Engineering, with a strong focus on electrical engineering, electronics, and automation; a discipline that is less about individual components and more about how entire systems are designed, optimized, and controlled. It is a highly theoretical field, and deliberately so: it teaches you to think in abstractions, constraints, and interactions rather than isolated solutions.
I continued with advanced engineering studies and research-focused programs, deepening my work in modeling, system dynamics, and experimental design. That path ultimately led me to a PhD in Neuroscience, where I worked on one of the most complex systems we know: the brain. In many ways, this was a continuation of the same question I had been asking since childhood; how distributed systems integrate information, coordinate action, and remain stable under uncertainty.
Across this trajectory, my role was never limited to implementation. I designed and architected entire experimental and technical ecosystems: from sensing and signal acquisition, to data processing pipelines, to control logic and long-term data handling. These systems had to function end-to-end, with every layer influencing the next. You cannot approach that kind of work with a narrow or tool-driven mindset; it requires systems thinking, architectural discipline, and a willingness to design beyond standard patterns.
This way of thinking; holistic, integrative, and grounded in reality; is what ultimately shaped everything that followed.
My professional path began in the Department of Justice of Catalonia, where I worked on tracking and verification technologies used in correctional systems. These included voice verification, GPS and GSM-based monitoring technologies for convicted individuals. In that environment, technology is not abstract. When systems fail, consequences are real; for institutions, for people, and for society. That early experience shaped my respect for accountability, robustness, and restraint in technical design.
From there, I moved into research.
I conducted a PhD in Neuroscience at Radboud University, working at the intersection of biophysics, perception, and computational modeling. My research focused on how humans estimate and represent the motion of sound sources and on the internal models that support this process; specifically, how the brain integrates head and eye movements to determine the spatial dynamics of acoustic stimuli. Along the way, I designed and built custom experimental setups, including head–eye tracking systems and signal-processing pipelines. Research at that level teaches you something fundamental: reality is messy, models are approximations, and every assumption is eventually tested.
During my research at the University of Zurich, I conducted experiments using a vestibular chair to study one of the more challenging problems in moving sound-source localization: how to dissociate self-motion from sound-source motion. Understanding whether a sound is moving in the world or whether we ourselves are moving requires an understanding of how vestibular, auditory, and proprioceptive signals are integrated by the brain under strict experimental control, where timing, calibration, and repeatability are essential. Small inconsistencies in any component can fundamentally change the interpretation of spatial perception.
Later, at the Donders Institute for Brain, Cognition and Behaviour, I supported neuroscience research by building experimental setups and technical infrastructures that allowed scientists to focus on science instead of tooling. At the FELIX Laboratory, a free-electron laser facility supporting advanced physics research, my role shifted further into systems architecture: data pipelines, infrastructure design, and long-term data handling in highly specialized research environments.
Most recently, at Wageningen University & Research, I worked on Research Data Management solutions; designing sustainable, compliant, and scalable systems for storing, preserving, and accessing scientific data over long time horizons. This work sits at the crossroads of technology, policy, funding, and human behavior. It is where you learn how often institutions become dependent on tools they don’t fully control or understand.
Across all these roles; government, research, infrastructure; I worked in different countries, cultures, and organizational models. I saw excellent people constrained by fragile systems, opaque vendor dependencies, and decisions made far away from those who had to live with the consequences. I also learned how much value there is in clear architecture, calm engineering, and honest limitations.
Starting a consultancy was something I had wanted to do for a long time. Not because I wanted to sell technology, but because I wanted to help organizations own their infrastructure, understand their trade-offs, and build systems that align with their values, budgets, and long-term realities.
That is why I founded LibreInfra.
LibreInfra exists to bring together everything I learned across decades of hands-on work: engineering discipline, scientific rigor, institutional awareness, and respect for autonomy. It is guidance-first, open-source–oriented, and intentionally modest in scale. No hype. No lock-in. Just infrastructure that makes sense—technically, ethically, and economically.