Engineer, founder, and researcher focused on deploying AI into the real world. I work across healthcare, multimodal systems, inference infrastructure, and world models, building the tooling and data layers behind the next generation of intelligent systems.
Bytespace Labs turns healthcare institutions into AI-native learning systems.
We capture the knowledge inside clinics, hospitals, labs, diagnostic centers, and care environments, then turn everyday clinical work into data hubs for better care, applied AI research, and future medical intelligence.
bytespace labs
UPenn M&T
BioengineeringWharton / FinanceAI/MLSelf-directed research| Project | Type | Status |
|---|---|---|
| Project 1 | Company / research | In progress |
| Project 2 | AI systems | Archive |
| Project 3 | Healthcare / data | Archive |
I care about the edge of research because it creates chances to solve hard problems in science. Building companies has become one of the most direct ways I have found to put myself near those problems: close enough to the technology, the users, the data, and the constraints to actually move something forward.
I love strategy. The technology is exciting, but I have learned that it is often the simpler part. The harder and more interesting work is getting into position to build it: aligning incentives, finding the right collaborators, protecting morale, allocating resources, and keeping a team pointed at a future that does not exist yet.
A lot of my best work still happens quietly late at night, when the world is slower and I can sit with research from 11pm into the early morning.
I grew up between science and art. My father gave me a way to connect with medicine, systems, and scientific thinking. My mother showed me, without ever making it a lesson, how intense inner states could be channeled into art. Watching her turn bipolar episodes into work with real force and beauty left a mark on me. I think it quietly taught me to turn pressure into making. My sister brought warmth, humor, and a kind of aliveness I deeply admire. I still play piano every day.
Computers became my own version of that outlet. I grew up in Guatemala around violence, instability, and loss, and later had an accident at 13 that left me paraplegic for a period of recovery. My father gave me a computer, and I disappeared into Coursera courses, programming, machine learning, and bioengineering.
Before I had the language for it, I was trying to understand the brain because I was trying to understand my mother. In my early teens I read about neuroscience, optogenetics, and neural signals, and became obsessed with the idea that mood and illness might be understood through encoding and decoding patterns in the brain. I failed at solving anything that large, of course, but the attempt changed me.
Healthcare made the work feel personal. During recovery I was moving through labs, doctors, scans, and diagnoses, while also carrying early memories of losing a childhood friend to H1N1. I became obsessed with neural networks: their compression, their strange resemblance to the brain, and their ability to extract structure from messy signals. Medical imaging was the first place that obsession felt concrete. I wanted software to help people understand disease earlier and better. That was the beginning of my path into computers, AI, ML, and science.
I want to meet researchers, engineers, clinicians, founders, and unusually driven people who care about hard scientific or technical problems. If any of this resonates, write me.