Mathematician in training. ML builder by conviction. Writer at heart.
I'm a 7th semester Computer Science undergraduate at Tecnológico de Monterrey. My degree is software engineering in practice — but I am a mathematician at heart, building toward that identity deliberately.
I study mathematical logic, theory of computation, and the formal foundations of artificial intelligence. Not because they appear on a syllabus — but because they reveal something real about the nature of thought itself.
The same foundations are why I build machine learning systems by hand. Logic and linear algebra aren't a separate life from ML — they're the substrate underneath the models everyone else treats as magic. When I extract MFCC features or train a classifier from scratch, I'm not switching identities. It's one discipline, seen whole.
I'm looking forward to applying to European masters programs in logic and theoretical CS. A masters is the next level in my intellectual journey.
Voice loop done: on-device ASR, local LLM, TTS. Currently training a wake-word classifier from raw MFCC features. Build log →
§2.4 — Structures and truth in first-order logic.
Formalizing ethical constraints in Standard Deontic Logic. Three theorems: consistency, completeness, lattice structure.
Linear algebra is the mathematics of today's ML. To understand it deeply is to build rigorous AI.
Exchange semester. Taking AI, ML and theoretical computer science courses.
"The math isn't a detour from the machine learning. It's the substrate underneath it — the part everyone else treats as magic."— why the theorist and the builder are the same person
Writing is a large part of who I am — essays, fiction, poetry. I think through writing. I understand through writing. Some thoughts only become clear when they're on a page.
read my writing ↗Fiction that thinks. Nonfiction that unsettles.
Wordsworth, Keats, Mary Shelley. The Romantic poets understood something about the sublime that modern thought has mostly forgotten. I return to them constantly.
Daily gym. Intentional eating. Consistent sleep. I treat my body the same way I treat a proof — with care, structure, and respect for the process. Clear head, clear thought.
I lean Platonist. Mathematical objects feel discovered, not invented. Gödel believed this too. The unreasonable effectiveness of mathematics in physics is hard to explain otherwise.
The question I keep returning to: can machines be kind? Not just capable — kind. That question is what turned me from an engineer into a mathematician. It still keeps me going.
First professional experience. SQL, Python pipelines, cohort analytics. The beginning.
The semester I stopped seeing CS as code and started seeing it as the study of thought. Turing speaks. Everything shifts.
Built BRAIN from first principles. First formal paper. First production AI system. Full autonomy, full responsibility.
Self-directed curriculum in mathematical logic, TOC, linear algebra, and quantum computing. Weekly sessions with Dr. Oliart. The cathedral under construction.
Leading development of three AI agents for insurance. Deontic logic paper in progress. Masters applications in October. At home: a voice assistant that runs entirely on my own machine.
Scouting European academic culture. Meeting researchers. Finalizing applications.
The north star. Mathematical logic, machine learning, AI. The place this entire trajectory points toward.