ESP
Who am I?

Geometry determines arithmetic.

— M. Hyndry and J. Silverman

Precise knowledge of the behavior of an analytic function in the neighborhood of its singular points is a source of number-theoretic theorems.

— E. Hecke

I am Edgar Delgado Vega, a musician born in Lima who develops software at the intersection of mathematics, computation, and music.

My vision is to create abstractions through structural analogies that naturally lead to mathematical discovery from the musical perspective and vice versa. To this end, I design code libraries that enable tackling complex problems in creative ways.

Picture of modular forms library on Sonic Pi
modular_forms (Sonic Pi)

As someone who enjoys questioning things, I prefer to reconstruct algorithms and music theory with sufficient mathematical rigor to unveil underlying patterns, which also involves thinking about asymmetries and non-commutativity. I find that this systematic approach is a genuine pathway to new concepts.

Figurate Number in Polar Coordinates
5D Hyperoctahedron

Teaching Experience

I have teaching experience at both undergraduate and postgraduate levels, particularly in live coding and musicology with a technological focus. You can read feedback on my teaching practice here.

Interests

  • Mathematical Music Theory
  • Domain-specific languages (DSLs) for music
  • Computer-assisted music composition and improvisation

I've tried to learn the hidden beauty in various things, but still for many areas the source of interest is for me a complete mystery. My theory is that too often people project their human weaknesses/properties onto their mathematical activity. There are obvious examples on the surface: for example, the idea of a classification of some objects is an incarnation of collector instincts, the search for maximal values is another form of greed, computability/decidability comes from the desire of a total control.
Fascination with iterations is similar to the hypnotism of rhythmic music.

— Maxim Kontsevich
Technologies

  • TypeScript, Node.js, Express, SQL, Git

  • Some knowledge of Ruby and Python

  • LaTex, GeoGebra, Zotero, BibTex

  • Sonic Pi, MuseScore, Reaper

GitHub Stats
Education

UNIR | Master's Degree in Music Research

2019 - 2020 | Spain
See more

I received the highest distinction with a perfect score in Computational Music Analysis. Overall average: Outstanding • TFM: I applied the theory of simplicial complexes (MaMuTh) to analyze a musical style using specialized software. 💻 HexaChord, Geogebra, LaTex

USMP | B.A. in Music

2009 - 2015 | Lima, Perú
© 2026 Edgar Delgado Vega