Wolfram Computation Meets Knowledge

Wolfram Summer School


Jofre Espigulé Pons

Summer School

Class of 2015


I’m a physicist through education. I did research on mathematical physics in Barcelona, and then I turned to experimental physics over the past two years at the University of Vienna (where Schrödinger’s cat is dead and alive). There I studied quantum effects in biological systems, in particular, one model for bird magnetoreception that makes use of quantum spin dynamics.

Recently, I jumped into the world of startups, and over the last three months I participated in three different hackathons. My first hackathon was the NASA Space Apps Challenge 2015 in Vienna. We won the local prize with a project called Brainterstellar, which is a Wolfram Cloud-based platform that allows people to scan thousands of satellite images efficiently. The project was selected by the NASA jury, and we reached the Global TOP15 out of 930+ projects around the world. Now we have an open dialog with NASA about the continuation of the project.

My second hackathon was the Health Hackathon 2015, this time at the Microsoft’s Vienna headquarters. I used the Wolfram Language to analyze data from the Fitbits of my friends, and we predicted sleep patterns using Classify. We also built up a wireless chest band that monitors respiration and sends emergency messages if the patient stops breathing for 15+ seconds.

Last month in Barcelona, I did my third Hackathon, called apps4citizens. We created an app that allows citizens to report incidents instantly and geolocate them using their phones. We used the Wolfram Data Drop in combination with the Wolfram Cloud and the Geographics function to create the app, AlertMapp, which automatically tweets updated maps of the city with its incidents.

Last but not least, I have a twin brother, Bernat Espigulé, who is also a member of Wolfram Community, and we share a passion for fractals and hunting fossils.

Project: BIRD.AI

BIRD.AI is an app/microsite based on the Wolfram Cloud that identifies bird species by analyzing their sounds. In order to achieve that, I’m using built-in machine learning functions like Classify and a large training set of sounds from the most common bird species in the North East of the US. Soon you will be able to identify the birds singing in your backyard just by recording them with your mobile phone or computer and get the information about the species directly from WolframAlpha.


Wolfram Summer School | Champaign, IL, USA | July 3 29–July 22, 2022