Summary 

The primary aim of ICTP PWF Honduras: Theory and Applications of Machine Learning is to strengthen foundational knowledge of machine learning and artificial intelligence among students and early-career researchers from diverse backgrounds in Honduras. Through a combination of lectures and hands-on practical sessions, participants will gain experience with modern computational and data analysis tools, develop programming and problem-solving skills, and learn about current research applications of machine learning. 
In addition, participants will have the opportunity to connect with researchers from institutions around the world through online talks. These sessions will allow them to learn firsthand how scientists use machine learning in their research and how these methods can be applied across different scientific disciplines. These interactions will foster opportunities for mentorship, collaboration, and future academic development. 


Organizers 

Organizing Committee: 

• Edith Natalia Villegas Garcia, ICTP 

• Carlos Enmanuel Soto Lopez, OGS 

Local Organizers: 

• Lucio Villanueva, UNAH 

• Melissa Cruz, UNAH 

Speakers

• Edith Natalia Villegas Garcia, ICTP 

• Carlos Enmanuel Soto Lopez, OGS 

• Ana Rivera, Massachusetts Institute of Technology 

• Alvaro Carbonero, Massachusetts Institute of Technology 

• Daniela Pinto, New York University 

• Elena Villalobos, Tecnológico de Monterrey 

• Alex Rodriguez, University of Trieste 

• Alessio Ansuini, University of Trieste 

• Joshua Lemus, University of Modena 

• Manuel Vasquez, GIMM 

• Sebastian Goldt, SISSA 

• Edgar Carrera, CERN 

 

Main Topics 

• Introduction to Machine Learning 

• Supervised Learning (regression, classification) 

• Unsupervised Learning (clustering, PCA, dimensionality reduction) 

• Neural Networks 

• Introduction to Reinforcement Learning 

• Applications 

 
Language: All the courses will be taught in Spanish, with some invited lectures in English 
Format: In person 
Registration: No registration fee 
Registration form: https://docs.google.com/forms/d/e/1FAIpQLScLMwvvdho4WaTA0CxTO8cFNtx0l7wojHmJ9I2F2FYGl-G1Sw/ 
Registration period: 1–30 Oct 2026 
Notification of selected participants: 15 Nov 2026