Summer School and Workshop on Optimization and Operator Learning

As event of SaC³ we organize a summer school and conference at the Universidad Nacional de Trujillo in Trujillo, Peru. School and workshop will take place from February 24 to 27, 2026. The summer school will be preceded by a pre-school on February 20 and 23, in which basic concepts will be taught and which will serve to deepen the knowledge of programming with Python.

Date and location

Universidad Nacional de Trujillo, Trujillo, Peru
February, 2026

Venue

The school will be held in at the Universidad National de Trujillo in the Math Faculty building:

The reception on Monday afternoon will be held in at the Paraninfo Universidad Nacional de Trujillo at the Plaza de Armas:

Contents

The main topics of the school include mathematical optimization and the theory of learning operators using methods of machine learning. A group of lecturers, all experts in these fields, will give introductions.

In the afternoon sessions we will go into detail and learn how to apply the methods in simple Python projects. These Python courses are aimed at students with some prior knowledge of Python.

During the last days of the week we will go over to a workshop character. Experts will present their research in the field of mathematical epidemiology. A call for papers for your contributions of posters and talks will be announced.

Material

• Website of the Python course: https://notaspedrok.com.br/mini_python_es/index.html
• Shared directory in the Cloud with lecture material and Python exercises: https://cloud.ovgu.de/s/5cAEdG9FA98inot
• How to Access the Material

Survey

As part of the constant evaluation of the SAC³ project we kindly ask you to give us your feedback by participating in this anonymous survey.

Pre-School

We will organize a short pre-school with an introduction to numerical linear algebra and scientific computing using Python. During the pre-school, we will cover two topics that will be of interest during the summer school: the gradient descent method for non-linear optimisation and linear regression. Theoretical sessions will be held in the morning, but the focus will be on practical work in the form of exercises and programming experiments in Python. As we will be a small group, you will be able to work on your own projects under our supervision. Based on your programming experience, we will divide the group and also offer Python classes. We expect you to continue working on your projects over the weekend, ready for presentations on Monday.

Fee

The local organisers may charge a moderate fee to cover expenses. If so, the fee will be published here by 16 January at the latest.

Contact

Thomas Richer at Otto von Guericke University Magdeburg thomas.richter@ovgu.de.

Organizers

Local organizers from Universidad Nacional de Trujillo

• Obidio Rubio Mercedes
• Julio César Peralta Castañeda

Responsible organizers of SaC3

• Stefan Frei, Konstanz University
• Dayron Dominguez, University of Magdeburg
• Thomas Richter, University of Magdeburg

Responsible Lecturers for the Summer School

• Peter Benner, Max Planck Institut for Dynamics of Complex Technical Systems Magdeburg
• Malte Braack, Kiel University
• Thomas Richter, University of Magdeburg

Responsible Lecturers for the Preschool

• Pedro Konzen, Universidade Federal do Rio Grande do Sul, Porto Alegre
• Thomas Richter, Otto von Guericke University Magdeburg

Docents for Summer School and Preschool

• Yevgeniya Filanova, Max Planck Institut for Dynamics of Complex Technical Systems Magdeburg
• Leonidas Gkimisis, Max Planck Institut for Dynamics of Complex Technical Systems Magdeburg
• Konrad Janik, Max Planck Institut for Dynamics of Complex Technical Systems Magdeburg
• Martyna Minakowska, Otto von Guericke University Magdeburg
• Hannah Scherer, Kiel University

Local Committee (scientific)

• Dr. Obidio Rio Mercedes
• MSc. Julio César peralta Castañeda
• Dr. Edmundo Vergara Moreno
• Dr. Nelson Aragonés Salazar
• Dr. Franco Rubio López

Local Committee (rreception and tourism)

Comité de Recepción y Turismo
• Prof. Jenny Rojas Jerónimo
• Prof. Alexis Rodríguez Carranza
• Prof. Rocío Rojas Jara
• Tesista Bianca Solorzano Carrillo
• Alumna María Laura Noriega de la Cruz

Local Committee (registration and certification)

• Prof. Ronald León Navarro
• Prof. Orlando Hernández Bracamonte

Local Committee (logistics)

• Prof. Juan Ponte Bejarano
• Prof. Luis Lara Romero
• Prof. José Luis Ponte Bejarano
• Alumno Jomar Rivas Cabanillas
• Alumno David Alexander Alfaro Benaute

Schedule of the Pre-School

Friday, Feburary 20

09:00 – 09:30: Registration
09:30 – 10:00: Opening
10:00 – 12:00: Theoretical: Linear Regression
12:00 – 14:00: Lunch Break
14:00 – 16:00 Python Course / Python exercises
Monday, February 23
09:00 – 10:30: Theoretical: Nonlinear Optimization
10:30 – 11:00: Coffee Break
11:00 – 12:30: Python Course / Python Exercises
12:30 – 14:30: Lunch Break
14:30 – 16:00: Python Course / Python Exercises
18:00 – 21:00: Reception and Registration for Summer School. Taking place at the Paraninfo Universidad Nacional de Trujillo at the Plaza de Armas

Schedule of the Summer-School and Workshop

Tuesday, February 24
08:00 – 09:00: Registration
09:00 – 09:30: Opening
09:30 – 11:00: Course I - Optimization
11:00 – 11:30: Coffee Break
11:30 – 13:00: Course II - Operator Learning
13:00 – 14:30: Lunch Break
14:30 – 15:30: Course III - Neural Networks
15:30 – 16:00: Coffee Break
16:00 – 17:30: Exercise
Wednesday, February 25
09:00 – 10:00: Course II - Operator Learning
10:00 – 11:00: Course III - Neural Networks
11:00 – 11:30: Coffee Break
11:30 – 12:30: Exercise
13:00 – 18:30: Excursion
19:00 – 22:00: Dinner at the El Mochica de Doña Fresia
Thursday, February 26
09:00 – 10:30: Course II - Operator Learning
10:30 – 11:00: Coffee Break
11:00 – 12:30: Course I - Optimization
12:30 – 14:00: Lunch Break
14:00 – 15:30: Exercise
15:30 – 16:00: Coffee Break
16:00 – 17:30: Exercise
Friday, February 27 - Workshop
Session 1: Neural Networks
08:30 – 08:50: Offline swimming learning strategies for simple articulated swimmers (Stevens Paz, Cali, Colombia)
08:50 – 9:10 Absorption Estimation in Radiative Transfer: PINN-SP1 method for Discrete Detectors with Noise (Renato Aloisio dos Santos Klein, Porto Alegre, Brazil)
09:10 – 9:30 Simulation of Chemical Reactor Dynamics using Physics-Informed Neural Networks (Leighton Leandro Estrada Rayme, Rio de Janeiro, Brazil)
09:30 – 9:50 Teaching Quantum Chemistry to Deep Learning Model: Transformer for the Many Bodies Schrödinge Equation (Jorge Alvaro Muñoz Laredo, UNI Lima, Peru)
09:50 – 10:10 Graph Neural Networks for weather forecasting (Bruno Scaratti, Porto Alegre, Brazil)
10:10 – 10:30 Stochastic rumor propagation: Modeling and simulation in complex networks (Daniel AlexisGutierrez-Pachas, Arequipa, Peru)
10:30 – 11:00 Coffee Break
Session 2: Flow problems and Stochastic Equations
11:00 – 11:20 Variational formulation of the 3D groundwater flow problem of the Moche aquifer (ROCÍO DEL PILAR ROJAS JARA, Trujillo, Peru)
11:20 – 11:40 Existence of weak solutions for a 2D model of the Moche aquifer (Alexis Rodriguez, Trujillo, Peru)
11;40 – 12:00 A Finite Volume Application of ANN-Flux to Scalar Conservation Laws (MarceloMello, Porto Alegre, Brazil)
12:00 – 12:20 Influence of Channel Bed Morphology on Hydrodynamic Soliton Propagation and Its Implications for Flood Risk Management (Ronal De La Cruz, Trujillo, Peru)
12:20 – 12:40 Stochastic Calculus and Financial Models: Theory and Simulation with Python (Dennis Quispe Sanchez and Obidio Rubio Mercedes, Trujillo, Peru)
12:40 – 14:00: Lunch Break
14:00 – 15:00 Poster Session and Coffee
Session 3: Optimal Control & Mathematical Biology
15:00 – 15:20 Optimization of Supermodular and Quasi-supermodular Functions over the Finite Boolean Lattice (Nelson Aragones Salazar, Trujillo, Peru)
15:20 – 15:40 QUALITATIVE ANALYSIS AND PARAMETER ESTIMATION IN DYNAMIC SYSTEMS DERIVED FROM THE SIR MODEL- A PERSPECTIVE FROM CASE STUDIES (Pedro Isaac Pesantes Grados, Lima (San Marcos), Peru)
15:40 – 16:00 Biological and Chemical Control of Mosquito Population by Optimal Control Approach (Juddy Heliana Arias Castro, Cali, Colombia)
16:00 – 16:20 MATHEMATICAL MODEL OF THE SPATIAL AND TEMPORAL DYNAMICS OF DENGUE INCORPORATING MOSQUITOES WITH WOLBACHIA (Tatiana Giron Carabali, Cali, Colombia)
16:20 – 16:40 Strategies for Controlling Diaphorina citri Using Mathematical Models and Integrated Pest Management (Carmen Alicia Ramirez Bernate, Cali, Colombia)
16:40 – 17:00 Mathematical Analysis of an Eco-epidemiological Model with Nonlinear Feedback and Prey Refuge Strategies (Neisser Pino Romero, Lima (San Marcos), Peru)
17:00 – 17:20 Application of optimization techniques in real life (Gunvant Birajdar, India)
17:20 – 18:00: Closing

Python classes

The Python exercises will be carried on using its powerful ecosystem of scientific computing libraries, including:

• NumPy: For numerical computations and array operations.
• SciPy: For scientific computations, including ODE solvers.
• PyTorch: For machine learning.

Using JupyterLab for Programming

Throughout this course, we will use JupyterLab as a programming tool. JupyterLab provides an interactive environment for writing and running Python code. We highly recommend installing it in your Python environment. Please, follow the installation instructions of the official JupyterLab website.