Summer School 2026 - UB School of Economics

Overview of previous editions of the UB School of Economics Summer School: 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2021 | 2022 | 2023 | 2024 | 2025

Seeing Through the Algorithms: A Summer School on Machine Learning & AI for Economists

6 – 10 July, 2026

Applications are open now!

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Nowadays, Machine Learning (ML) and Artificial Intelligence (AI) are reshaping economic research, policy evaluation, and business decision-making. Yet many economists use these tools as “black boxes,” often unaware of their assumptions, limitations, and potential pitfalls.

This Summer School, hosted by the UB School of Economics in 2026, offers an accessible yet rigorous introduction to ML and AI specifically designed for economists.

Over five intensive days, participants will explore the foundations of machine learning, the logic behind modern AI models, and the ways in which these techniques can both illuminate and distort empirical insights when misapplied. Through hands-on sessions, real-world economic datasets, and critical discussions, the course equips participants with a clear understanding of what algorithms actually do, without requiring them to engage in programming. Attendees will learn how to use ML responsibly and how to identify and avoid incorrect applications in academic papers, policy reports, and industry contexts.

By the end of the course, participants will be able to evaluate ML and AI methods from an economist’s perspective, with particular emphasis on identification, causality, interpretability, fairness, and robustness. No prior experience with ML is required, only curiosity and a willingness to engage critically with new analytical tools.

Academic Director: Montserrat Guillen (Universitat de Barcelona, National Research Award 2025) | Academic Coordinator: Juan S. Yañez (Universitat de Barcelona)

Lecturers

Montserrat Guillen, UB School of Economics

Montserrat Guillén Estany is Chair Professor at the University of Barcelona and former honorary visiting professor at City, University of London. She holds degrees in Mathematics, Economics, and Data Analysis, with visiting research positions at the University of Cambridge, the University of Essex, Paris Panthéon-Assas, the University of Texas at Austin, and UC Berkeley.

She leads a consolidated research group on Risk in Finance and Insurance and is one of the world’s top researchers in actuarial science and quantitative risk analysis. She is the highest-ranked woman among highly cited Spanish economists, has held key roles in major statistical and actuarial institutions, and has received the ICREA Academia distinction twice.  She is Editor-in-Chief of the North American Actuarial Journal and was awarded the 2025 National Science Prize in Law Economics and Social Sciences by the Spanish Ministry of Science.

Lluís Bermúdez Morata holds a PhD in Economics and Business Administration and a Bachelor’s degree in Actuarial and Financial Sciences from the University of Barcelona, as well as a Bachelor’s degree in Statistics from the Polytechnic University of Catalonia. He is currently a Full Professor in the Department of Economic, Financial, and Actuarial Mathematics at the University of Barcelona and a member of the research group “Risk in Finance and Insurance” (Riskcenter-IREA). He is the Director of the UB Postgraduate Programme “Data Science for Social and Business Analytics.”

Juan Sebastian Yañez holds a Ph.D. in Mathematics from Université du Québec à Montréal (UQAM) and is a lecturer at the Faculty of Econometrics, Universitat de Barcelona. He previously worked as a postdoctoral fellow and external researcher at UB’s Riskcenter, focusing on accident modeling in automobile insurance. He also taught finance, statistics, and actuarial science at UQAM (2017-2023).

He has been an active member of the Chaire Co-operators en Analyse des Risques Actuariels (C.A.R.A.), and has published in leading journals including ASTIN Bulletin: The Journal of the IAA and Insurance: Mathematics and Economics. He received a Postdoctoral Fellowship from the Fonds de Recherche du Québec (2024-2026).

Anja Schulze is an economist with an MSc in Economics from the University of Barcelona and extensive experience at the intersection of management, product, finance, and data-driven business analytics. She works with enterprises through complex transformations, focusing on business resilience by enabling data-based decisions that combine product management, customer-centric development, and financial steering in volatile environments.

She helped build and scale two Volkswagen Group subsidiaries, MOIA and CARIAD, contributing to the mobility ecosystem and automotive software stack. Today, she works as an independent advisor, helping companies strengthen resilience and clarity during transformation. Her talks blend economic thinking with practical execution experience.

Jordi Vidal is an experienced data science and analytics leader with a strong background in statistical modeling and machine learning. He currently serves as Data Analytics Director & Chief Data Officer (CDO) at VidaCaixa, a position he has held since 2024. Prior to this, he led the company’s advanced analytics and modelling teams, driving the development and deployment of data-driven solutions across the organization.

His experience includes leading multi-team machine learning projects, developing advanced predictive models in big data environments, and applying text mining and sentiment analysis techniques. He also has a strong track record of mentoring practicum students and supporting applied research through thesis supervision.

Course outline

• Day 1: Foundations and Intuition

• Day 2: From Linear Regression to Neural Networks

• Day 3: From Regression Trees to Ensemble Models

• Day 4: Interpretability

• Day 5: Good Practices and Misuses

A more detailed outline is available here.

The course includes:

• Theory and hands-on taught by 3-4 expert instructors

• Real-world applications using economic data

• Coverage of prediction, causal ML, interpretability, and modern AI models

• Discussion of ethical, methodological and policy issues

• A final capstone project with feedback from faculty

Schedule

Day 1 to 5 | 9:00 – 14:00

• 9:00-10:30: Lecture (Part I)

• 10:30–11:00: Coffee break

• 11:00–12:15: Lecture (Part II)

• 12:15–12:30: Short break

• 12:30–14:00: Workshops / External speaker talks

Applications

Applications are open now!

APPLICATION FORM

The summer school is designed for advanced graduate students and professionals with a strong interest in machine learning & AI for Economists.

It aims to attract:

• Graduate students from disciplines such as economics, political science, and other social sciences with a quantitative focus.

• Early-career researchers.

• Applied Economist.

This programme is ideal for graduate students, early-career researchers, and applied economists looking for being able to evaluate ML & AI methods with an economist’s eye for identification, causality, interpretability, fairness, and robustness. Final-year bachelor’s students may also be eligible.

Participants requirements:

• Curiosity and a willigness to engage critically with new tools.

• Proficiency in English, as all lectures, materials, and discussions will be conducted in English.

• No prior experience with machine learning is required.

Important dates:

• Application deadline for the Summer School: April 20th, 2026, or until all slots are filled.

• Application deadline, including student scholarship application: March 20th, 2026.

Note: If you are interested in scholarships, please see the Scholarships section for details.

Additional information:

• Applicants will receive the admission resolution by email within 3 weeks of their application.

• To secure a space in the programme, admitted participants will need to formalize the payment by the indicated deadline in the admission resolution email.

Tuition Fees

General fee: 710€*

Student fee: 475€

*25% discount on the general fee for early career researchers (within five years of the award of their PhD).

Fees: The fees cover coffee, a welcome dinner, a farewell cocktail, and materials required for the course. They do not cover lunches, accommodation, transport, or any other services.

Payments: Participants offered a place on the Summer School will receive an email with (i) the admission letter and (ii) the payment instructions. Payment of the tuition fees is required to secure a place once offered.

Cancellation policy: All cancellations must be received in writing and sent in advance by email. Participants wishing to withdraw from the Summer School will have their tuition fees partially refunded according to the following policy: Prior to 15 days before the beginning of the course: full refund of the registration fee, less €100 of administrative costs.

The University of Barcelona reserves the right to cancel the Summer School if the minimum number of required students is not reached.

Scholarships

Master and PhD students seeking financial aid might be interested in applying for one of the five available student scholarships, which cover the full course tuition fees.

Deadline for registration, including student scholarship application, is March 20th, 2026. Applications will be reviewed by the Dean, the Vice-Dean for Research, Doctoral Studies and Social Impact, and the course coordinators. The list of awarded participants will be published by April 5th, 2026.

Scholarship applications will require:

A Cover Letter
A Transcript of Records

Applications will be evaluated based on:

Cover Letter
Academic Profile – with priority given to PhD students working on topics closely related to the course content.

Tuition fees already paid by participants awarded with a scholarship will be reimbursed as soon as possible.

Attendance Certificates

Summer School at the UB School of Economics is accredited in accordance with the European Credit Transfer System and will be recognized by the University of Barcelona as 2 ECTS credits.

ECTS – a common language for academic recognition: ECTS, the European Credit Transfer and Accumulation System, was developed by the European Commission in order to provide common procedures to guarantee academic recognition of studies abroad. It provides a way of measuring and comparing learning achievements and transferring them from one institution to another. This is achieved through the use of common ECTS credit units and a common ECTS grading scale.

Accomodation

Accomodation for a 5-night stay is available at UB Residence Montserrat-Penyafort. Admitted participants will be eligible to reserve a room on a first-come, first-served basis.

The price of a single room ranges from 64,46€/night to 85,45€/night (depending on the meal plan). Double rooms are subject to availability and must be confirmed directly with the Residence; prices range from 113,93€/night to 155,92€/night (depending on the meal plan).

The 5-night stay covers the nights from July 5 to July 9, 2026. Departure is scheduled for the morning of July 10, 2026. Extra nights are subject to availability.

Once you have been admitted and have confirmed your place by paying the course fee, you will receive the contact information required to arrange your room reservation directly with UB Residence Montserrat-Penyafort.

The residence is located within a 10-minute walk from the campus and is also well connected by public transport.

Important Information:

• Payment for accommodation is not included in the course fee and must be made directly to the residence.

• Cancellation and payment conditions will be confirmed directly by the residence, which is responsible for managing all room bookings.