🚀Registration is open for the #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning, Feb 2–13 2026, hybrid at @ses_unifr or online. Topics: data analytics, predictive/causal machine learning, deep learning using Python, R, Julia, Knime. 👉 Sign up: https://t.co/aGUYUoOjtr

Super recomendado el libro de @CausalHuber..sencillo de leer y con la matemática justa para entender todo.

Very happy to attend the Young Researcher Workshop of the Universities of Tübingen and #Hohenheim (as an invitee, even if I’m not that young anymore 😉) - lots of great presentations and lively discussions, including on causal machine learning! Many thanks to the organising team!

@mitpress Huge thanks to Emma Bacci, Sarina J. Oberhänsli, Jeremy Proz, Andreas Stoller, and Melissa Uhrig for their great work and support in preparing the teaching slides!

📚 In summer 2023, my book Causal Analysis was published with @mitpress. Just two years later😉 I’m very happy to share that the lecture slides are now freely available in both PDF and LaTeX (as zip files), along with the datasets and R/Python code: 👉 https://t.co/VfahR3aqVR

😀 Attending the World Congress of the Econometric Society in the stunning city of Seoul, and thrilled to present joint work with N Apfel, J Hatamyar, & J Kueck on machine learning–based testing of conditions sufficient for identifying treatment effects: https://t.co/TxOCLwZtqE

Excited to share our working paper “Machine Learning for Detecting Collusion and Capacity Withholding in Wholesale Electricity Markets”, joint with Jeremy Proz. We propose a machine learning–based approach for detecting cartels in electricity markets:

Very happy to be teaching a @gesistraining workshop on causal inference with instrumental variables and regression discontinuity designs on October 9–10, 2025. Registration is still open: https://t.co/EmOCk5wi84

🎉 Seems like the release of "Impact Evaluation in Firms and Organizations" is off to a great start! Huge thanks to everyone who's been reading, sharing, and supporting my book! https://t.co/7l3CrweNem

This moment brings back memories from 2 years ago, when my 1st book, Causal Analysis, was released. It’s a comprehensive MA/Ph.D.-level textbook on impact evaluation and causal machine learning, with use cases in R (and Python versions available online): https://t.co/qtc3KF9juJ

📘 My book Impact Evaluation in Firms and Organizations is officially out today with @mitpress! An accessible, non-technical introduction to impact evaluation (& causal machine learning) designed for practitioners & students, with use cases in R & Python: https://t.co/7l3CrweNem

Delighted that our working paper “Catching Bid-rigging Cartels with Graph Attention Neural Networks”, joint work with D. Imhof and E. Viklund, is out! We propose a novel #DeepLearning algorithm based on GATs to detect collusive behavior in markets/tenders:

And here it is! Just received my author copies of my book Impact Evaluation in Firms and Organizations, out with @mitpress on Aug 5. It offers a compact overview of methods for evaluating interventions, like marketing campaigns, with R and Python examples: https://t.co/7l3CrweNem

Delighted to attend the second edition of the Causal Machine Learning Workshop in the UK, this time hosted at Queen Mary University of London. Many thanks to my co-author Michel Haddad and the co-organizers for putting together such a fantastic event! #MachineLearning

Visiting the @ZEW (Leibniz Centre for European Economic Research) in #Mannheim this week and delighted to teach a PhD course on machine learning methods as part of their summer school! #DataScience #MachineLearning

Attending the International Association for Applied Econometrics (IAAE) conference this week in beautiful Torino. Excited to present joint work with N. Apfel, J. Hatamyar, and Jannis Kueck on testing identifying assumptions in causal inference: https://t.co/lfevkqX9PT

Just 1.5 months to go until my book Impact Evaluation in Firms and Organizations is out with @mitpress! An accessible introduction to impact evaluation & causal machine learning, with examples in #R & #Python: https://t.co/7l3Crwfl3U Examples (for free): https://t.co/k0U7OuVbAr

Great to be visiting the Chair for Entrepreneurship at @UZH_ch for a seminar on data analytics and machine learning. Many thanks to Prof. Ulrich Kaiser and his team for the warm welcome and generous hospitality! #DataScience

Visiting the Centre d'études et de recherches sur le développement international (@cerdi) in Clermont-Ferrand this week, a leading center for development economics. Many thanks for the warm welcome and the stimulating discussions on impact evaluation and causal machine learning!

🚀 Less than 3 months to go! My book "Impact Evaluation in Firms and Organizations" (@mitpress) is now available for pre-order: https://t.co/7l3CrweNem It features intuitive graphs to explain key concepts and common challenges in evaluating interventions like marketing campaigns: