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Johan de Aguas

Postdoctoral Fellow - Statistics and Data Science
Image of Johan de Aguas
Email johanmd@math.uio.no
Room 803
Username
Visiting address Moltke Moes vei 35 Niels Henrik Abels hus 0851 Oslo
Postal address Postboks 1053 Blindern 0316 Oslo

 

About me

I am a postdoctoral research fellow at Integreat - the Norwegian Centre for Knowledge-driven Machine Learning. I am also an international Fulbright scholar.

Research and academic profile

My research focuses on:

  • Efficient estimation of effects from modified stochastic interventions,
  • Graphical models for causal inference under selection and mechanism shift,
  • Partial identification of causal and counterfactual queries,
  • Econometric analysis of regional and network drivers of development.
Tags: causal inference, graphical models, semiparametric theory, machine learning, econometrics

Publications

  • Pérez, Johan Manuel de Aguas & Jullum, Martin (2026). Scope-Restricted Backtracking Counterfactuals. Proceedings of Machine Learning Research (PMLR). 343. doi: https:/openreview.net/forum?id=BEb4fBP6LI. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas (2026). Collaborative Representations for Targeted Causal Inference Under Outcome Selection. In Ceci, Michelangelo; Kocev, Dragi; Monreale, Anna; Vens, Celine; Flach, Peter; Manco, Giuseppe; Spiliopoulou, Myra & Masciari, Elio (Ed.), Machine Learning and Knowledge Discovery in Databases. Research Track. Springer Nature Switzerland. ISSN 9783032376541. p. 623–640. doi: 10.1007/978-3-032-37654-1_36. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas (2026). Interpolated Stochastic Interventions Based on Propensity Scores, Target Policies and Treatment-Specific Costs. Proceedings of the AAAI Conference on Artificial Intelligence. ISSN 2159-5399. 40(43), p. 36654–36662. doi: 10.1609/aaai.v40i43.40989. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Henckel, Leonard; Pensar, Johan & Biele, Guido (2025). Causal Inference amid Missingness-Specific Independencies and Mechanism Shifts. Proceedings of Machine Learning Research (PMLR). 286, p. 31–42. doi: https:/proceedings.mlr.press/v286/aguas25a.html. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Henckel, Leonard; Pensar, Johan & Biele, Guido (2025). Causal Inference amid Missingness-Specific Independences and Mechanism Shifts. Proceedings of Machine Learning Research (PMLR). 286, p. 31–44. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Krumscheid, Sebastian; Pensar, Johan & Biele, Guido (2025). The Probability of Tiered Benefit: Partial Identification with Robust and Stable Inference. Proceedings of Machine Learning Research (PMLR). 275, p. 90–113. doi: https:/proceedings.mlr.press/v275/aguas25a.html. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan; Pérez, Tomás Fernando Varnet & Biele, Guido (2025). Recovery and inference of causal effects with sequential adjustment for confounding and attrition. Journal of Causal Inference. ISSN 2193-3677. 13(1). doi: 10.1515/jci-2024-0009. Full text in Research Archive
  • Biele, Guido; Pérez, Johan Manuel de Aguas & Pérez, Tomás Fernando Varnet (2023). What can we conclude about the effect of parental income on offspring mental health? International Journal of Epidemiology. ISSN 0300-5771. 52(2), p. 641–643. doi: 10.1093/ije/dyac144. Full text in Research Archive

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  • Abdulkadir, Mohammed A.; Alay, Özgü; Dreibholz, Thomas; Elmokashfi, Ahmed; Li, Xi & Lopez, Diego [Show all 13 contributors for this article] (2021). AI and ML – Enablers for Beyond 5G Networks. 5G PPP Technology Board. doi: 10.5281/zenodo.429989. Full text in Research Archive

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  • Melteig, Elina; Glad, Ingrid Kristine; Ramezani-Kebrya, Ali; Pérez, Johan Manuel de Aguas; Holmsen, Sigurd & Palomares, Alfonso Diz-Lois [Show all 7 contributors for this article] (2026). Blir KI vår dommedag? Ekspertene strides. [Journal]. Titan. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan; Pérez, Tomás Fernando Varnet & Biele, Guido (2024). Recovering target causal effects from post-exposure selection induced by missing outcome data. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan & Biele, Guido (2024). Partial identification and efficient estimation for the stratum-specific probability of benefit with thresholds on a continuous outcome. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan; Pérez, Tomás Fernando Varnet & Biele, Guido (2024). Recovering target causal effects from post-exposure selection induced by missing outcome data. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan & Biele, Guido (2023). Recovering causal effects from confounding and selection biases: Extended graphical criteria via mediation analysis. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan & Biele, Guido (2023). Recovering causal effects from confounding and selection biases: Extended graphical criteria via mediation analysis. Full text in Research Archive
  • Pérez, Johan Manuel de Aguas; Pensar, Johan & Biele, Guido (2023). Counterfactual inference with nonparametric Bayes: Causal attribution of ADHD treatment on level achievement at the national test. Full text in Research Archive

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Published Oct. 10, 2025 11:48 AM - Last modified Nov. 4, 2025 12:09 PM

Projects

Research groups

Github Page: https://johandh2o.github.io

LinkedIn: linkedin.com/in/johandh2o/