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Sebastian Weichwald.

📢 News · 👥 Group · 🔍 Research with us · 🏛 Contact

I aim to understand and resolve what holds causal modelling back in practice by clarifying its foundations (specifying what is being modelled, how it can be tested, which metrics reflect progress) and by prioritising ready-to-use implementations. I am fortunate to work with a relentlessly curious group and inspiring collaborators.

We argue that the common interpretation of actions as interventions renders causal model predictions circular and thus non-falsifiable (2025) and make the case for time in causal graphs (2025). These challenges relate to our earlier work on causal model transformations and abstractions (UAI 2017 & 2021), and have become increasingly urgent with growing interest in causal representation learning. Our success in the NeurIPS Causality 4 Climate competition (PMLR 2020) motivated our work uncovering how common causal discovery benchmarks may be gamed and fail to capture meaningful progress (NeurIPS 2021 & 2023). We have developed 𝚐𝚊𝚍𝚓𝚒𝚍 for evaluating learned causal graphs via adjustment identification distances (UAI 2024) and CIfly for fast algorithm development in graphical causal inference (2025).

At the University of Copenhagen, I am part of the Copenhagen Causality Lab (CoCaLa), a faculty member in the Department of Mathematical Sciences, and co-lead for causality at the Pioneer Centre for AI (P1). I also serve on the fellowship evaluation committee of the Danish Data Science Academy (DDSA). Previously, I was a postdoc in Copenhagen and a PhD student at the Max Planck Institute for Intelligent Systems and ETH Zurich.

News.

2026-Apr.
New preprint on causal effect estimation via a single proxy variable using SPICE 🌶️; at the same time, Marcel presented our flopsearch work at ICLR, and Frederik’s work on causal foundations of collective agency made it to CLeaR. It is fun to collaborate with such sharp, generous minds! 🙏
2026-Mar.
“The Case for Time in Causal DAGs” accepted at Philosophy of Science – my first paper in a philosophy journal 🏛️
2026-Jan.
Starting 2026 in a fair way: “Unfair Utilities and First Steps Towards Improving Them” accepted at the Journal of Causal Inference. Happy New Year 🎉
2025-Nov.
A new PhD adventure begins: Francesco joins us, with Leonard as co-supervisor. Expect plenty of verification, and perhaps a few surprises along the way.

↳ Olds.

Group at CoCaLa.

We are part of the Copenhagen Causality Lab, where I feel lucky to work with people who are open-minded, technically sharp, and generous with ideas. We often step back to the blackboard to question defaults, sharpen concepts, and see whether a problem needs a new formulation rather than another incremental variation. If this sounds like an environment you would like to contribute to, check out how to research with us.

Alumni: Simon Bing (2025, PhD exchange), Emanuele Marconato (2024, PhD exchange), Alexander G Reisach (2024, PhD exchange; 2020/21, MSc exchange), Theo Würtzen (2023/24, RA)

Research with us.

For official contact details, see my University of Copenhagen profile.

Before emailing, please read the relevant section below and use the subject prefix indicated there. This is a small but useful intervention: it makes it more likely that your message surfaces in the right context.

We are always happy to hear from curious people who want to think deeply about causal modelling, its foundations, and its practical limits. We receive many inquiries and may not be able to respond to all messages. Please do not read silence as a lack of interest. It usually means we are at the blackboard or immersed in research discussions with the group 📚. If your message is still relevant after a few weeks, do feel free to resend it. We won’t mind at all 📬.

Postdoc and PhD positions.

Postdoc positions are announced annually (applications due November 15) and PhD positions twice a year (applications due April 1 or November 15) through official department calls.

Applications must be submitted through the official calls. To keep the process fair and manageable, we cannot pre‑assess applications, provide feedback, or consider application materials sent by email outside these calls.

In your application, describe your own ideas and explain why they fit well with our group and, if relevant, with the specific project mentioned in the call. Even when a project is listed, you are always welcome to pitch your own research agenda. If you are unsure whether your background or interests are a perfect match, we still encourage you to apply. We value curiosity and originality, and details can be discussed during the process.

If you plan to apply for your own funding (for example, DDSA, DARA, MSCA), email me using the subject prefix “[initiative]” and include a concise sketch of your project, the relevand funding scheme, and why you believe our group offers the right environment for it.

Additional resources: PhD programme overview, salary conditions (PhDs usually start at step 4 after a 3+2 BSc+MSc education), pointers for prospective postdocs or PhD students on Jun Yang’s website.

Research visits and exchanges.

We have had great experiences hosting research visitors and PhD exchange students. If you are interested in visiting, please email me using the subject prefix “[visit]” and include a note about your background, what you would like to research with us, and what draws you to Copenhagen or the Copenhagen Causality Lab. DDSA visit grants may be a funding option for short visits.

Collaborations.

We welcome collaborations where our interests and expertise can add something useful, whether that means a joint research project, organising a workshop, or inviting us for a talk. If you have an idea that aligns with our work, feel free to reach out using the subject prefix “[collaboration]”.

MSc thesis and student projects.

If you are a student at the University of Copenhagen and would like to do a thesis or student project with me, please stop by my office or email me from your university address using the subject prefix “[UCPH]”. Include one concept, topic, or paper from a relevant course that sparked your curiosity and a question it raised. Also tell me which aspects of the work you enjoy most (for example theory, proofs, literature research, coding, data analysis, or writing) and what your ambitions are for the project.

Imprint & Credits