APPLIED CAUSAL GRAPHS
Workshop 2024
| Date | Tuesday 23rd April 2024 |
| Times | 09:00-17:30 |
| Location | Hertie School, Berlin |
| Organizers | Silvana Tiedemann, Hertie School |
| Patrick Klösel, PIK / MCC | |
| Logistics | Trisha Kershaw |
| Support | Centre for Sustainability |
| Data Science Lab | |
| Sign up | FORM (deadline: 29th February 2024) |
Concept
We all love causal graphs! But alas, not all disciplines love causal graphs equally. That is why we want to bring together the broader community of researchers in the Berlin area who work with causal graphs.
The focus of the workshop will be on how graphs can help us in applied research in the social sciences, climate science, and beyond.
The big question is: How can we transfer methods and solutions for specific problems from one discipline to another?
Format
Short presentations (about 10 minutes), followed by 10 minutes of discussion.
We encourage everyone to present work in progress, new software or implementations, and really anything that makes it easier for applied scientists to harness the power of causal graphs in their research.
We also invite each participant to send a picture of the graph that best summarizes their current work, which will be displayed in the conference room to facilitate discussion.
Schedule
| 9:00 | Welcome |
| Silvana Tiedemann, Patrick Klösel | |
| 9:15 | Keynote 1: Will Lowe (Hertie School) |
| New Directions for Causal Graphs [slides] | |
| 10:05 | Coffee Break (on-site) |
| 10:20 | Session 1: Applications in the Social Science and Psychology |
| Moderator: Silvana Tiedemann | |
| Julia Rohrer (Uni Leipzig): Causal Graphs in Psychology | |
| Giulia Malevolti (PIK): Agroforestry and household nutrition in southern Madagascar: does gender matter? | |
| Peter Wieland and Konrad Bierl (HU Berlin): Climate Policies and Green Party Performance in Local Election [slides] | |
| Leonard Missbach (TU/MCC Berlin): Coal-fired power plants and industrial development [slides] | |
| 11:40 | Keynote 2: Urmi Ninad (TU Berlin) |
| Causal Inference for Time-Series and Applications to Climate [slides] | |
| 12:30 | Light Lunch Break (on-site, cordially provided by Hertie School) |
| 1:30 | Session 2: Applications in Times Series |
| Moderator: Patrick Klösel | |
| Felix Wagner and Florian Nachtigall (TU/MCC Berlin): Using machine learning to understand causal relationships between urban form and travel CO2 emissions across continents [slides] | |
| Silvana Tiedemann (Hertie School): Identifying elasticities in autocorrelated time series using causal graphs [slides] | |
| Timo Stiglitz (HU Berlin): Stability and narrow counterfactuals: Limits of experimentalist causal inference in economic history (Eggtimer) | |
| 2:15 | Keynote 3: Vanessa Didelez (BIPS Bremen) |
| Expert-driven versus Data-driven Causal Graph Selection in Epidemiology [slides] | |
| 3:15 | Coffee Break (on-site) |
| 3:30 | Session 3: Applications in Epidemiology and the Life Sciences |
| Moderator: Silvana Tiedemann | |
| Jess Rohmann (Charité Berlin): Rethinking animal attrition in preclinical research: expressing causal mechanisms of selection bias using directed acyclic graphs | |
| Silvia Do (BIPS Bremen): The causal effects of psychosocial well-being and emotion-driven impulsiveness on food choices among European adolescents [slides] | |
| Marco Piccininni (HPI, Potsdam): Using negative control populations to assess unmeasured confounding and direct effects | |
| Claudia Paarmann-Chien (Charité Berlin): Combining Network Analysis & Machine Learning Methods for Patient Prognosis [slides] | |
| 4:50 | How to Use DAGs in Your Own Research (Eggtimer Session) |
| Moderator: Patrick Klösel | |
| Hannah Klauber: Causal Graphs in Health Economics | |
| Klaas Miersch: Causal Graphs for Evidence Synthesis | |
| Sarah Hiller: Causal Graphs in Formal Ethics | |
| 5:20 | Wrap Up |
| 5:30 | End |