EDBT 2026 Demo / reviewers in the wild / expert
Philippe J. Giabbanelli
dblp:00/10687
· DBLP profile ↗
2ranked-venue papers in the field
1as first author
2since 2021 · last 2025
0000-0001-6816-355XORCID · verified
Domains — venue-derived; a paper can count in several
Data Mining & Knowledge Discovery · 1 (1 first)Business Process & Enterprise Data · 1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Rethinking Learning: The Role of Unlearning in Generative AI-Based Conceptual Modeling
Shahnewaz Karim Sakib, Stephen W. Liddle, Christopher J. Lynch, Ameeta Agrawal, Philippe J. Giabbanelli |
ER | 5 |
| 2021 | Mapping the complexity of suicide by combining participatory modeling and network scienceabstractSuicide rates are steadily increasing among youth in the USA. Although several theories and frameworks of suicide have been developed, they do not account for some of the features that define suicide as a complex problem, such as a large number of interrelationships and cycles. In this paper, we create the first c omprehensive m ap o f a dverse c hildhood experiences (ACEs) and suicide for youth, by combining a participatory approach (involving 15 subject-matter experts) and network science. This results in a map of 946 edges and 361 concepts, in which we identify ACEs to be the most important factor (per degree centrality). The map is openly shared with the community to support further network analyses (e.g., decomposition into clusters). Similarly to the high-impact Foresight Map developed in the context of obesity, the largest map on suicide and ACEs to date presented in this paper can start a discussion at the crossroad of suicide research and network science, thus bringing new means to address a complex public health challenge. Philippe J. Giabbanelli, Michael C. Galgoczy, Duc M. Nguyen, Romain Foy, Ketra L. Rice, Nisha Nataraj, Margaret M. Brown, Christopher R. Harper |
ASONAM | 1 |