Demo Data from EDBT 2026 / reviewers in the wild / expert
Lisa Soder
dblp:361/7129
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
0009-0001-6972-4491ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% | |
| Artificial intelligence
1 paper |
Trustworthy machine learning · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational social science and digital humanities
AI governance |
0.8 | 1 | 2024 | Position: Technical Research and Talent is Needed for Effective AI Governance · ICML 2024 |
Machine learning › Trustworthy machine learning › AI governance
AI regulation |
0.2 | 1 | 2024 | Position: Technical Research and Talent is Needed for Effective AI Governance · ICML 2024 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | More than Marketing? On the Information Value of AI Benchmarks for Practitioners
Amelia F. Hardy, Anka Reuel, Kiana Jafari Meimandi, Lisa Soder, Allie Griffith, Dylan M. Asmar, Oluwasanmi Koyejo, Michael S. Bernstein, Mykel J. Kochenderfer |
IUI | 4 |
| 2024 | Position: Technical Research and Talent is Needed for Effective AI GovernanceabstractIn light of recent advancements in AI capabilities and the increasingly widespread integration of AI systems into society, governments worldwide are actively seeking to mitigate the potential harms and risks associated with these technologies through regulation and other governance tools. However, there exist significant gaps between governance aspirations and the current state of the technical tooling necessary for their realisation. In this position paper, we survey policy documents published by public-sector institutions in the EU, US, and China to highlight specific areas of disconnect between the technical requirements necessary for enacting proposed policy actions, and the current technical state of the art. Our analysis motivates a call for tighter integration of the AI/ML research community within AI governance in order to i) catalyse technical research aimed at bridging the gap between current and supposed technical underpinnings of regulatory action, as well as ii) increase the level of technical expertise within governing institutions so as to inform and guide effective governance of AI. Anka Reuel, Lisa Soder, Ben Bucknall, Trond Arne Undheim |
ICML | 2 |