Demo Data from SIGIR 2026 / reviewers in the wild / expert
Isaiah Andrews
dblp:357/4405
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0003-2492-2288ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 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.
| Theoretical computer science
1 paper |
Algorithmic game theory and mechanism design · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational finance and economics · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational finance and economics › economics
economic forecasting |
0.3 | 1 | 2025 | The Transfer Performance of Economic Models · EC 2025 |
Methods — techniques the papers use, named apart from their topics
machine learning · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | The Transfer Performance of Economic ModelsabstractEconomists routinely make predictions in environments where data is unavailable, relying on evidence from related but distinct contexts. For example, an economist at a development agency may need to predict diffusion of microfinance takeup in one Indian village given data on diffusion in others. Or an economist at an insurance company may need to predict willingness-to-pay for certain insurance plans given data on willingness-to-pay for others. Isaiah Andrews, Drew Fudenberg, Lihua Lei, Annie Liang |
EC | 1 |