Demo Data from EDBT 2026 / reviewers in the wild / expert
Luis Rayo
dblp:297/4344
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0000-0003-4429-7398ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 since 2021Theory of computation · 2 · 2 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
2 papers |
Algorithmic game theory and mechanism design · 86% Mathematical optimization · 14% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › mechanism design › information elicitation
feedback design |
0.8 | 1 | 2024 | Feedback Design in Dynamic Moral Hazard · EC 2024 |
Algorithmic game theory and mechanism design › mechanism design › contract theory
principal-agent problem |
0.8 | 1 | 2024 | Feedback Design in Dynamic Moral Hazard · EC 2024 |
Algorithmic game theory and mechanism design › mechanism design
contest design |
0.5 | 1 | 2021 | Optimal Feedback in Contests · EC 2021 |
Algorithmic game theory and mechanism design › non-cooperative game › dynamic games
dynamic contest |
0.5 | 1 | 2021 | Optimal Feedback in Contests · EC 2021 |
Mathematical optimization › sequential decision making
feedback policy |
0.5 | 1 | 2021 | Optimal Feedback in Contests · EC 2021 |
Algorithmic game theory and mechanism design › resource allocation
prize allocation |
0.5 | 1 | 2021 | Optimal Feedback in Contests · EC 2021 |
Methods — techniques the papers use, named apart from their topics
dynamic mechanism design · 0.8contract theory · 0.8mechanism design · 0.5dynamic optimization · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Feedback Design in Dynamic Moral HazardabstractThe early stages of many careers serve as a trial period where employees seek a high-value reward (e.g., a promotion) while working hard to demonstrate their productivity. A key design component of such jobs is the performance feedback offered to the employee, as it allows them to adjust their behaviors and learn what their future rewards might look like. While some experts argue that a policy of full transparency is best---that is, keeping employees fully apprised of their performance---such practice is far form uniform as employers may see a strategic gain from hiding information or postponing its release. Jeffrey Ely, George Georgiadis, Luis Rayo |
EC | 3 |
| 2021 | Optimal Feedback in ContestsabstractWe derive an optimal dynamic contest for environments where effort can be monitored only through a coarse, binary performance measure and the principal chooses prize-allocation and termination rules together with a real-time feedback policy for the contestants. The optimal contest takes a stark cyclical form: contestants are kept fully apprised of their own successes, and at the end of each fixed-length cycle, if at least one agent has succeeded, the contest ends and the prize is shared equally among all successful agents irrespective of when they succeeded; otherwise, the designer informs all contestants that nobody has yet succeeded and the contest resets. Applications include promotions, innovation contests, and proof-of-work protocols. Jeffrey Ely, George Georgiadis, Sina Moghadas Khorasani, Luis Rayo |
EC | 4 |