Demo Data from EDBT 2026 / reviewers in the wild / expert
Arjun Prakash
dblp:263/7830
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 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
1 paper |
Algorithmic game theory and mechanism design · 67% Mathematical optimization · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization › minimax optimization
convex-concave optimization |
0.7 | 1 | 2023 | Convex-Concave Zero-Sum Stochastic Stackelberg Games · NeurIPS 2023 |
Algorithmic game theory and mechanism design
stackelberg game |
0.7 | 1 | 2023 | Convex-Concave Zero-Sum Stochastic Stackelberg Games · NeurIPS 2023 |
Algorithmic game theory and mechanism design › stackelberg game
stochastic stackelberg games |
0.7 | 1 | 2023 | Convex-Concave Zero-Sum Stochastic Stackelberg Games · NeurIPS 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Bi-Level Reinforcement Learning for Multi-Robot Systems
Arjun Prakash |
AAMAS | 1 |
| 2023 | Convex-Concave Zero-Sum Stochastic Stackelberg Games
Denizalp Goktas, Arjun Prakash, Amy Greenwald |
NeurIPS | 2 |