VLDB 2026 Research / reviewers in the wild / expert
Nicholas T. Wu
dblp:392/7859
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0000-0003-0876-1587ORCID · reported
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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | From Doubt to Devotion: Trials and Learning-Based PricingabstractIn the digital marketplace, a prominent feature of software products and digital services is the implementation of dynamic pricing mechanisms that are fine-tuned by consumer preference data. To fix ideas, consider a streaming service provider offering access to a library of entertainment content. Consumers are uncertain about whether the streaming library contains movies or shows tailored to their preferences but can become convinced of the service's value from finding content that resonates with their tastes. On the other hand, the pervasive collection of consumer data enables the streaming platform to predict whether the content matches a consumer and forecast the consumer's private experience. What pricing strategy the seller would take to leverage the buyer's ability to learn and data on buyer taste, and what are its welfare implications? Tan Gan, Nicholas T. Wu |
EC | 2 |
| 2023 | Managed Campaigns and Data-Augmented Auctions for Digital AdvertisingabstractDigital advertising facilitates the matching of consumers and advertisers online. Large platforms leverage their extensive consumer data to offer access to qualified online shoppers, helping them find their preferred brands. In turn, advertisers join these platforms to target a wider range of potential consumers beyond their existing customer base. Dirk Bergemann, Alessandro Bonatti, Nicholas T. Wu |
EC | 3 |