VLDB 2026 Research / reviewers in the wild / expert
Kornrapat Pongmala
dblp:329/5996
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 2 · 2 since 2021Software engineering, systems software and programming languages · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | What Drives the (In)stability of a Stablecoin?abstractIn May 2022, an apparent speculative attack, followed by market panic, led to the precipitous downfall of UST, one of the most popular stablecoins at that time. However, UST is not the only stablecoin to have been depegged in the past. Designing resilient and long-term stable coins, therefore, appears to present a hard challenge. To further scrutinize existing stablecoin designs and ultimately lead to more robust systems, we need to understand where volatility emerges. Our work provides a game-theoretical model aiming to help identify why stablecoins suffer from a depeg. This game-theoretical model reveals that stablecoins have different price equilibria depending on the coin’s architecture and mechanism to minimize volatility. Moreover, our theory is supported by extensive empirical data, spanning 1 year. To that end, we collect daily prices for 22 stablecoins and on-chain data from five blockchains including the Ethereum and the Terra blockchain. Yujin Potter, Kornrapat Pongmala, Kaihua Qin, Ariah Klages-Mundt, Philipp Jovanovic, Christine A. Parlour, Arthur Gervais, Dawn Song |
ICBC | 2 |
| 2024 | Unpacking How Decentralized Autonomous Organizations (DAOs) Work in PracticeabstractDecentralized Autonomous Organizations (DAOs) have emerged as a novel way to coordinate a group of (pseudonymous) entities toward a shared vision (e.g., promoting sustainability). In just a few years, over 4,000 DAOs have been launched in various domains, such as investment, education, health, and research. Despite such rapid growth and diversity, it is unclear how these DAOs actually work in practice. Given this, we aim to unpack how (well) DAOs work in practice. We conducted an in-depth analysis of a diverse set of 10 DAOs of various categories and smart contracts, leveraging on-chain data and interviewing DAO members. Specifically, we define metrics to characterize key aspects of DAOs, such as the degrees of decentralization and autonomy. We observed some DAOs having poor decentralization in voting, while decentralization has improved over time for one-person-one-vote DAOs. Lastly, we offer a set of design implications for future DAOs based on our findings. Tanusree Sharma, Yujin Potter, Kornrapat Pongmala, Henry Wang, Andrew Miller 0001, Dawn Song, Yang Wang 0005 |
ICBC | 3 |
| 2023 | Part-Based Models Improve Adversarial Robustness
Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen 0001, Nicholas Carlini, David A. Wagner 0001 |
ICLR | 2 |