5 papers in the archive (2023–2026), average empirical rigor 5.6/10, average math complexity 8/10. Quadrant mix: Holy Grail ×3, Lab Rats ×2.
Works mostly in Crypto Markets & DeFi, Insurance & Actuarial Risk, Market Microstructure.
Frequent co-authors: Nagu Thogiti (1), Mauricio Jean Pieer Trujillo Ramirez (1), Victor Xu (1), Theo Diamandis (1), Max Resnick (1), Guillermo Angeris (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
Autodeleveraging (ADL) is a last-resort loss socialization mechanism used by perpetual futures venues when liquidation and insurance buffers are insufficient to restore solvency. Despite the scale of perpetual futures markets, ADL has received limited formal treatment as a sequential control problem
Autodeleveraging (ADL) is a last-resort loss socialization mechanism for perpetual futures venues. It is triggered when solvency-preserving liquidations fail. Despite the dominance of perpetual futures in the crypto derivatives market, with over $60 trillion of volume in 2024, there has been no form
Constant function market makers (CFMMs) such as Uniswap have facilitated trillions of dollars of digital asset trades and have billions of dollars of liquidity. One natural question is how to optimally route trades across a network of CFMMs in order to ensure the largest possible utility (as specifi
Lending within decentralized finance (DeFi) has facilitated over $100 billion of loans since 2020. A long-standing inefficiency in DeFi lending protocols such as Aave is the use of static pricing mechanisms for loans. These mechanisms have been shown to maximize neither welfare nor revenue for part
Restaking protocols have aggregated billions of dollars of security by utilizing token incentives and payments. A natural question to ask is: How much security do restaked services \emph{really} need to purchase? To answer this question, we expand a model of Durvasula and Roughgarden [DR24] that inc