3 papers in the archive (2026), average empirical rigor 8.2/10, average math complexity 7.2/10. Quadrant mix: Holy Grail ×3.
Works mostly in Crypto Markets & DeFi, Stochastic Control & Optimal Stopping, Statistical Arbitrage & Pairs Trading, Reinforcement Learning for Trading.
Frequent co-authors: Edward W. Felten (1), Akaki Mamageishvili (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%).
Concentrated liquidity provision in decentralized exchanges presents a fundamental Impulse Control problem. Liquidity Providers (LPs) face a non-trivial trade-off between maximizing fee accrual through tight price-range concentration and minimizing the friction costs of rebalancing, including gas fe
Flashblocks divide a block’s priority gas auction into shorter sequential auctions that commit transaction order before the block is complete. We ask how this auction cadence affects bidding and competition among automated arbitrageurs, or searchers. In July 2025 Base replaced a single 2 s auction w
Demand on blockchain-based marketplaces arrives in bursts and at a high rate. On these platforms the data are completely visible, which makes it feasible to compare the bursty demand against the usual load. The congestion manifests as an increased demand for gas, the primary resource a blockchain se