4 papers in the archive (2022–2026), average empirical rigor 1.9/10, average math complexity 9/10. Quadrant mix: Lab Rats ×4.
Works mostly in Stochastic Control & Optimal Stopping.
Frequent co-authors: Dominykas Norgilas (2), Xiang Yu (1), Jiacheng Zhang (1), Xin Zhang (1), Erhan Bayraktar (1), Gaoyue Guo (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%).
We explicitly construct the supermartingale version of the Fr{é}chet-Hoeffding coupling in the setting with infinitely many marginal constraints. This extends the results of Henry-Labordere et al. obtained in the martingale setting. Our construction is based on the Markovian iteration of one-period
We consider the distribution-constrained optimal stopping problem $\sup_{τ\sim μ} \mathbb E[B^τ]$, where $μ$ is a probability distribution on $\mathbb R+$, and $(B^_t)$ denotes the running maximum of a standard Brownian motion. This problem was introduced in Beiglbock et al. (PTRF, 2018), where
We investigate stability properties of weak supermartingale optimal transport (WSOT) problems on $\mathbb{R}$. For probability measures $μ,ν\in\mathcal{P}r$ satisfying $μ\leq{cd} ν$ (equivalently, $Π_S(μ,ν)\neq\emptyset$), we consider supermartingale couplings $π=μ(d x)π_x(d y)$ and the weak trans
This paper studies a central planner’s decision making on behalf of a group of members with diverse discount rates. In the context of optimal stopping, we work with an aggregation preference to incorporate all discount rates via an attitude function that reflects the aggregation rule chosen by the c