3 papers in the archive (2024–2025), average empirical rigor 5.5/10, average math complexity 6.2/10. Quadrant mix: Holy Grail ×1, Lab Rats ×1, Street Traders ×1.
Works mostly in Crypto Markets & DeFi, High-Frequency Trading & Optimal Execution, Risk Management & Tail Risk, Market Simulation & Agent-Based Models.
Frequent co-authors: Madhur Prabhakar (1), Tanuj Behl (1), Rik Ghosh (1), Samrat Gupta (1), Arka Datta (1), Sudipan Sinha (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 propose a mathematically rigorous framework for identifying and completing Coincidence of Wants (CoW) cycles in decentralized exchange (DEX) aggregators. Unlike existing auction based systems such as CoWSwap, our approach introduces an asset matrix formulation that not only verifies feasibility u
Compound Finance is a decentralized lending protocol that enables the secure and efficient borrowing and lending of cryptocurrencies, utilizing smart contracts and dynamic interest rates based on supply and demand to facilitate transactions. The protocol enables users to supply different crypto asse
As restaking protocols gain adoption across blockchain ecosystems, there is a need for Actively Validated Services (AVSs) to span multiple Shared Security Providers (SSPs). This leads to stake fragmentation which introduces new complications where an adversary may compromise an AVS by targeting its