activity
20242026
most citedDecision Predicate Graphs: Enhancing Interpretability in Tree Ensembles

5 citations · 9 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CR2026

A Systematization of Knowledge on DeFi Vaults: Architectures, Curation Mechanisms, and Strategy Design

Davide Mancino, Luca Pennella

Decentralized finance (DeFi) vaults are smart-contract-based asset management systems that pool deposits, execute programmable strategies, and mint tokenized shares representing cl…

econ.GN2026

A Taxonomy of Real-World Asset Tokenization for Blockchain-Based Financial Infrastructure

Giorgio Vella, Luca Pennella, Mark C. Ballandies

Real-world asset (RWA) tokenization has emerged as a prominent application of blockchain technology, enabling off-chain financial and non-financial assets to be represented through…

cs.CE2026

Designing a Token Economy: Incentives, Governance, and Tokenomics

Samela Kivilo, Alex Norta, Marie Hattingh +2

In recent years, tokenomic systems, decentralized systems that use cryptographic tokens to represent value and rights, have evolved considerably. Growing complexity in incentive st…

cs.GT2025★ 1 cited

A Unified Framework and Comparative Study of Decentralized Finance Derivatives Protocols

Luca Pennella, Pietro Saggese, Fabio Pinelli +1

Decentralized Finance (DeFi) applications introduce novel financial instruments replicating and extending traditional ones through blockchain-based smart contracts. Among these app…

cs.ET2025★ 3 cited

Money in Motion: Micro-Velocity and Usage of Ethereums Liquid Staking Tokens

Benjamin Kraner, Luca Pennella, Nicolò Vallarano +1

We introduce a micro-velocity framework for analysing the on-chain circulation of Lidos liquid-staking tokens, stETH, and its wrapped ERC-20 form, wstETH. By reconstructing full tr…

cs.LG2024★ 5 cited

Decision Predicate Graphs: Enhancing Interpretability in Tree Ensembles

Leonardo Arrighi, Luca Pennella, Gabriel Marques Tavares +1

Understanding the decisions of tree-based ensembles and their relationships is pivotal for machine learning model interpretation. Recent attempts to mitigate the human-in-the-loop…