From algorithmic game theory to reinforcement learning in quantitative finance: mechanism design to DeFi market making
2
papers here
2
reviewed by Evolve
0
first-author
0
corresponding
—
works · OpenAlex
16
h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-16) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.
Research profile
Output—
Not yet scored: this snapshot lacks the underlying volume data the output axis needs. It would measure total works, venue quality distribution and per-year productivity, normalized for career stage and field conventions.
Impact—
Not yet scored: citation-level aggregates required for the impact axis are unavailable in this snapshot. It would measure field-normalized citation performance and uptake of this researcher's methods and frameworks by other groups.
Focus0/100
The focus score of 0/100 reflects exceptional topical breadth rather than a missing record: the OpenAlex record spreads across five topic clusters — Game Theory and Voting Systems (126 works), Game Theory and Applications (96), Auction Theory and Applications (96), Financial Markets and Investment Strategies (42) and Stock Market Forecasting Methods (35) — and the recent field split is exactly even (0.5/0.5) between market microstructure and machine learning for finance.
Collaboration39/100
Collaboration scores 39/100 in this snapshot: the recent three-year window lists 6 distinct coauthors, and the recurring circle — Georgios Chionis, Charalampos Kleitsikas, Stefanos Leonardos, Leandro Sánchez-Betancourt, Giovanni Dispoto and Marcello Restelli — supplies the author teams for both reviewed 2026 papers. Both works are last-authored, a pattern consistent with a senior role inside a stable quant-finance and reinforcement learning group rather than large ad-hoc consortia.
Activity100/100
Activity is the standout axis at 100/100: 75 works in the last three years, and OpenAlex counts-by-year climbs from 4 works (2018) through 13 (2019) and 19 (2022) to 22 (2024), a record 28 (2025) and 25 already logged in 2026. Cumulative career indicators — h-index 16 and i10-index 34 — keep pace with a publishing rate roughly four times the late-2010s level.
Reproducibility55/100
Reproducibility sits at 55/100, matching the 55/100 reproducibility mean across the 2 scored papers, both rated medium readiness. Evolve's verdicts explain the middling band: SAiFE-gym ships modular, vectorized environments but rests its empirical case on a single thin demonstration, while the ESG elicitation pipeline is sound yet leans on synthetic ratings and LLM-persona oracles in place of human preference data.
Research summary
Carmine Ventre (King's College London) is a computer scientist whose OpenAlex record spans two decades, from 2003 to the present, with an h-index of 16 and an i10-index of 34. The bibliometric core sits in algorithmic game theory: the record's largest topic clusters are Game Theory and Voting Systems (126 works), Game Theory and Applications (96) and Auction Theory and Applications (96), alongside smaller finance clusters in Financial Markets and Investment Strategies (42) and Stock Market Forecasting Methods (35). The recent profile, however, is firmly quantitative finance: the current field distribution splits evenly between market microstructure (DeFi and reinforcement learning) and machine learning for finance. Activity is the standout signal — 75 works in the last three years and a 100/100 activity score, with annual counts climbing from 4 (2018) to 19 (2022), 22 (2024) and 28 (2025). Evolve has reviewed two 2026 arXiv papers, both last-authored: SAiFE-gym, modular RL environments for concentrated-liquidity automated market making, and a multi-objective RL plus Gaussian-process pipeline for eliciting ESG preferences in portfolio optimization. Both earn medium reproducibility readiness (mean 55/100), with verdicts praising engineering soundness while flagging thin empirical validation and synthetic preference oracles.
Collaboration pattern
The recent record shows a compact, stable team: 6 distinct coauthors in the last three years (collaboration score 39/100), anchored by Georgios Chionis, Charalampos Kleitsikas, Stefanos Leonardos, Leandro Sánchez-Betancourt, Giovanni Dispoto and Marcello Restelli. Both 2026 Evolve-reviewed papers are last-authored team efforts, a pattern consistent with a senior or supervisory role in a quant-finance and reinforcement learning group rather than solo writing or large ad-hoc consortia.
Research keywords
Highlights
SAiFE-gym: RL environments for concentrated-liquidity market making
Eliciting ESG preferences for RL-based portfolio optimization
Output surge: 75 works in three years
OpenAlex counts-by-year reaches 22 works in 2024, a record 28 in 2025 and 25 already logged in 2026 — 75 works over the last three years and a 100/100 activity score, the fastest stretch of a career recorded since 2003.
Timeline
- 2003Earliest year in the OpenAlex counts-by-year record (1 work), with output building through the 2000s — 8 works by 2006.
- 2013A first clear peak: 10 works, followed by 8 in 2014 and 11 in 2015.
- 2019Output re-accelerates to 13 works after a flat stretch of 4 per year from 2016 to 2018.
- 202219 works recorded — the highest annual total to that point in the record.
- 2025Record year: 28 works, after 22 in 2024; 25 more are already logged in 2026.
- 2026Two last-authored arXiv papers enter the Evolve catalog: SAiFE-gym for concentrated-liquidity market making and multi-objective RL with ESG preference elicitation.
Papers in the Evolve catalog
Frequent co-authors
About this profile
This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.
- All bibliometric figures come from a single OpenAlex snapshot (identity: openalex); citation-level detail beyond h-index (16) and i10-index (34) is not available.
- Output and impact axes are unscored in this snapshot (insufficient underlying data), so no citation-normalized impact claims are made here.
- Evolve has reviewed only two papers, both 2026 arXiv preprints with last-author positions; quality signals beyond these two works are not represented.
- The profile is name-resolved from public bibliographic data and linked to ORCID 0000-0003-1464-1215; historical topic counts may span a long career.