LLM uncertainty quantification researcher with roots in stochastic modeling and quantitative finance
2
papers here
2
reviewed by Evolve
2
first-author
1
corresponding
—
works · OpenAlex
15
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 scored: complete per-work output records are unavailable for this OpenAlex profile, so cumulative publication volume cannot be verified. This axis would measure total and per-year works across all indexed venues.
Impact—
Not scored: citation-level aggregates are not populated for this profile, so scholarly influence cannot be measured. This axis would capture citation counts, citation velocity, and uptake of the works indexed under this researcher ID.
Focus0/100
The focus axis scores 0, reflecting a split profile: the current field distribution assigns 0.5 to natural language processing / machine learning (LLM uncertainty and governance) and 0.5 to natural language processing (LLM uncertainty quantification), while cumulative OpenAlex topic counts remain dominated by financial topics such as stock market forecasting methods (26) and stochastic processes and financial applications (25).
Collaboration0/100
The snapshot records 0 distinct co-authors and lists no frequent co-authors, so this axis scores 0 and the co-authorship network cannot be characterized. Both reviewed 2026 preprints are first-authored, one also corresponding, consistent with a lead-author working mode — but the zero should be read as a data gap rather than verified solo output.
Activity84/100
Activity scores 84 on recent volume: 17 works in the last three years and 14 works already recorded in 2026, approaching the all-time peak of 21 in 2020. Yearly counts reach back to 2003 (2 works), with earlier surges of 6 works in 2011 and 7 in 2018, indicating a sustained and currently accelerating publication cadence across two decades.
Reproducibility38/100
Reproducibility scores 38, the mean across 2 papers assessed by Evolve. The two 2026 preprints carry low and medium reproducibility readiness respectively: the stochastic lexical calculus paper's empirical evidence is a small synthetic demo, and the evidence-graphs paper's headline governance results rest on a 20-sample test — the theory was judged sound in both cases.
Research summary
Matthew Francis Dixon, listed at IIT Research Institute (US), is profiled here from public OpenAlex bibliographic data resolved against ORCID 0000-0001-5908-1747. The record spans two strands. A long-running quantitative-finance bibliography dominates cumulative OpenAlex topic counts — stock market forecasting methods (26), stochastic processes and financial applications (25), financial markets and investment strategies (20), financial risk and volatility modeling (17), and parallel computing and optimization techniques (16). More recently, a first-authored 2026 arXiv line addresses uncertainty quantification and governance for large language models, and the profile's current field distribution splits evenly (0.5/0.5) between LLM uncertainty quantification and LLM uncertainty and governance. Evolve reviewed both preprints, judging the theory sound while flagging thin empirical validation — a small synthetic demo in one case and a 20-sample governance test in the other. Activity is the strongest axis (84): 17 works in the last three years, 14 works already recorded in 2026, approaching the all-time peak of 21 in 2020, with h-index 15 and i10-index 21. Reproducibility averages 38 across the two assessed papers. Output and impact remain unscored for lack of citation-level records, and the co-author network is unresolved in this snapshot.
Collaboration pattern
Both reviewed 2026 preprints are first-authored — one also corresponding — pointing to a lead-author working pattern. However, the OpenAlex snapshot records 0 distinct co-authors and the frequent-coauthor list is empty, so no key collaborators can be named and the co-authorship network should be treated as unresolved in this profile.
Research keywords
Highlights
Stochastic Semantic Evidence Graphs: certifying uncertainty in agentic AI workflows
Foundations of Stochastic Lexical Calculus: when can LLM probabilities act as a stochastic state?
Timeline
- 2003Earliest works appear in the OpenAlex record, with 2 indexed publications in this year.
- 2011Annual output rises to 6 indexed works, the highest count of the record's first decade.
- 2020All-time publication peak in the record: 21 indexed works in a single year.
- 2021Output moderates into a lower-volume phase: 5 works in 2021, then 4 in 2022, 1 in 2024, and 2 in 2025.
- 202614 works recorded so far, including both reviewed first-authored arXiv preprints on LLM uncertainty quantification and agentic-AI governance.
Papers in the Evolve catalog
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.
- Profile is name-resolved from public OpenAlex bibliographic data (identity: openalex) tied to ORCID 0000-0001-5908-1747; non-indexed output may be missing.
- Output and impact axes are unscored because citation-level records are incomplete; the recorded h-index (15) and i10-index (21) are the only citation aggregates available.
- The co-author network is unresolved: 0 distinct co-authors recorded and no frequent co-authors listed, so collaboration patterns could not be verified.
- The reproducibility score is a mean over only 2 assessed papers, both 2026 arXiv preprints, and may not represent the wider bibliography.