Early-career UT Dallas researcher spanning LLM-assisted kernel bug detection and egocentric video understanding
2
papers here
2
reviewed by Evolve
0
first-author
0
corresponding
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works · OpenAlex
0
h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-15) 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—
Output is not yet scored: this OpenAlex record lacks a publication-volume baseline beyond the four recent works, so productivity relative to field norms cannot be computed. This axis would measure total and per-year publication counts.
Impact—
Impact is not yet scored: OpenAlex reports h-index and i10-index of 0, giving no usable citation signal. This axis would measure citation counts, h-index trajectory, and influence on subsequent research.
Focus0/100
The focus score is 0, and the underlying fieldDist explains it: this record splits exactly evenly, 0.5 to software engineering (static analysis and LLM-assisted bug detection) and 0.5 to computer vision (egocentric video understanding). The topic list repeats the pattern, pairing Human Pose and Action Recognition, Speech and Audio Processing, and Multimodal Machine Learning Applications (2 each) with Logic/Programming/Type Systems and Software Engineering Research (1 each). No single direction yet dominates.
Collaboration39/100
Collaboration scores 39 on a 0-100 scale, drawn from a compact coauthor footprint: six distinct coauthors appear in the OpenAlex record, and the frequent-collaborator list — Ruoyu Wang, Tuo Li, Feiyu Du, Xi He, Yapeng Tian, Weili Wu — spans both research lines. In both catalog papers Li holds neither first nor corresponding authorship (middle on the talk-to-me paper, last on TyPatch), indicating contributor rather than lead roles so far.
Activity47/100
Activity scores 47. The OpenAlex countsByYear list contains a single entry — 4 works in 2026 — and recent3yWorks confirms 4 works over the most recent three-year window, so all visible output is compressed into one year. Both catalog papers are 2026 arXiv preprints, consistent with a burst of recent submissions; older yearly counts are absent, so sustained cadence cannot yet be judged.
Reproducibility38/100
Reproducibility scores 38 (reproMean), averaged over the two papers Evolve has reviewed (reproPapers = 2). Ratings differ by direction: TyPatch is rated medium, while the talk-to-me detection paper is rated low, with reviewers flagging possible ground-truth target-box input leakage and the cost of a 900K-frame benchmark as practical barriers. ArXiv-only sourcing also means peer-reviewed artifacts are not yet in evidence.
Research summary
Jia Li is a researcher at The University of Texas at Dallas whose public bibliographic record, resolved from OpenAlex, spans two distinct lines of work: software engineering — static analysis and LLM-assisted bug detection — and computer vision, specifically egocentric video understanding. The record is early-stage: OpenAlex lists an h-index and i10-index of 0, four works across the most recent three-year window (all four surfacing in 2026), six distinct coauthors, and a focus score of 0 reflecting an even 0.5/0.5 split between the two fields. In software engineering, TyPatch (2026) transforms kernel patches into LLM-generated typestate rules, reporting 559 detected bugs at 88–90% lower cost than KNighter, while an initial precision of 4.7–9.1% marks filtering as open work. On the vision side, a rethinking of talk-to-me detection recasts the task as online four-state frame prediction on a 900K-frame benchmark (75.5% F1), with reviewers flagging possible ground-truth target-box input leakage for scrutiny. Both catalog entries are arXiv preprints carrying Evolve reproducibility ratings of low and medium (mean 38), and neither credits Li as first or corresponding author. This profile is a name-resolved, evolving snapshot rather than a settled record.
Collaboration pattern
Jia Li's visible coauthor network is compact: OpenAlex lists six distinct coauthors, and the frequent-collaborator set — Ruoyu Wang, Tuo Li, Feiyu Du, Xi He, Yapeng Tian, Weili Wu — spans both research lines, yielding a collaboration score of 39. Neither catalog paper credits Li as first or corresponding author (middle position on the talk-to-me paper, last on TyPatch), so the current pattern reads as a contributing member of small teams rather than a lead.
Research keywords
Highlights
TyPatch turns kernel patches into LLM-mined typestate rules (559 bugs, 88–90% cheaper than KNighter)
Talk-to-me detection reframed as online four-state prediction (75.5% F1, with a leakage caveat)
Timeline
- 2026TyPatch posted to arXiv: LLM-mined typestate rules detect 559 Linux kernel bugs at 88–90% less cost than KNighter (last-author position).
- 2026Talk-to-me detection paper posted to arXiv, recasting the task as online four-state frame prediction with 75.5% F1 on a 900K-frame benchmark (middle position).
- 2026OpenAlex records 4 works in 2026 — the entire recent three-year output — across 6 distinct coauthors and a 0.5/0.5 split between two fields.
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 bibliometrics come from OpenAlex only; h-index and i10-index are recorded as 0, so citation impact cannot yet be assessed.
- ORCID is not linked and 'Jia Li' is a common name; this profile is name-resolved from public bibliographic data and may merge or split identities.
- Qualitative assessments rest on only two reviewed papers, both 2026 arXiv preprints; this is an early-stage profile.
- Dimension scores (including the reproducibility mean of 38) derive from just two Evolve-reviewed papers and should be read as indicative.