Lan Huang — Jilin University ML researcher spanning drug-discovery models, spectral pooling, and materials prediction.
3
papers here
0
reviewed by Evolve
0
first-author
0
corresponding
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works · OpenAlex
0
h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-17) 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—
This axis cannot be scored yet: the snapshot lists only three recent works and zero citation indices, with no total publication count or venue breakdown. It would measure cumulative and recent output volume and venue quality.
Impact—
No impact score is possible: h-index and i10-index are both zero in this snapshot and no citation counts are provided. This axis would measure citation-based influence such as h-index, i10-index, and citation trajectory once a fuller record exists.
Focus—
Focus cannot be scored: topic counts exist (two works each in drug-discovery ML, materials ML, and bioinformatics ML) but lack the per-field publication distribution the axis requires. It would measure thematic concentration and depth within a primary field.
Collaboration59/100
Lan Huang's collaboration dimension scores 59. The OpenAlex snapshot records 18 distinct coauthors, and the Evolve frequency list names recurring partners including Fengfeng Zhou, Ruochi Zhang, Kewei Li, and Rongying Zhang. All three 2026 catalog papers position Huang as a middle author rather than corresponding author, consistent with a collaborative, contribution-focused role inside a larger team rather than sole or senior leadership.
Activity40/100
The activity dimension scores 40. All three works in the snapshot fall in 2026 — recent3yWorks is 3 and countsByYear lists exactly three publications in 2026 — indicating a publishing surge this year but a thin record before it. Two of the three are Evolve-reviewed arXiv preprints, so the visible activity is concentrated in recent, not yet peer-reviewed, output.
Reproducibility—
No aggregate reproducibility score exists yet. Evolve's reviews flag two of three cataloged preprints at medium repro-readiness — one without code release, one with weakened ablations — but a full axis needs code-availability data across all works.
Research summary
Lan Huang is a machine learning researcher at Jilin University, China, profiled from OpenAlex bibliographic data; because 'Lan Huang' is a common name, identity confidence is moderate and no ORCID is linked. The snapshot suggests an early-career or incompletely attributed record: h-index 0, i10-index 0, three works in the past three years — all three dated 2026 — and 18 distinct coauthors. Topic assignments span Computational Drug Discovery Methods, Machine Learning in Materials Science, and Machine Learning in Bioinformatics (two works each), plus Advanced Chemical Physics Studies and Advanced Neural Network Applications (one each), a pattern of method-oriented contributions to applied ML problems. The Evolve catalog holds three 2026 arXiv preprints — CliffRank, FLaG, and DISTAL — in each of which Huang is a middle author, not corresponding author. Evolve's reviews of CliffRank (dual-branch activity-cliff ranking) and FLaG (Fourier-domain gated pooling) find gains real but modest, partly within seed noise, and rate repro-readiness medium; CliffRank lacks significance tests and code, and FLaG's ablations weaken its full design. DISTAL, on structure-agnostic materials property prediction, is not yet reviewed.
Collaboration pattern
Lan Huang works within a sizable collaborative network: the OpenAlex snapshot counts 18 distinct coauthors, and the supplied frequency list contains Fengfeng Zhou twice, alongside Kewei Li, Rongying Zhang, Zhongjian Wang, Ruochi Zhang, and Peiyu Yang. Across all three 2026 catalog papers Huang holds a middle author position without corresponding-author credit, consistent with a contributor role in a team whose work spans drug discovery, bioinformatics, and materials ML.
Research keywords
Highlights
CliffRank: dual-branch activity-cliff ranking, with caveats
FLaG: Fourier-domain gating helps pooling, modestly
DISTAL: self-supervised pretraining for materials, unreviewed
A 2026 arXiv preprint on structure-agnostic materials property prediction via distillation and self-supervised pretraining, with Huang as a middle author. It is not yet reviewed by Evolve, so no verdict, keywords, or reproducibility rating exists.
Timeline
- 2026CliffRank appears on arXiv: a dual-branch framework for activity-cliff ranking prediction.
- 2026FLaG appears on arXiv: frequency-domain latent-attention gated pooling for token aggregation.
- 2026DISTAL appears on arXiv: distillation and self-supervised pretraining for structure-agnostic materials property prediction.
- 2026Snapshot year on OpenAlex: all 3 recorded works date to 2026, alongside 18 distinct coauthors.
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.
- Profile is name-resolved from OpenAlex bibliographic data; 'Lan Huang' is a common Chinese name, so identity confidence is moderate and no ORCID is linked.
- Bibliometrics (h-index, i10-index, works, topics, coauthors) come from the OpenAlex snapshot only; zero citation indices likely reflect incomplete attribution or early career rather than measured influence.
- Only two of the three catalog papers carry Evolve verdicts; DISTAL is unreviewed, with no quality or reproducibility assessment.
- Both reviewed works are arXiv preprints rated medium for reproducibility; no code release was noted for CliffRank.