Data-management veteran now leading polar GeoAI: uncertainty-aware sea-ice mapping and autonomous Arctic navigation
3
papers here
3
reviewed by Evolve
0
first-author
0
corresponding
—
works · OpenAlex
24
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—
No output-dimension score is available in this snapshot: the underlying publication-volume aggregates are incomplete. This axis would measure total works, output trajectory, and productivity consistency over the career; it is left unscored rather than estimated.
Impact—
Impact data is insufficient for scoring in this snapshot; citation-based aggregates are not available here. This axis would measure citation counts, citation trajectory, and the uptake of this researcher's work by the wider field; it is not estimated.
Focus0/100
Focus scores 0/100 because the record is deliberately broad: the recent field distribution splits evenly (0.33 each) across machine learning for polar sea-ice remote sensing and GeoAI route planning, while career topic counts span data management and algorithms (47), database systems (36), GIS (22), peer-to-peer networks (16), and COPD research (14).
Collaboration28/100
The collaboration axis scores 28/100, reflecting a compact working circle: the recent record lists only 3 distinct coauthors, and all three Evolve-catalog papers place Banaei-Kashani in the last (senior) author position with none as corresponding author. Recurring partners Samira Alkaee Taleghan, Younghyun Koo, and Andrew P. Barrett point to a small, stable team rather than a broad collaboration network.
Activity97/100
Activity scores 97/100 on sustained, currently accelerating productivity: the OpenAlex counts-by-year series runs from 2001 through 2026, with 27 works in the most recent three-year window and a peak of 19 works in 2022, followed by 8 works in each of 2023–2025 and 11 already in 2026 — a quarter-century record that remains dense at its latest edge.
Reproducibility70/100
Reproducibility scores 70/100, the mean readiness across the 3 Evolve-reviewed papers: two sea-ice studies rate medium readiness (multi-label proportion learning; uncertainty-aware mapping with multiple ice charts), while the Arctic eco-navigation GeoAI agent rates high — strong for a profile whose recent work leans on complex multi-annotator labels and multi-agent systems.
Research summary
Farnoush Banaei-Kashani is a computer scientist at the University of Colorado Denver (US; ORCID 0000-0003-4102-9873), whose profile is name-resolved from OpenAlex bibliographic data. The career record spans 2001–2026 with an h-index of 24 and an i10-index of 47, and topic counts anchored in data management and algorithms (47 works), advanced database systems and queries (36), geographic information systems (22), peer-to-peer networks (16), and COPD research (14). Activity remains high: 27 works in the last three years, peaking at 19 in 2022 and continuing at 8–11 works per year through 2026. The current cataloged focus has narrowed onto polar GeoAI: machine learning for sea-ice monitoring from Sentinel-1 SAR, uncertainty quantification across multiple operational ice charts, and autonomous LLM-based agents for multi-objective Arctic route planning. Three 2026 arXiv papers in the Evolve catalog place Banaei-Kashani in the last (senior) author position, with frequent coauthors Samira Alkaee Taleghan, Younghyun Koo, and Andrew P. Barrett, and a compact recent coauthor set of 3. Evolve's reproducibility review averages 70 across the three papers (medium, medium, high), with the Arctic eco-navigation agent rated highest. Output- and impact-dimension scores are not available in this snapshot and are left unscored.
Collaboration pattern
The collaboration axis scores 28/100 and the recent record lists just 3 distinct coauthors. All three Evolve-catalog papers place Banaei-Kashani as last (senior) author, none as corresponding author, consistent with supervising a small core team. Recurring collaborators are Samira Alkaee Taleghan, Younghyun Koo, and Andrew P. Barrett, indicating a stable small-team pattern rather than a wide coauthor network.
Research keywords
Highlights
Uncertainty-aware sea-ice typing across four national ice charts
Reframing sea-ice prediction as multi-label proportion learning
An autonomous GeoAI agent for Arctic eco-navigation
Timeline
- 2026Publishes “Multi-Label Proportion Learning for Sea-Ice Type Prediction” on arXiv (last author; Evolve reproducibility readiness: medium).
- 2026Publishes “Uncertainty-Aware Sea-Ice Type Mapping with Multiple Ice Charts” on arXiv (last author; Evolve reproducibility readiness: medium).
- 2026Publishes “An Autonomous GeoAI Agent for Arctic Eco-Navigation” on arXiv (last author; Evolve reproducibility readiness: high).
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.
- Bibliometric figures (h-index, i10-index, counts by year, topics) come from an OpenAlex snapshot; output- and impact-dimension scores were unavailable and are not estimated.
- Identity is name-resolved from public bibliographic data (OpenAlex, ORCID 0000-0003-4102-9873); no independent biographical verification was performed.
- The timeline covers only Evolve-catalog papers, all 2026 arXiv preprints, so it is not a full career chronology.
- Reproducibility scores reflect Evolve's reviews of 3 papers only; the rest of the record is unassessed.