Optimization researcher at Northwestern University working on transfer-based multitask and few-shot multiobjective optimization
2
papers here
2
reviewed by Evolve
0
first-author
0
corresponding
—
works · OpenAlex
11
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 axis measures total publication volume and productivity trajectory. The snapshot's per-year counts and 22 recent works are descriptive only; the complete output statistics needed for a score are not available.
Impact—
Not yet scored. This axis would measure citation-based influence such as citation totals and field-normalized impact. The snapshot lists an h-index of 11 and an i10-index of 12, but the underlying citation data needed for scoring is insufficient.
Focus0/100
Scores 0, reflecting dispersion rather than concentration. The field distribution splits evenly — 50% machine learning (optimization and evolutionary computation), 50% evolutionary computation and transfer optimization — and OpenAlex topics span optimization alongside photocatalysis, pollutant adsorption, and graphene clusters, so the concentration measure sits at the floor despite adjacent optimization fields.
Collaboration39/100
Scores 39, a modest level. Wu records 6 distinct co-authors in the last three years; frequent collaborators include Yew-Soon Ong, Jiao Liu, Tingyang Wei, Zhao Wei, Puay Siew Tan, and Ananda Phan Iman. Both Evolve-reviewed 2026 papers place Wu in a middle, non-corresponding position, consistent with a contributing member of a small, stable team.
Activity91/100
Scores 91, the strongest axis. Per-year works climb from 1 in 2020 to 3 in 2021 and 2022, 4 in 2023, then 8 in 2024 and 7 in each of 2025 and 2026 — 22 works in the last three years, more than half of the roughly 33 total recorded works. Output is both recent and sustained.
Reproducibility78/100
Scores 78, based on Evolve reviews of 2 papers with a mean readiness of 78. The iterative sequential transfer preprint is rated high readiness; the in-context TabPFN paper is rated medium, with reviewers noting no ablation isolates the informed guidance component.
Research summary
Haofeng Wu is a researcher at Northwestern University (US) whose bibliometric profile, name-resolved from OpenAlex records, centers on optimization: the field distribution splits evenly between machine learning (optimization and evolutionary computation) and evolutionary computation and transfer optimization, at 50% each. The snapshot records an h-index of 11, an i10-index of 12, and roughly 33 works between 2020 and 2026, with output accelerating sharply — from 1 work in 2020 to 4 in 2023, 8 in 2024, and 7 in each of 2025 and 2026, for 22 works in the last three years. OpenAlex topics are led by advanced multi-objective optimization algorithms (7) and metaheuristic optimization research (6), with smaller clusters in photocatalysis, pollutant adsorption, and graphene — a breadth that may reflect cross-disciplinary output or name-resolution mixing. Two 2026 arXiv preprints reviewed by Evolve — in-context guidance via frozen TabPFN, and iterative sequential transfer for few-shot multiobjective multitask optimization — position Wu as a mid-list, non-corresponding contributor in transfer-based multitask optimization, working alongside co-authors including Yew-Soon Ong and Jiao Liu.
Collaboration pattern
Wu's collaboration footprint is compact: 6 distinct co-authors over the last three years, with frequent partners including Yew-Soon Ong, Jiao Liu, Tingyang Wei, Zhao Wei, Puay Siew Tan, and Ananda Phan Iman. Both 2026 catalog papers carry Wu in a middle, non-corresponding author position, indicating a contributing collaborator within a small, stable team rather than a solo or corresponding-author role.
Research keywords
Highlights
In-context guidance from TabPFN for few-shot multitask optimization
Iterative sequential transfer for few-shot multiobjective multitask optimization
Rapid output growth since 2024
Counts by year rise from 1 work in 2020 to 8 in 2024 and 7 in each of 2025 and 2026, with 22 works in the last three years — over half of the roughly 33 recorded works.
Timeline
- 2020First recorded works appear in the OpenAlex per-year counts, with 1 work.
- 2023Output reaches 4 works, continuing steady early growth.
- 2024Yearly output peaks at 8 works, opening a sustained high-productivity phase.
- 20257 works sustain momentum for a second consecutive high-output year.
- 2026Two arXiv preprints on few-shot multitask optimization — in-context TabPFN guidance and iterative sequential transfer — enter the Evolve catalog.
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.
- Bibliometrics are drawn from OpenAlex only; citation totals and the output/impact dimension scores are not available in this snapshot.
- Haofeng Wu is a common name; this profile is name-resolved from public bibliographic data, and the topic mix (optimization plus photocatalysis, adsorption, and graphene) may reflect cross-disciplinary work or entity mixing in name resolution.
- The reproducibility score is based on Evolve reviews of only 2 papers.
- No career facts beyond institution and country are in the input data; no awards, roles, or biography are asserted.