Funders › FL › Nina Haven Scholarships Inc Fka Nina Haven Charitable Foundation › 2023
Grants paid by Nina Haven Scholarships Inc Fka Nina Haven Charitable Foundation, tax year 2023
EIN 13-6099012 · Stuart, FL · Form 990-PF, Part XV
In tax year 2023, Nina Haven Scholarships Inc Fka Nina Haven Charitable Foundation (EIN 13-6099012) reported 26 grants paid totaling $278,500. Dataset version 2026.09.0, built 2026-09-03.
Every grant, 2023
| Tax year | Recipient | Match | Amount | Type | Purpose | Source filing |
|---|---|---|---|---|---|---|
| 2023 | University of Florida Gainesville, FL | U | $96,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | University of South Florida Tampa, FL | U | $24,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Florida State University Tallahassee, FL | U | $22,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | University of Central Florida Orlando, FL | B | $21,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | Florida Atlantic University Boca Raton, FL | C | $12,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | Indian River State College Fort Pierce, FL | C | $10,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | University of North Florida Jacksonville, FL | U | $10,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Florida Gulf Coast University For Myers, FL | U | $8,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Grand Canyon University Phoenix, AZ | U | $7,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | Louisiana State University Baton Rouge, LA | B | $5,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | Stanford University Stanford, CA | C | $5,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | MIT Massachussetts Inst of Technology Cambridge, MA | U | $5,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | The University of Richmond Richmond, VA | U | $5,000 | paid | EDUCATION | 202411909349100216 |
| 2023 | Palm Beach Atlantic University West Palm Beach, FL | B | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | University of California Berkley Berkeley, CA | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | University of Miami Coral Gables, FL | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Duke University Durham, NC | B | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Harvard University Cambridge, MA | C | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | The University of Alabama Tuscaloosa, AL | B | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Auburn University Auburn, AL | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Belmont University Nashville, TN | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Virginia Tech Blacksburg, VA | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Brown University Providence, RI | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | University of Southern California Los Angeles, CA | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Georgia Institute of Technology Atlanta, GA | U | $3,500 | paid | EDUCATION | 202411909349100216 |
| 2023 | Vanderbilt University Nashville, TN | C | $3,500 | paid | EDUCATION | 202411909349100216 |
Match tier: A Reported EIN · B Exact name and place · C Strong name match · D Probable name match · U Unresolved. Tiers C and D are inferred, not reported; see how matching works.
Recipient matching for this dataset version has not yet completed its independent precision check. Tier A rows carry the EIN the filer reported; tiers B–D are the matcher's inference and should be read as leads until the check is published on the methodology page.
Derived from IRS Form 990-PF e-file XML. Dataset version 2026.09.0, built 2026-09-03. All years for this funder.
The same organization elsewhere in the program: exempt status and filing health · federal awards · grant guidance · open opportunities.
This is informational only, derived from public data on the dates shown. It is not an eligibility determination, and not legal, tax, or accounting advice. Verify against the official source before relying on it.