Funders › NJ › Matthew Larson Foundation for Pediatric › 2019
Grants paid by Matthew Larson Foundation for Pediatric, tax year 2019
EIN 37-1540551 · Franklin Lks, NJ · Form 990, Schedule I · NTEE T30
In tax year 2019, Matthew Larson Foundation for Pediatric (EIN 37-1540551) reported 7 grants paid totaling $525,000. Dataset version 2026.09.0, built 2026-09-03.
Every grant, 2019
| Tax year | Recipient | Match | Amount | Type | Purpose | Source filing |
|---|---|---|---|---|---|---|
| 2019 | Timothy Phoenix Phd Cleveland, OH | A | $75,000 | paid | Medl Research | 202000459349302040 |
| 2019 | Sarah Injac Md Dallas, TX | A | $75,000 | paid | Medl Research | 202000459349302040 |
| 2019 | Tabitha Cooney Md San Francisco, CA | A | $75,000 | paid | Medl Research | 202000459349302040 |
| 2019 | Chaomel Xiang Phd New York, NY | A | $75,000 | paid | Medl Research | 202000459349302040 |
| 2019 | Ram Kannan Phd New York, NY | A | $75,000 | paid | Medl Research | 202000459349302040 |
| 2019 | Jian Hu Phd Houston, TX | A | $75,000 | paid | Medl Research | 202000459349302040 |
| 2019 | Jessica Foster Md Philadelphia, PA | A | $75,000 | paid | Medl Research | 202000459349302040 |
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 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.