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· Public charity

Marconi Society Inc

Building communities of leaders and stakeholders that are at the forefront of emerging technology so that together we can create a more connected and sustainable world.

$65k
Granted FY2024still arriving
4
Grants FY2024still arriving
2
States reached
$50k
Largest
01What it funds
0197% classified

What it funded, over time

Every grant placed by its stated purpose and the recipient’s mission, by year, FY2017 to 2024.

Education$65kArts & Culture$65kScience & Tech$32kSocial Science$14kHealth$11kOther$0
02FY2024 · 4 grants

Where the money goes

Grants by size, and the largest recipients.

By grant size · FY2024

  • Under $10k3 grants · $15k
  • $50k–250k1 grant · $50k
$5,000
Median grant
2
States reached
$655k
Total assets
Largest grants
RecipientAmount
Individual grant recipient$50,000
Individual grant recipient$5,000
Individual grant recipient$5,000
Individual grant recipient$5,000
02The need
03

Does the money reach high-need areas?

Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.

US giving: 68% of grant dollars ($162k). The need read here covers only this US portion; the 32% that went abroad ($75k) is mapped below.

show:

Dollar for dollar, its grants (FY17–24) land where the poverty rate runs at 13%, against an area that typically sits at 9%. 56% of its dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 9%WENHAN DAI: $4k → 8%Pennsylvania State University: $50k → 16%KARTIK VENKAT: $148 → 8%TERESA MENG: $50k → 9%NEGAR REISKARIMIAN: $4k → 17%GEORGE MACCARTNEY JR: $4k → 20%KENNETH MARK PESYNA JR: $800 → 10%JOSEPH M LUKENS: $600 → 12%JUNWEN ZHANG: $4k → 4%AAKANKSHA CHOWDHERY: $600 → 11%WENHAN DAI: $881 → 8%NEGAR REISKARIMIAN: $779 → 17%GEORGE MACCARTNEY JR: $1k → 20%VENKAT ARUN: $5k → 10%JUNWEN ZHANG: $1k → 4%STEFANIA BARTOLETTI: $4k → 8%ANANDA THEERTA SURESH: $4k → 17%GEORGE MACCARTNEY JR: $420 → 20%STEFANIA BARTOLETTI: $1k → 8%ANANDA THEERTA SURESH: $572 → 17%SHU SUN: $4k → 20%STEFANIA BARTOLETTI: $572 → 8%JARED GREENE: $14k → 20%DINESH BHARADIA: $4k → 8%SHU SUN: $631 → 20%DINESH BHARADIA: $1k → 8%DINESH BHARADIA: $547 → 8%0%20%40%50%more need →
grant to an above-average-need area below average· circle size = grant amount
How this is measured
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty line in the grantee’s ZIP, averaged from the tracts in that ZIP.

Beyond the US: 32% of all-years giving ($75k)

3 countries, by the recipient’s country on the filing.

grant dollars sentlessmore
Uganda$65k · 3 grants
Canada$5k · 1 grant
United Kingdom$5k · 1 grant
How this is measured
US grants placed by each grantee’s ZIP, which can differ from where services are delivered. Need from public data (U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA), shown as context about the area, never attributed to the funder’s giving. International giving is mapped by the recipient’s country from the same 990 filings; comparable need data isn’t available at that grain.
03Its grantees
repeat funding

Who it funds again

Organizations funded in more than one year, against those funded once.

34%of every dollar goes to organizations it has funded before.
$81k · 4 repeat orgs$155k to everyone else

4 repeat relationships: 0 still active in FY2024, 4 since wound down; 4 grantees were first funded in FY2024 (too recent to call).

How the two cohorts compare

Re-uppedFunded once

Organizations

4
11

Total granted

$81k
$90k

Still filing today

0%
0%

New vs renewed · share of each year

In FY2024, 0% of grant dollars renewed an existing relationship; $65k went to new ones.

50%100%’17’18’20’21’22’23’24
RenewedFirst-time
How this is measured
First-time means a grantee’s first year in the filing window; renewed means funded in an earlier year too. The renewed share climbs naturally as a portfolio matures, so the signal is a year that bucks it (a wave of new grantees). The earliest year is left-censored: relationships that predate the data read as new. Theme is the grantee’s IRS cause.

Backed again, and grew

  • IG
    Individual grant recipient
    3× · 2021–2023 · $65k
  • IG
    Individual grant recipient
    2× · 2017–2018 · $6k
  • IG
    Individual grant recipient
    2× · 2017–2018 · $6k

Funded once

  • PS
    PENNSYLVANIA STATE UNIVERSITY
    one grant, 2020 · $50k
  • IG
    Individual grant recipient
    one grant, 2018 · $14k
  • IG
    Individual grant recipient
    one grant, 2017 · $5k
How this is measured

Repeat means funded in two or more distinct years. Growth and survival are read from each grantee’s own subsequent IRS filings.

04Its field
04the grantee network

0 grantees tracked through their own filings, 2017–2024.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2017 to 2024, not grant rows in a single year, so this will not match the grant count on the cover. 0 of the 19 grantees resolved in that span have returns of their own we could reconcile.

Each grantee is resolved to its own IRS returns. Association, dated; never a causal claim.

0
Load-bearing (≥25% of a budget)
0
Early backer (in before they grew)
0/0
Grantees still filing
0/0
Grew since first funded

Where the money sits, by cause and then by grantee

Individual grant recipient: $64,960 · OtherIndividual grant recipientIndividual grant recipient: $50,000 · OtherIndividual grant recipientPENNSYLVANIA STATE UNIVERSITY: $50,000 · OtherPENNSYLVANIA STATE UNIVERSITYIndividual grant recipient: $14,000 · OtherIndividual grant recipient+15 more: $57,550 · Other+15 more
Other$236,510

Each grantee by its size and the funder’s share of it; top left is load-bearing

25%50%75%100%grantee revenue →↑ funder's share of their budget
Grantee by grantee: a decade per organization, before and after funding

A decade per grantee: revenue shaded, grants as bars, all rows on one timeline.

On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, and from the multi-year returns of the 19 grantees we resolved, each linked to its source. Grantee outcomes are each organization’s own program-service reporting (Form 990, Part III), read as association with funding, never as caused by it. Low-confidence name matches are suppressed rather than guessed. How we build these →

How this is measured
Each figure carries one of six labels. Filed is what the funder reported on its return. Official is another government record about an organization, such as a federal award or a charity register, joined by name where no shared identifier exists. Resolved is an identity we worked out where the filing named a recipient without an EIN, kept only above a measured confidence threshold. Computed is arithmetic over those, like themes, portfolio clusters and co-funder strength. Context is a statistic about a place rather than about an organization, which is what the need overlay is: it describes the area a grantee’s address sits in, not where its work lands. Inferred is drawn by a model from text, like the partnerships read out of public news and organization websites. Each is labeled where it appears.

Generated from the IRS Form 990-PF e-file return for fiscal year 2024, released 2024. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

Possibly out of date. A more recent filing (FY2025) is on record and reports $70k of grant expense with no grantee named in the published copy. A private foundation itemizes every grant it makes, so a return carrying none has filed its list as an attachment that the public copy does not include. The figures above are therefore from FY2024, the most recent year this funder’s grantee list reached the public record.

Source object · view filing

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