File built on September 15, 2026

US College & University Administrator Contacts
U.S. Location Dataset // 135,434

Every person a US college or university names in a public record — 135,434 people across 6,014 institutions, with their title, our normalised job function (chief administrator, finance, procurement and grants, payments, academic, admissions, athletics, coaching, governance) and, on the IRS rows, their federally reported pay (45,598 rows). Built from IRS Form 990 Part VII officer schedules, SAM.gov entity registrations, the IPEDS chief administrator field and the athletics staff directories colleges publish on their own sites. Every row carries the document or page it came from. Email addresses appear on 12,422 rows and phone numbers on 30,795 — only where the institution publishes them on its own staff directory. Nothing is pattern-generated. One row is one named person — 135,434 of them, the full national file. It is built from the federal IPEDS collection run by the National Center for Education Statistics, the Department of Education's Equity in Athletics Data Analysis collection, the College Scorecard, IRS Form 990 officer schedules, SAM.gov entity registrations, and the staff directories institutions publish on their own athletics sites The federal sources are US government works in the public domain. The athletics staff-directory rows carry the page they were read from and the date they were read. Nothing in it was bought, licensed or taken from another company's product. Measured on every row of this file: a phone number on 22.7%, a person's title on 99.8%. 16 columns in all, and the page lists the fill rate for each one. What is not in it: No email addresses on the institution file. No federal source publishes a contact email for a college, and nothing here is generated from a name and a domain. No campus square footage. No federal collection publishes it. Not a branch-campus list. A university with several campuses under one federal id is one row. No rows from the NCAA member directory. Its terms prohibit republication.

What we did to this data: Re-placed 0 misplaced map points, flagged 135,434 incomplete addresses and measured 135,434 rows. Rebuilt September 15, 2026 from nces.ed.gov.

The source is a free public file from nces.ed.gov. What this file adds: checked every map point against the state in its address and re-placed 0 points that fell outside that state; flagged 135,434 addresses that are incomplete, a PO box, or missing a house number, in an address quality column; checked that the row count, state count and field completeness published for this file were measured from the file itself; and all 135,434 rows in one download.

How complete the key fields are: email 9%, phone 23%, state 100%. 12 of 16 columns are filled on at least half the rows.

135,434named people
59States
16Data Fields
September 15, 2026File built

The file has all 135,434 named people across 59 states in one download. Building the same list by searching one area at a time tends to miss places, and a missed place looks like a gap in coverage that is not really there.

Ask this list a question with a link

Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.

How assistants ask

No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.

If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.

Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>

Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>

Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro).

Open one of these to see how many rows match, a few preview rows and the price for just that part:

Where the rows are

Free preview: how many rows fall in each ZIP code. Names and contact details come with the file.

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Who uses this data

Higher-Ed Vendors & Campus Sales

Territory and account planning against the real institution universe — by enrolment, sector, Carnegie class, revenue and athletics programme, with a named person to address by job function.

Athletics & Team Suppliers

Which institutions field which sports, how many athletes of each sex they kit out, their NCAA or NAIA division, and the athletic director where the school publishes one.

Procurement & Grants Teams

The finance, controller, grants and payments contacts a purchase order actually passes through, taken from federal filings rather than a compiled contact list.

Researchers & Policy Analysts

The full Title IV population with enrolment, admission rate, tuition, accreditor, graduate earnings, core revenue and staffing on one row, joinable to any federal education file on the institution ID.

Where this data comes from

This dataset is built from IPEDS — the federal directory every Title IV institution must file with the National Center for Education Statistics — joined on the institution's own federal ID to the Department of Education's Equity in Athletics collection, the College Scorecard, and the IPEDS finance and staffing files. The named people come from three more published records: the chief administrator IPEDS itself collects, the officer schedules of IRS Form 990 for institutions that file one, and the points of contact on SAM.gov entity registrations. SAM.gov carries no institution ID, so it is matched on name and state and the match rate is measured and printed rather than assumed. Athletic directors are read from the staff directory an institution publishes on its own athletics site, with the page and the date on the row. The NCAA member directory is not used: its terms prohibit republication.

September 15, 2026

File built

16 fields

Columns filled on at least 1% of rows

Fill measured

On every row of the delivered file

Institutions are published as the federal collections hold them. An institution with no athletics programme is written as No rather than left blank, because that is a measured fact. Core revenue is carried from whichever of the three accounting standards applies and labelled, never totalled across them. City spellings are corrected to the Census place name for their postcode, counties are confirmed against the coordinates, and every row carries a coordinate-precision flag and an address-quality flag. There are no email addresses: no federal source publishes one for a college, and none is guessed from a name and a domain.

How we build and date every file: methodology.

Three ways to buy this dataset

The whole file

$149

All 135,434 records as a CSV. One payment, yours to keep, no subscription.

Just the rows you need

$0.23 / 100 rows

Open a link above to see the count and price for just those rows, then buy them by card. Buying the file wins above 67,717 records.

Optional: connect

Repeat use

Not needed for a one-off question: the links above work in any assistant. Connect an assistant for repeat use or to pay from a wallet.

Get this list through ChatGPT or Claude

No setup needed. Ask ChatGPT or Claude your question about the US College & University Administrator Contacts and give it this page: it can open https://locationlists.com/find?dataset=college-administrator-contact-list with the filters you need and show you the count and price.

Optional: connect for repeat use or wallet payments:

Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the US College & University Administrator Contacts list.

Your assistant will walk you through setup and show you the price before you pay.

For developers

Every step below has a no-connector equivalent: https://locationlists.com/find?dataset=college-administrator-contact-list with the same filters as query parameters.

  1. Connect your agent to https://locationlists.com/mcp (no key, no signup).
  2. Call count_locations with dataset: "college-administrator-contact-list" and any filter — it is free, and returns how many rows match and what they cost.
  3. Fetch the rows with query_locations: $0.23 per 100 rows from this dataset. Above 67,717 rows, buying the whole file is cheaper.

Paid in USDC over x402 — the agent gets an HTTP 402 with the exact price, signs, and retries. Money moves only after rows are delivered, so a failed or empty query costs nothing. Setup for Claude, Cursor and VS Code

{}Data Fields

unitid100%institutionName100%state100%personName100%title100%titleFamily100%contactClass100%reportedPay34%compensationYear34%phone23%email9%source100%sourceKey100%sourceUrl100%referenceYear100%address_quality100%

The percentage is how much of the file carries that field, measured on the delivered CSV rather than estimated. 4 of 16 fields are populated on under half the rows (reportedPay, compensationYear, phone, email).

How complete each column is
ColumnRows filled
unitid100%
institutionName100%
state100%
personName100%
title100%
titleFamily100%
contactClass100%
reportedPay34%
compensationYear34%
phone23%
email9%
source100%
sourceKey100%
sourceUrl100%
referenceYear100%
address_quality100%

Sample Data Preview

college-administrator-contact-list.csv5 of 135,434 rows, 12 of 16 columns · scroll →UTF-8
unitidsourceUrlinstitutionNamestatepersonNametitletitleFamilycontactClasssourcesourceKeyreferenceYearaddress_quality
102553https://nces.ed.gov/ipeds/University of Alaska AnchorageAKSean ParnellChancellorpresidentchief_administratoripeds1025532024-25missing
135364https://nces.ed.gov/ipeds/Luther Rice College & SeminaryGADr. Steven SteinhilberPresidentpresidentchief_administratoripeds1353642024-25missing
161688https://nces.ed.gov/ipeds/Allegany College of MarylandMDCynthia BambaraPresidentpresidentchief_administratoripeds1616882024-25missing
182634https://nces.ed.gov/ipeds/Colby-Sawyer CollegeNHLaura SykesInterim Presidentpresidentchief_administratoripeds1826342024-25missing
217615https://nces.ed.gov/ipeds/Aiken Technical CollegeSCForest E. MahanPresidentpresidentchief_administratoripeds2176152024-25missing
Showing 5 real rows from the file, all 12 columns that carry data in them. The free sample file has up to 10 rows. 4 further columns are empty in the rows shown here.

US College & University Administrator Contacts

135,434 named people · CSV · File built on September 15, 2026

Buy Dataset — $149

?Frequently Asked Questions

What is one row?

One institution as the federal government counts it — 6,072 of them — located at its main campus address. It is not a campus list: a university with five campuses reporting under one federal id is one row here. The coordinates are the main campus, so a radius or drive-time filter gives you the place the decision gets made.

Does it name anyone I can write to?

Yes, by job. The chief administrator — usually the president or chancellor — is named on 98.8% of records. A named finance, controller, procurement or grants contact is on 59.8%, and 59.9% of institutions carry at least one named person beyond the chief administrator. Those names come from IRS Form 990 officer schedules and SAM.gov registrations, both public domain, and every one is traceable to the document it came from.

Are there email addresses?

Not on this file. No federal source publishes a contact email for a college: IPEDS has no email field, Form 990 has none, and SAM.gov's point-of-contact emails are withheld from the public extract. We do not guess addresses from a person's name and the institution's domain. The separate contacts file does carry email on the rows where an institution publishes it on its own staff directory page, and nowhere else.

Do you have the athletic director?

On 831 institutions — 40.8% of the 2,036 that run an intercollegiate programme. The name is read from the staff directory the school publishes on its own athletics site, so it is only there when the school publishes one. 636 of those rows also carry a published athletics phone number. We do not use the NCAA member directory: its terms do not allow it to be republished.

What athletics data is in it?

For the 2,036 institutions with a programme: the NCAA, NAIA or NJCAA classification, how many sports they sponsor, athlete counts for men and women, and head-coach counts — all from the federal Equity in Athletics collection, which every Title IV institution with a programme must file. An institution with no programme is written as No, not left blank. Sport-by-sport detail is a separate file.

What financial figures are included?

Core revenue and core expenses on 98.2% of records, from the federal finance collection. Public, private non-profit and for-profit institutions report under three different accounting standards, so the file carries whichever one applies plus a column saying which — never a total across the three, which would not mean anything. Published tuition, admission rate and median graduate earnings come from the College Scorecard.

How complete are the contact details?

Measured on every row of this file: a street address on 100.0%, a phone number on 98.8%, a website on 98.8% and map coordinates on 100.0%. The product page lists the fill rate for every column, so nothing is a surprise after you buy it.

What was cleaned up before you sold it?

City names were checked against the US Census place name for their ZIP code, lost leading zeros in ZIP codes were repaired, county names and codes were confirmed against the coordinates, and every row was graded for address completeness. Two campuses of one university at one address are never merged, because the federal institution id guards the check. The processing log on this page lists each step with its count and date.

How is it different from the free federal data?

The federal data is five separate collections that do not join themselves: institutional characteristics, athletics, the College Scorecard, the finance and staffing files, plus Form 990 and SAM.gov for the names. This is those five joined on the federal institution id, with the fuzzy join measured and reported rather than assumed, and with the named contacts sorted into job functions by rule. You can build it yourself; this is a day of work for the price of a lunch.

How often is it updated?

File built on September 15, 2026. It is not on an automatic refresh schedule, so check the build date above before you buy.

Where exactly does it come from?

From the federal IPEDS collection run by the National Center for Education Statistics, the Department of Education's Equity in Athletics Data Analysis collection, the College Scorecard, IRS Form 990 officer schedules, SAM.gov entity registrations, and the staff directories institutions publish on their own athletics sites. The federal sources are US government works in the public domain. The athletics staff-directory rows carry the page they were read from and the date they were read. Nothing in it was bought, licensed or taken from another company's product.

Is the NCAA directory in it?

No. The NCAA publishes a member directory that names the athletic director at nearly every member, but its terms prohibit republishing it in any form. We checked, and we left it out. The athletics names in this file come from the institutions' own published staff directories.

Does it include campus square footage, enrolment by programme, or rankings?

No. No federal collection publishes campus square footage. Programme-level enrolment and any kind of ranking are out of scope; this is a list of institutions with the facts a seller needs to target and address them.

Can I match it to other lists?

Yes. Every row carries the federal IPEDS institution id and, where it exists, the Office of Postsecondary Education id and the IRS employer identification number, so it joins cleanly to federal student-aid data, nonprofit filings and federal contracting records. Coordinates are on nearly every row for matching against any other list of places.

How is this data cleaned?

Every rebuild runs the same steps and counts what each one changed. For the current file, rebuilt September 15, 2026 from nces.ed.gov: Merged 0 duplicate listings that had the same business name, street address and ZIP code, keeping every filled-in detail from both (September 15, 2026). Unified 0 city names written more than one way within the same ZIP code (for example with and without a space or an abbreviation) to the US Census Bureau spelling (September 15, 2026). Corrected 0 misspelled city names to the US Census Bureau place name for their ZIP code (September 15, 2026). Added map coordinates to 0 listings that had none, from the US Census Bureau address geocoder or, where the street address could not be matched, the centre of the ZIP code (September 15, 2026). Checked every map point against the state in its address and re-placed 0 points that fell outside that state (September 15, 2026). Set the county and its federal county code on 0 listings, matched to the US Census Bureau county list from the county the source records, the listing's map point, or its ZIP code area (September 15, 2026). Flagged 135,434 addresses that are incomplete, a PO box, or missing a house number, in an address quality column (September 15, 2026). Checked that the row count, state count and field completeness published for this file were measured from the file itself (September 15, 2026).

Isn't this free on nces.ed.gov?

The underlying records are public on nces.ed.gov. What you pay for is the work between that public release and this file: re-placed 0 misplaced map points, flagged 135,434 incomplete addresses and measured 135,434 rows. The current file was rebuilt September 15, 2026 from nces.ed.gov. Doing it yourself means downloading the full release, repeating each of those steps, and repeating them again every time the source updates.

How complete is each field?

Measured on every row of the current file, the share of rows that carry each key field: email 9%, phone 23%, state 100%. 12 of 16 columns are filled on at least half the rows.

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