grant
Carnegie Mellon University — Research on Adversarial Examples
Metadata
| Source Table | grants |
| Source ID | IW6lqLtxni |
| Description | to carnegie-mellon-university, $343,235, 2022-07 |
| Source URL | coefficientgiving.org/grants/ |
| Parent | ULjDXpSLCI |
| Children | — |
| Created | Mar 12, 2026, 5:54 AM |
| Updated | Mar 23, 2026, 3:17 PM |
| Synced | Mar 19, 2026, 8:57 PM |
Record Data
id | IW6lqLtxni |
organizationId | Coefficient Giving(organization) |
granteeId | Carnegie Mellon University(organization) |
orgEntityId | Coefficient Giving(organization) |
orgDisplayName | — |
granteeEntityId | Carnegie Mellon University(organization) |
granteeDisplayName | carnegie-mellon-university |
name | Carnegie Mellon University — Research on Adversarial Examples |
amount | 343235 |
currency | USD |
period | — |
date | 2022-07 |
status | — |
source | coefficientgiving.org/funds/ |
notes | [Navigating Transformative AI] Open Philanthropy recommended a grant of $343,235 over three years to Carnegie Mellon University to support research led by Professor Aditi Raghunathan on adversarial examples (inputs optimized to cause machine learning models to make mistakes). This follows our Augus… |
programId | EXpTP-ujq6 |
dataSourceId | — |
Source Check Verdicts
confirmed95% confidence
Last checked: 4/9/2026
[deterministic-row-match] Deterministic match: grantee, amount, date matched in source snapshot (2714 rows)
Debug info
Thing ID: IW6lqLtxni
Source Table: grants
Source ID: IW6lqLtxni