Collaborative Research: Frameworks: MobilityNet: A Trustworthy CI Emulation Tool for Cross — NSF Award to University of California
In the era of Artificial Intelligence, accessing large-scale data plays a pivotal role in advancing Science and Engineering research. However, most of these mobility data are often proprietary and thus cannot be accessed or are costly to acquire by the Science and Engineering community unless released by data owners. R
| Award title | Collaborative Research: Frameworks: MobilityNet: A Trustworthy CI Emulation Tool for Cross |
|---|---|
| Award ID | 2411153 |
| Awardee | University of California-Los Angeles |
| City | LOS ANGELES |
| State | CA |
| Amount obligated | $330,000 |
| Principal investigator | Yuan Tian |
| Program | Software Institutes |
| Start date | 07/01/2024 |
| Abstract | In the era of Artificial Intelligence, accessing large-scale data plays a pivotal role in advancing Science and Engineering research. However, most of these mobility data are often proprietary and thus cannot be accessed or are costly to acquire by the Science and Engineering community unless released by data owners. Recently, under the context of Data Science for Social Good, some data owners are willing to share their mobility data with the public to unlock their values, but there are signific |
| Source | NSF Awards |
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