By Jon Saad-Falcon, Omar Shaikh, Jay Wang, Austin Wright, Sasha Richardson, and Polo Chau.

Discovering research expertise at institutions can be a difficult task. Manually curated university directories easily become out of date and often lack the information necessary to understand a researcher’s interests and past work, making it harder to explore the diversity of research at an institution and pinpoint potential collaborators, resulting in lost opportunities for both internal and external entities to discover new connections and nurture research collaboration.

To solve this problem, we have developed PeopleMap, the first interactive, open-source, web-based tool that visually “maps out” researchers based on their research interests and publications by leveraging embeddings generated by natural language processing (NLP) techniques. PeopleMap provides a new engaging way for institutions to summarize their research talents and for people to discover new connections. PeopleMap is developed with ease-of-use and sustainability in mind. Using only researchers’ Google Scholar profiles as input, PeopleMap can be readily adopted by any institutions using its publicly-accessible repository and detailed documentation.

Click the following links to access two live demos:

https://poloclub.github.io/people-map/ideas/

https://poloclub.github.io/people-map/ml/

We have tested the PeopleMap on Google Chrome, Firefox, Safari. It should run on all modern web browsers.

For steps on how to set up and deploy PeopleMap, please see PeopleMap's GitBook documentation at:

https://app.gitbook.com/@poloclub/s/people-map/

PeopleMap was created by Jon Saad-Falcon, Omar Shaikh, Jay Wang, Austin Wright, Sasha Richardson, and Polo Chau. We would also like to thank everyone in the Polo Club of Data Science for assisting us in the development of the project.

The software is available under the MIT License.

If you have any questions, feel free to open an issue or contact Jon Saad-Falcon.