Applied Platforms | CRiSS-LAB

Capybara: AI-assisted school coexistence and bullying prevention

Mon, 01 Sep 2025 00:00:00 +0000

Capybara is an applied platform for school coexistence and bullying prevention. It uses a brief, age-appropriate interaction to map classroom relationships and transform those interactions into evidence about cooperation, reciprocity, integration, leadership, isolation, and group fragmentation.

The platform supports school teams by identifying early relational signals, prioritizing preventive action, and providing clearer evidence for follow-up. It builds on CRiSS-LAB research in experimental game theory, social networks, cooperation, and learning environments.

Discolab: Collaborative Discussions

Mon, 15 Aug 2022 00:00:00 +0000

The Discolab platform offers a service for collaborative readings and discussions that helps generate solutions to complex problems. By placing users at the center, Discolab aims to increase people's knowledge through their interactions with others, machines, and various methods of processing information. This idea emerged as a continuation of postdoctoral research on engagement and information diffusion in online content conducted by academic Cristian Candia-Castro Vallejos, Ph.D., at Northwestern University's Kellogg School of Management.

Discolab enables people to interact on both public and private content. Users can create annotations linked to each paragraph of the content in question. Other users can vote on these annotations, and an algorithm orders them, prioritizing new and highly consensus annotations. By doing so, Discolab makes it easy for teams and organizations to find consensus and crystallize the knowledge and information that every member holds, making it accessible to others in an auditable and user-friendly manner.

Users can vote for or against the content being discussed and the annotations made by other users. Discolab then displays rankings for the content, the comments, and the users based on the votes. This feature helps identify the contents or processes that generate more consensus, as well as more controversy, in teams and organizations, allowing them to prioritize potential issues.

Currently, Discolab allows users to interact for free on the actual texts of the political constitutions of both the current and proposed Republic of Chile. Users can interact on the paragraphs of each constitutional text by voting at the article level and leaving comments. Rankings are then displayed to identify the articles that generate more consensus or division and the comments that help the community understand the legal text. Discolab also identifies the most controversial and polarized users.

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SocialRec: Personalizing Educational Experience through Social Network-based Recommender Systems

Mon, 01 Aug 2022 00:00:00 +0000

This project was undertaken as part of the University's Personalization Strategic Project, and it involved overcoming several challenges. The first of these was integrating data from various sources, each with their own unique formats, which required significant effort to ensure compatibility. Additionally, privacy and security were paramount concerns given the sensitive nature of the data. To address these issues, we developed both an anonymization protocol and a de-identification process that could preserve the necessary granularity of the data. Our team also developed a novel algorithm capable of creating a benchmark for inferring social networks from router connections. Finally, we integrated the analysis of mixed, individual, and relational data to build a recommendation system based on machine learning and interaction networks, which is a cutting-edge approach. Our work will be valuable for researchers and companies looking to develop state-of-the-art recommendation systems in their own research or business endeavors.

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Lixandria: A Platform for discovering your degree program

Sun, 01 Dec 2019 00:00:00 +0000

Lixandria is a platform that offers guidance, visualization, and distribution of data on university careers. It utilizes the Higher Education Space (HES), which integrates information from historical applicants to the higher education system through their preferences and a network science-based algorithm. By doing so, the HES expands the options available to applicants when selecting their desired career. Additionally, Lixandria integrates and distributes data from multiple sources, such as the Ministry of Education, DEMRE, and mifuturo.cl, empowering applicants to the higher education system and decision-makers in higher education institutions and the central government.

The HES was originally developed as part of Cristian Candia’s Doctoral Thesis in 2018, which was carried out at the MIT media lab and the Center for Research in Social Complexity at UDD. The seminal article of Lixandria, which both constructs and validates the HES, was published in 2019 by Professor Cristian Candia (University of Desarrollo) in collaboration with Professor Flavio Pinheiro and researcher Sara Encarnaçao (both from Universidade NOVA de Lisboa).

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