PROJECTS UNDER MENTORING
Cohorts 2024
Artificial Intelligence
The research aims to analyze artificial intelligence (AI)-based epidemiological surveillance platforms for pandemic prevention and preparedness in Latin America (LATAM), using the COVID-19 pandemic as a case study. To this end, traditional COVID-19 detection methods, such as Polymerase Chain Reaction (PCR) and rapid antigen tests, will be compared with next-generation technologies like Next-Generation Sequencing (PacBio SMRT, Oxford Nanopore Technologies (ONT), and Ion Torrent) and AI platforms (HealthMap and BlueDot).
This analysis seeks to highlight the importance of AI in health systems to provide a timely response to health emergencies. Additionally, recommendations will be provided to public health decision-makers in LATAM, aiming to strengthen health systems’ capacity to detect and manage infectious disease outbreaks, especially in resource-limited contexts.
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Global Health and Development
The project aims to gather information on the simulation of human emotions by artificial intelligence, resulting in a brief report on the legal and ethical implications. It will propose best practices for AI developers to guide responsible use and mitigate human-created biases, protecting individuals’ rights and ensuring transparency and accountability in using this technology. The current issue is the general public’s lack of understanding of AI’s potential in emulating human emotions and the possibility of manipulative use. Specialists from the World Compliance Association highlight concerns such as loss of control over personal information and the ability to make informed decisions. The research will employ a qualitative approach, collecting literature and conducting semi-structured interviews with experts. The final report will compare and analyze expert responses and literature review findings, to be published on Effective Altruism blogs, guiding government decision-makers in creating or modifying public policies and raising awareness among future AI developers to ensure ethical regulation in AI applications.
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Global Health and Development
This article addresses the importance of developing resilient food systems in response to potential Abrupt Sunlight Reduction Scenarios (ASRS). It initially focuses on identifying vitamin D-rich foods that can be produced, stored, and distributed during global food crises. Through the use of weighting matrices, various factors were evaluated, such as availability, vitamin D concentration, bioavailability, overall nutritional value, and production scalability. The results identify anchovies, chicken eggs, and cod liver oil as the most viable options to ensure adequate vitamin D intake. In particular, eggs and cod liver oil are effective during the first 3 to 9 months of the crisis, while anchovies are viable both during this initial period and the second phase, which lasts from 4 to 18 months. The study also analyzes the limitations and potential challenges in producing and distributing these foods under extreme conditions, highlighting the need for future research to propose strategies aimed at ensuring food security in crisis situations.
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Artificial Intelligence
This project, wilI intend to propose graph problem-solving tasks for different models, taking the BIG-benchmark format as a starting point and using models such as BLOOM, GPT-3, GPT-4, T5, FLAN-T5, and BERT.
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Communication
This project will explore the transformative impact of effective social media communication on the perceptions, attitudes, and behaviors of the Latin American audience regarding priority causes. Focusing on platforms like LinkedIn and Instagram, the research will target Latin American university students aged 18 to 26, aiming to increase their awareness of global catastrophic risks and important social issues through engaging content. The main objective is to demonstrate how continuous exposure to relevant social media content can raise public awareness. Initial strategies will include educating the audience on content and posting times, with a gradual increase in reach through tactics to boost followers and visibility.
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Communication
This project aims to raise awareness about pandemic prevention through an audiovisual communication strategy on platforms like TikTok and Instagram Reels. The series will cover historical and current pandemics, combining historical elements, expert interviews, and impactful visual content. The methodology includes thorough research, detailed scripts, and audiovisual production. The findings will focus on the effectiveness of social media interventions in influencing audience behavior. In conclusion, this project seeks to fill an informational gap and contribute to future pandemic prevention while advancing the student creator’s career by integrating skills in communication, audiovisual production, and technology.
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Global Health and Development
The project will examinate the feasibility and effectiveness of integrating alternative protein and plant-based diets as strategies to combat malnutrition and undernutrition in India.evaluating sections and articles of the treaty and exploring diplomatic alternatives, including other bilateral or multilateral agreements and confidence-building measures among nuclear powers.
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Biosafety & Biosecurity
This report aims to explore the challenges and opportunities in preventing and detecting pandemic-potential pathogens in Ecuador. It starts with a detailed analysis of the country’s current epidemiological situation, reviewing major biological threats and their potential public health impacts. It then examines existing surveillance systems and outlines the procedures and manuals for efficient outbreak response. Finally, it explores improvement opportunities in pathogen prevention and detection, proposing specific recommendations to strengthen health and surveillance systems, enhance outbreak response capabilities, and promote collaboration among various stakeholders in national and international risk management.
Gabriela was accepted in the Genomics and Epidemiological Surveillance of Bacterial Pathogens course from the Universidad de Costa Rica, after being recommended by Carreras con Impacto.
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Artificial Intelligence
This paper focuses on the collection and modeling from scaling laws of a dataset oriented to speech recognition models, with the aim of estimating trends in their capabilities. The dataset was created by reviewing 172 studies related to speech recognition, collecting variables such as the number of model parameters, floating-point operations (FLOPS), and word error rates (WER). The main challenges in developing this research include difficulties encountered when the number of FLOPS is not reported in the reviewed studies. It was found that the architectures with the lowest error rates (WER) are Transformer (2.6% WER) and E-Branchformer (1.81% WER). Change rates in trends for different benchmarks were estimated (Common Voice Spanish 5 months, LibrarySpeech Test Clean 7 months, LibrarySpeech Test Other 10 months). Finally, the high uncertainty of the estimates was noted due to the small sample size, and potential future research directions were suggested.
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Global Health and Development
The project idea arises from the awareness that many development aid initiatives are not effectively functioning. However, there is existing knowledge on how to conduct effective interventions and make optimal institutional decisions. The project aims to answer the question: Can the academic frameworks developed by organizations aligned with Effective Altruism be applied to projects by smaller actors? What is the best way to disseminate this knowledge? This idea is envisioned as a bridge, a consultancy work connecting academic frameworks with local initiatives, with the goal of finding the best way to exchange information between them.
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