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Dos Investigadores de la Iniciativa estratégica en Inteligencia Artificial
Iniciativa Estratégica en Inteligencia Artificial
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The Advanced Artificial Intelligence Research Group conducts basic and applied research in all aspects of artificial intelligence. In particular, it contributes to general knowledge in the following subdisciplines: machine learning, computer vision, image processing, computational intelligence, hyper-heuristics, and data visualization, applying them to solve problems in contexts such as healthcare, business, public safety, and cybersecurity, among others.

Given its intersection with the areas mentioned above, our group also plays a role in the development and application of data science.

Objectives

 

This initiative focuses on two main pillars of Artificial Intelligence (AI):):

  • Classic AI: It encompasses established techniques such as machine learning, deep learning, natural language processing, computer vision, hyper-heuristics, and robotics.
  • Generative AI: It involves the creation of new data such as text, images, video, and voice.

Research Areas: 

• Machine Learning
• Computational Intelligence and Hyper-Heuristics
• Data Science and Applied Mathematics
• Biomedical Engineering

Group members:

  • Members of the Strategic Initiative on Artificial Intelligence
    Members of the Strategic Initiative on Artificial Intelligence
  • Members of the Strategic AI Initiative
     Members of the Strategic AI Initiative

Areas & Objectives

Our goal is to harness the enormous potential of AI for the benefit of humanity and to advance its knowledge, delivering products designed to meet the following requirements:

1. Energetic efficiency: Our goal is to develop AI models and algorithms that are more energy-efficient in order to reduce their environmental impact. This includes, among others, techniques such as model compression, algorithm design and optimization, machine learning, data analysis and verification, and AI-oriented hardware design.
2. Sustainable Design: We will explore how to ensure that AI design takes environmental issues into account, including the development of hardware and software that minimize the carbon footprint without overlooking functional and performance requirements. We will also investigate how to make AI more robust against misuse and other vulnerabilities. In addition, we will study how to make AI more accurate, reducing mistrust and the potential for discrimination.
3. Data Governance: We will study how to establish robust data governance to ensure that personal information collected and processed by AI is handled securely and in compliance with regulations.
4. Transparency and explainability: Transparency and Explainability: We will develop AI that promotes transparency, providing clear information on how data is collected, processed, and used, as well as on the decisions made by AI systems. In addition, we will investigate the design and development of mechanisms that explain how predictions and recommendations are generated, so that users can understand and trust the outcomes delivered by artificial intelligence. 
5. Cibersecurity: We will investigate the design and development of robust cybersecurity mechanisms to protect AI systems against threats such as hackers, malware, and adversarial attacks.

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