These strategic initiatives act as enabling disciplines that strengthen research across all cores, accelerating innovation, expanding capabilities, and generating impactful solutions for people, the planet and prosperity.
Strategic
Initiatives
Artificial Intelligence for Impact
This initiative advances the development and application of intelligent systems that support decision-making, optimize complex processes, and drive innovation in health, sustainability, and industrial transformation.
This initiative advances classical and generative AI to create text, images, audio, and insights, applied to health, sustainability, and industry. It also addresses model efficiency, ethical use, regulation, impact measurement, and human–AI collaboration.
Faculty advancing emerging technologies
Our faculty bring diverse expertise in artificial intelligence, spanning research, teaching, and real-world applications. Together, they advance knowledge, guide students, and foster interdisciplinary collaboration.
The professors in the Strategic Initiative in Artificial Intelligence contribute from multiple disciplines, combining academic rigor with practical experience in areas such as machine learning, robotics, data science, and ethical AI. Their work strengthens research, supports innovative teaching, and encourages collaboration with industry and society to address complex challenges through responsible and impactful AI.
Our Latest
Findings
Minutiae-Based Palm Recognition with Deep Learning
Minutiae-Based Palm Recognition with Deep Learning
Engineering Applications of Artificial Intelligence
A GAN-based approach (FreqGAN) enhances blurred palm photos captured by smartphones, reducing creases and false minutiae. New DNN models improve minutiae extraction and feature robustness, outperforming existing methods for contactless palm recognition.
Fragmentation transparency in distributed databases
Fragmentation transparency in distributed databases
Journal Systems and Software
Distributed database theory is widely known, but fragmentation transparency is rarely supported in commercial systems. This study proposes a new syntax and prototype to optimize fragmented queries, showing improved performance in a real case study.
Prompt-Assisted Correction of Illumination in Endoscopy
Prompt-Assisted Correction of Illumination in Endoscopy
Springer Nature
Accurate medical diagnosis depends on image quality. We present a prompt-assisted system that reduces illumination artifacts in endoscopic images, enabling localized enhancement, improving SLAM performance, 3D reconstruction, and clinician-driven real-time corrections.
Nanotechnology & Semiconductors
This initiative brings together a multidisciplinary science and engineering group that works as a transversal enabler, strengthening the impact of applied research in Health, Climate and Sustainability, and Industrial Transformation.
In parallel, it promotes the evolution of Mexico’s semiconductor ecosystem by developing specialized training programs and strengthening university–industry–government collaboration. These efforts align education with industry needs while fostering research, innovation, and entrepreneurship in strategic niches of the semiconductor sector.
Faculty Contributing to Technological Advancement
Faculty members in this initiative apply their expertise in science and engineering to advance enabling technologies that strengthen research, innovation and knowledge generation across multiple fields.
Through interdisciplinary collaboration, these researchers support both applied and fundamental science, driving the development of new materials, devices and technological solutions. Their work amplifies the impact of research in health, sustainability and industrial transformation, while also contributing to training, knowledge transfer and the formation of highly specialized talent.
Our Latest
Findings
Advances in metal-free seawater electrocatalysts
Advances in metal-free seawater electrocatalysts
Renewable Energy
Seawater electrolysis enables green hydrogen from ocean resources but faces efficiency and durability challenges due to chloride oxidation. This review explores key mechanisms and advances in noble-metal-free catalysts to improve stability and performance.
Multimode fiber sensor using Fresnel reflection for RI
Multimode fiber sensor using Fresnel reflection for RI
Optics & Laser Technology
This study analyzes a multimode fiber sensor based on Fresnel reflection. Despite modal distribution and non-normal incidence, simplified assumptions yield accurate refractive index measurements, validated experimentally with <0.1% error.
Interferometric measurement of biphoton wave function
Interferometric measurement of biphoton wave function
Physical review letters
Interference between an unknown biphoton and a two-photon reference reveals a phase-sensitive arrival-time distribution containing full information on the temporal wave function, enabling its reconstruction from a squeezed vacuum state.