Higher Technological Institute of the East of the State of Hidalgo | Mexico
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🧠 DR. GERMAN CUAYA-SIMBRO: A VISIONARY IN INTELLIGENT COMPUTING
🎓EARLY ACADEMIC PURSUITS
Dr. German Cuaya-Simbro began his academic journey with a clear inclination toward advanced computational studies. Holding a Ph.D. in Computational Sciences, he directed his research efforts toward machine learning, establishing a strong theoretical and analytical foundation early in his career. His academic rigour and research-driven mindset were instrumental in shaping a future focused on technological innovation and societal impact.
💼PROFESSIONAL ENDEAVORS
With eight years of professional experience as a Senior IT Consultant at IBM, Dr. Cuaya-Simbro built a formidable profile in the tech industry. His expertise spanned mainframe computing, high availability systems, virtualization, and cognitive computing. These experiences enriched his academic lens and prepared him for a robust career in research and higher education. Presently, he serves as a professor-researcher at the Higher Technological Institute of the East of the State of Hidalgo (TecNM), where he continues to bridge academic insight with real-world problem-solving.
Dr. Cuaya-Simbro's research addresses key challenges in Industry 4.0, leveraging cutting-edge technologies such as artificial intelligence, robotics, IoT, cloud computing, blockchain, big data, and cyber-physical systems. His contributions include leading and co-leading over a dozen nationally funded projects—ranging from deep learning systems for soil sustainability to AI-driven cloud platforms for education. He also explores probabilistic graphical models and graph data structures, with an active focus on precision agriculture and educational AI tools. His approach is rooted in the practical application of intelligent computing to address pressing global challenges, such as food security, healthcare, and education, aligning closely with the United Nations Sustainable Development Goals (SDGs).
🌍IMPACT AND INFLUENCE
Recognized as a CONAHCYT SNI Level C member, Dr. Cuaya-Simbro has influenced both national and international spheres. He has collaborated with prestigious institutions—such as a Colombian university—on developing AI-integrated teaching support systems. His work reflects a global vision that combines academic excellence with inclusive innovation. His mentorship of undergraduate and graduate students, coupled with impactful publications and registered innovations, positions him as a thought leader in smart, sustainable technology solutions.
📚ACADEMIC CITES
Dr. Cuaya-Simbro’s work is widely cited and indexed in prominent databases including Web of Science, Scopus, Scielo, CONAHCYT, SCIMAGO, and Sciendo. His peer-reviewed articles and conference papers contribute significantly to scholarly discourse in AI, machine learning, and cyber-physical systems, with consistent recognition from the global research community.
🏅LEGACY AND FUTURE CONTRIBUTIONS
Dr. Cuaya-Simbro’s legacy lies in his ability to transform complex computational theories into actionable innovations. His role in supervising theses, developing prototypes, securing patents, and publishing scientific works solidifies his status as a pioneer in intelligent computing and Industry 4.0 applications. As a member of research networks like REHICO México and consultant for companies such as QS Data Base Specialist SA de CV and End to End Technical Support LA SA de CV, he continues to extend his influence beyond academia. His future contributions are set to further empower educational systems, enhance sustainable technologies, and inspire the next generation of computational scientists.
🔎OTHER KEY AREAS OF EXPERTISE
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Domain: Graph Data Structures and Algorithms
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Subdomain: Structural Learning
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Professional Memberships:
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Research Network REHICO México
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Consultant with QS Data Base Specialist SA de CV
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Consultant with End to End (E2E) Technical Support LA SA de CV
📑NOTABLE PUBLICATIONS
"Deep learning to identifying food maturity for prevent food waste"
- Author: German Cuaya Simbro; David Williams Cuevas Ordoñez
- Journal: Engineering, Research and Technology
- Year: 2025
"Improving structural learning in Bayesian networks: Stationarity analysis for algorithm choice"
- Author: German Cuaya-Simbro; Manolo Tellez Meneses; Elías Ruiz Hernández
- Journal: Data and Information Management
- Year: 2025
"Proposal for an Adaptive Recommender System to Support Teaching Practices"
- Author: German Cuaya-Simbro; Jose A. Gonzalez; Elias Ruiz; Helena CI Alemán; Alexander Barinas
- Journal: International Journal of Interactive Mobile Technologies (iJIM)
- Year: 2025
"Recommender systems as a tool in teaching: a systematic review"
- Author: Mariana Torres-Herrera; German Cuaya-Simbro; Ciro Canales-Castillo
- Journal: Pädi Scientific Bulletin of Basic Sciences and Engineering of the ICBI
- Year: 2024
"Comparing Machine Learning Methods to Improve Fall Risk Detection in Elderly with Osteoporosis from Balance Data"
- Author: German Cuaya-Simbro; Alberto-I. Perez-Sanpablo; Eduardo-F. Morales; Ivett Quiñones Uriostegui; Lidia Nuñez-Carrera; Sharan Srinivas
- Journal: Journal of Healthcare Engineering
- Year: 2021