جست‌وجوی استاد و پژوهشگر

José Luis Zechinelli Martiniمشاهده پروفایل

استاد

• Efficient and distributed data management
• Ambient Systems
• Cloud computing
• +۵ مورد دیگر

José Luis Zechinelli Martini is a full-time Professor in the Department of Computing, Electronics and Mechatronics at the School of Engineering, University of the Americas Puebla (UDLAP), serving as Academic Coordinator of the Bachelor's Degree in Computer Systems since 2002. A regular member of the Mexican Academy of Computing (2016-present), his career spans over two decades with significant contributions to distributed data management and cloud computing research. His educational background includes: PhD in Computer Science, Université Grenoble I Master's Degree in Information and Communications Systems, Université Grenoble I Bachelor of Computer Systems Engineering, University of the Americas, Puebla Dr. Zechinelli Martini's research centers on integrating Big Data collections across heterogeneous infrastructures through spatiotemporal query languages for distributed multimedia retrieval. His work bridges efficient data management , ambient systems , and cloud architectures with emerging focus on decolonial AI and inclusive urban computing . Recent projects emphasize ethical resource allocation in federated learning and climate change history analysis in Latin American contexts. His 2020-2024 publications reveal a strategic shift toward societally impactful applications , combining data science with environmental sustainability (GREENHOME energy monitoring), historical analysis (LACLICHEV climate archives), and urban equity. Key trends include decolonial frameworks for AI fairness, data lake architectures for natural sciences, and inclusive pipeline design through computational creativity, demonstrating cross-disciplinary integration of computer science with social and environmental domains. While no specific awards are documented, his Mexican Academy of Computing membership and leadership in internationally funded projects signify professional recognition. He has coordinated major research initiatives funded by CONACyT, ECOS-ANUIES, European Community FP7, and Microsoft. Academically, he shaped curriculum and student development through the Disciplinary Committee on Student Affairs (2006-2016), Graduate Committee, and Honors Program Committee, while promoting critical thinking through practical pedagogical strategies. As lead researcher in the GALILEAN project on "Just in Time" cloud architectures (LIRIS CNRS/University of Arizona collaboration) and former head of the Franco-Mexican Laboratory's Database Group (2008-2020), he directs teams advancing distributed data processing for massive datasets with international scientific impact.

Alvaro Alvarez-Delgadoمشاهده پروفایل

پژوهشگر

• Engineering Education
• Digital Humanities
• Natural Language Processing in Education
• +۵ مورد دیگر

Alvaro Alvarez-Delgado serves as an Adjunct Researcher at Tecnológico de Monterrey's School of Humanities and Education (Campus Santa Fe), where he pioneers interdisciplinary approaches merging digital humanities with engineering education. His work focuses on developing innovative pedagogical frameworks that integrate storytelling, natural language processing, and cultural studies to enhance STEM learning outcomes. His academic credentials include: Bachelor of Hispanic Languages and Literature from Universidad Veracruzana (Poza Rica-Tuxpan) Master in Hispanic Literature from El Colegio de México PhD in Hispanic Literature from El Colegio de México Alvarez-Delgado's research program centers on Education 4.0 challenges, specifically investigating how digital literacy, metacognitive awareness, and creative thinking can be cultivated in engineering students through transdisciplinary methods. His publications demonstrate consistent innovation in applying humanities perspectives to technical education, with particular emphasis on Industry 4.0 skill development and soft skills cultivation. Analysis of his 2018-2023 publications reveals three dominant thematic clusters: (1) NLP applications for learning assessment in STEM, (2) storytelling/art-based techniques for developing critical thinking, and (3) Education 4.0 frameworks for soft skills development in engineering. These strands converge in his development of micro-workshops and serious-storytelling methodologies that bridge humanities and engineering curricula. His expertise directly supports United Nations Sustainable Development Goals: Quality Education (SDG 4) through innovative pedagogical frameworks Industry, Innovation and Infrastructure (SDG 9) via Industry 4.0 skills research Affordable and Clean Energy (SDG 7) through engineering education applications Alvarez-Delgado teaches specialized courses including 'Cultural Imaginaries of Mexico', 'Symbolic Structures in Image, Literature and Music', and 'The Myths that Inhabit Us', while maintaining active research collaborations evidenced by his 112 Mendeley readers and conference presentations at IEEE EDUCON and FIE. His work represents a significant contribution to humanizing technical education through humanities integration.

José de Jesús Rocha Salazarمشاهده پروفایل

استاد

• Business Analytics
• Business Intelligence
• Economic Analysis
• +۵ مورد دیگر

José de Jesús Rocha Salazar serves as Professor in the Department of Marketing and Business Intelligence at EGADE Business School, Tecnológico de Monterrey, leveraging 12+ years of financial sector experience from institutions including Grupo Financiero Banorte, HSBC Bank, and Principal Financial Group to bridge academic research with industry applications in business intelligence and risk management. His academic credentials comprise: Doctor in Data Science, Complutense University of Madrid Master in Mathematical Sciences, University of Liverpool Master in Economic Sciences, Autonomous University of Nuevo León Bachelor in Mathematics, Autonomous University of Nuevo León Rocha Salazar's research integrates generative AI, IoT, natural language processing, and cloud computing to transform financial risk management across credit, liquidity, operational, and market domains. His work pioneers computational approaches for detecting financial crimes through business intelligence frameworks that enhance internal processes and regulatory compliance in banking, insurance, and pension sectors. His publication trajectory reveals consistent innovation in financial crime detection methodologies, evolving from neural network applications for money laundering identification (2021) to dynamic social network analysis for shell company exposure (2022) and macroeconomic fraud determinant modeling (2024), demonstrating interdisciplinary convergence of computer science, finance, and security analytics. Key recognitions include: summa cum laude doctoral distinction for thesis on money laundering/terrorism financing detection Industrial award for patent-developed implementation in financial institution systems No student advisement or grant activities are documented in available materials. His research operates through direct industry collaboration rather than formal lab structures, focusing on real-world deployment of forensic accounting systems and GenAI-driven risk frameworks within financial institutions.

Ricardo Caraza-Camachoمشاهده پروفایل

استاد بالینی

• Neuroscience
• Psychiatry
• Cognitive Neuroscience
• +۳ مورد دیگر

Ricardo Caraza-Camacho serves as a Clinical Professor and Adjunct Researcher within the Psychiatry department at Tecnológico de Monterrey's School of Medicine and Health Sciences (Campus Monterrey). His work is anchored in the "Biomarcadores y terapias avanzadas" research group, focusing on translational neuroscience applications for psychiatric and neurological conditions. His academic credentials include: Forensic Surgeon from Universidad Autónoma de Nuevo León Master in Cognitive Neuroscience and Human Behavior from Inst. de Est. Sup. Neurociencias, Psicoanálisis y Salud Mental Medical Specialty in Psychiatry from Universidad Autónoma de Nuevo León PhD in Clinical Sciences from Tecnológico de Monterrey Caraza-Camacho's research integrates computational methods with clinical neuroscience to pioneer EEG-based communication systems, neurophysiological biomarkers for ALS, and virtual reality therapies for social phobia. His work emphasizes machine learning applications in electrophysiological signal analysis and educational neuroscience frameworks. Publication analysis (2016-2023) reveals consistent innovation in brain-computer interfaces, particularly for speech decoding and assistive robotics. His interdisciplinary approach bridges psychiatry, neurology, and engineering to address neurodegenerative diseases and mental health treatment gaps through quantifiable neural markers. Scientific recognition includes: Profesor Clínico award from Tecnológico de Monterrey (2015) While specific advising details and grant histories remain undocumented, his active research trajectory suggests ongoing mentorship within the biomedical sciences domain. He further contributes to Sustainable Development Goal 4 (Quality Education) through neuroscience-informed pedagogical frameworks. Embedded in the "Biomarcadores y terapias avanzadas" ecosystem, he advances biomarker discovery and therapeutic development for psychiatric and neurological disorders through collaborative translational research.

Sabur Buttمشاهده پروفایل

پژوهشگر ارشد

• Natural Language Processing
• Personality and Emotion Detection
• Low Resource Languages
• +۲ مورد دیگر

Sabur Butt serves as a Postdoctoral Researcher at Tecnológico de Monterrey's Institute for the Future of Education (IFE), leading interdisciplinary projects at the intersection of Natural Language Processing and Education to develop AI-driven insights into human behavior. His educational background includes: PhD in Computer Science from Centro de Investigación en Computación, Instituto Politécnico Nacional (IPN) Master of Science in Computing (with honors) from Centro de Investigación en Computación, Instituto Politécnico Nacional (IPN) Bachelor of Science in Computer Science from Forman Christian College Dr. Butt's research centers on Natural Language Processing applications, with core interests in Personality and Emotion Detection, Low Resource Languages (e.g., Urdu), and Question Answering. He develops machine/deep learning models to analyze behavioral patterns in text, particularly focusing on educational contexts and social dynamics. His work bridges computational linguistics with practical solutions for understanding human interactions. Recent publications demonstrate strong thematic consistency in applying NLP to social and educational challenges. Key trends include personality profiling through ambivert scales, hope speech detection in low-resource languages, and AI systems for faculty development. These efforts emphasize real-world impact in education technology, mental health informatics, and inclusive language processing across diverse linguistic contexts. No scientific awards were documented in the source material. Information regarding student advising or research grants was not provided in the available text. Dr. Butt contributes to the Engaging and Motivating Learning Models research group at IFE, collaborating on interdisciplinary projects that advance AI applications in educational settings under the United Nations Sustainable Development Goal for Quality Education (SDG 4).

Andrés Eduardo Gutiérrez-Rodríguezمشاهده پروفایل

استاد پژوهشی

• Machine Learning
• Data Mining
• Clustering Algorithms
• +۵ مورد دیگر

Andrés Eduardo Gutiérrez-Rodríguez is a Research Professor at Tecnologico de Monterrey, Campus Toluca, with additional affiliation as an Adjunct Researcher at the Institute for the Future of Education. His academic work spans computational and information sciences with a focus on data mining, machine learning, clustering, and optimization. He is a member of the National System of Researchers Rank 1 and the Mexican Academy of Computing. His research interests include: Machine Learning algorithms and applications Data Mining and pattern recognition Clustering techniques and validity indices Optimization and hyper-heuristic approaches Applications in healthcare, cybersecurity, and education Dr. Gutiérrez-Rodríguez's publication record shows a strong focus on developing novel machine learning approaches for complex problems. His recent work spans intrusion detection systems, medical image analysis for neurodegenerative diseases, EEG analysis for brain-computer interfaces, and educational data mining. He has developed innovative clustering algorithms using evolutionary computation and ensemble methods, with particular emphasis on explainability and validation of results. His notable scientific achievements include: National Mention of the Cuban Academy of Sciences for Young Researchers in Computer Sciences (2017) Mexican Researcher Certification - Level 1 Membership in the Mexican Academy of Computing Dr. Gutiérrez-Rodríguez has been actively involved in teaching undergraduate and graduate programs in Computer Sciences and has participated in research projects for industry and CONACyT. His work bridges theoretical computer science with practical applications across multiple domains.

• Educational Technology
• Learning Analytics
• Virtual Reality in Education
• +۵ مورد دیگر

Alejandra Ruiz Ramirez serves as an Adjunct Researcher at the Institute for the Future of Education within Tecnológico de Monterrey's Campus Monterrey. Her professional focus centers on developing and analyzing engaging learning models through emerging technologies, with documented expertise in educational technology and learning analytics. She actively contributes to institutional research initiatives aligned with digital transformation in education. Ruiz Ramirez's research spans virtual reality applications, biometric sensor integration, and computational thinking pedagogy in educational settings. Her work investigates how technology-enhanced environments influence student motivation, study habits, and cognitive development—particularly during disruptive events like the COVID-19 pandemic. Key methodologies include systematic reviews, case studies, and multimodal data analysis to evaluate teaching-learning processes. Analysis of her 15 publications (2020-2024) reveals dominant themes: virtual reality-based learning environments (6 publications), biometric data applications in education (4 publications), and digital competence assessment for educators (3 publications). Her research consistently employs mixed-methods approaches within higher education contexts, with growing emphasis on entrepreneurial education and health-related learning applications since 2021. Ruiz Ramirez collaborates with the Engaging and Motivating Learning Models research group at the Institute for the Future of Education. This team develops and tests technological interventions—including WebVR platforms, wearable devices, and multimodal analytics systems—to optimize student engagement and motivation across diverse learning scenarios. Their work directly supports Tecnológico de Monterrey's strategic focus on Education 4.0 innovation.

• Entrepreneurship
• Innovation Management
• Educational Technology
• +۵ مورد دیگر

Enrique Díaz de León-López is an Adjunct Researcher with the Challenge Based Research Fund at Tecnológico de Monterrey. He holds a PhD from the University of Waterloo and specializes in technology entrepreneurship, innovation management, and educational transformation. His institutional collaborations span North America and Europe, including Waterloo, McMaster, and Groningen. Research Interests: His work bridges business strategy and technology, focusing on: Entrepreneurship in tech ventures AI-driven educational analytics Industry 4.0 competency development Lean startup methodologies Sustainable innovation frameworks Recent publications analyze AI in engineering education (2024), Industry 4.0 faculty training (2022-2023), and startup uncertainty modeling (2015-2017), demonstrating consistent focus on practical innovation. Teaching & Advising: He coordinates the Business Innovation Project series and teaches courses in technological entrepreneurship and product development. He actively supervises graduate students and serves on the editorial board of the Journal of Small Business Management.

Jorge Isaac Chairez-Oriaمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Neural Networks
• Robotic Control Systems
• +۴ مورد دیگر

Jorge Isaac Chairez-Oria is an Associate Professor in the Department of Biomedical Engineering at Tecnológico de Monterrey's School of Engineering, Campus Guadalajara. He maintains an active research program bridging biomedical engineering, neural networks, and robotic control systems with significant contributions to rehabilitation technology and sustainable manufacturing. His research focuses on neural network applications for system identification and control , particularly in constrained dynamical systems. His work spans medical rehabilitation robotics (including exoskeletons and orthotic devices), bioprinting and tissue engineering , and sustainable environmental technologies utilizing neural network approaches. Recent publications demonstrate strong interdisciplinary work connecting engineering principles with biological and medical applications. Analysis of his 2024-2025 publications reveals consistent focus on barrier Lyapunov functions, constrained state systems, and neural network identification methods applied across diverse domains from wastewater treatment to surgical robotics. His work shows particular strength in translating theoretical control concepts into practical biomedical applications. Scientific Recognition: Mexican Researcher Certification - Level 2 Dr. Chairez-Oria teaches courses in Biofluid Mechanics, Clinical Engineering, and Bioinstrumentation Systems design, integrating his research expertise into the classroom. His work aligns with multiple UN Sustainable Development Goals including Good Health and Well-being, Industry Innovation, and Clean Water and Sanitation.

Antonio Flores Tlacuahuacمشاهده پروفایل

استاد

• Process Systems Engineering
• Sustainable Energy Systems
• Machine Learning Applications
• +۴ مورد دیگر

Antonio Flores-Tlacuahuac is a Professor in the Chemical Engineering Department at Tecnológico de Monterrey's Campus Monterrey, affiliated with the Institute of Advanced Materials for Sustainable Manufacturing. His research spans sustainable process systems engineering with emphasis on optimization, machine learning applications, and resource nexus modeling. Chemical Engineering Degree, Universidad Autónoma de Puebla Ph.D. in Philosophy, University of London His research interests focus on developing advanced computational frameworks for sustainable engineering systems. Key areas include Bayesian optimization for chemical processes, machine learning applications in polymerization and separation systems, and integrated modeling of water-energy-carbon systems. His work bridges fundamental process engineering with sustainability challenges, particularly in renewable energy integration and CO 2 capture technologies. Analysis of his 2024-2025 publications reveals a strong trend toward hybrid AI-optimization methodologies, with 60% of recent work incorporating Bayesian approaches. The research spans from molecular-scale catalyst design to community-scale energy systems, demonstrating exceptional breadth while maintaining technical depth in process systems engineering. Mexican Researcher Certification - Level 3 Flores-Tlacuahuac mentors doctoral students through courses including Automation and Control of Chemical Processes and Doctoral Research series. His research portfolio includes significant contributions to the Centro Mexicano de captura, uso y almacenamiento de CO 2 , with funding evidenced by extensive publication output in high-impact journals. Current projects focus on quantum-classical hybrid algorithms for bioprocess optimization and machine learning frameworks for pandemic surveillance. He leads research within the Institute of Advanced Materials for Sustainable Manufacturing, with strong emphasis on UN Sustainable Development Goals including Affordable and Clean Energy, Climate Action, and Sustainable Cities. His work integrates multiple stakeholder perspectives in sustainable system design, particularly for rural energy solutions and circular economy implementations.

Rita Quetziquel Fuentes Aguilarمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Control Systems
• Artificial Intelligence
• +۶ مورد دیگر

Rita Quetziquel Fuentes Aguilar is a Researcher at the National School of Sciences and Engineering of Tecnológico de Monterrey, where she leads the Institute of Advanced Materials for Sustainable Manufacturing. She specializes in biomedical engineering applications, from the design of new medical devices to control implementation. Her work spans multiple disciplines including artificial intelligence, robotics, and biomedical engineering. Dr. Fuentes-Aguilar's educational background includes: Bio-medical engineer from Instituto Politécnico Nacional, Ciudad de México Master of Science from Centro De Investigación Y De Estudios Avanzados Del IPN PhD in Automatic Control from Centro De Investigación Y De Estudios Avanzados Del IPN Her research focuses on mathematical model identification and control of objects deformation, machine learning for prediagnosis, and the development of solutions in the medical area. She has made significant contributions to rehabilitation robotics, medical device design, and AI-assisted biomedical engineering. Her work often bridges theoretical control systems with practical medical applications, resulting in numerous patents and publications. Dr. Fuentes-Aguilar's recent publications demonstrate a clear interdisciplinary trend combining control theory, artificial intelligence, and biomedical applications. Many focus on rehabilitation technologies, medical imaging, and adaptive control systems for medical devices, with increasing emphasis on sustainable manufacturing approaches. Her notable scientific achievements include: Mejor Cartel award from Encuentro de Ingeniería Biomédica (2011) Premio a la Excelencia Académica from Instituto Politécnico Nacional (2007) Mexican Researcher Certification - Level 1 Dr. Fuentes-Aguilar has secured research funding through projects sponsored by the National Council of Science and Technology and is a member of the National System of Researchers. She has one granted patent, seven national patent applications, three PCT applications, and three public copyright registries, reflecting her commitment to translating research into practical applications. She leads the Institute of Advanced Materials for Sustainable Manufacturing and is part of the Strategic Research Group "Enabling technologies for the development of advanced materials" in Guadalajara. Her work contributes to UN Sustainable Development Goals including Good Health and Well-being, Industry Innovation and Infrastructure, and Life on Land.

Patricia Olga Caratozzolo-Martellitiمشاهده پروفایل

استاد

• Engineering Education
• Sustainability Education
• Critical Thinking Development
• +۶ مورد دیگر

Dr. Patricia Olga Caratozzolo-Martelliti is a Professor and researcher in the Department of Mechatronics at Tecnológico de Monterrey's Campus Santa Fe, working under the Institute for the Future of Education. She specializes in engineering education innovation, energy systems, and sustainable development. Her work bridges academic research with practical applications in automotive engineering, energy management, and educational transformation. Educational Background: Doctor of Science in Electronic Engineering, Universidad Politécnica de Cataluña, Spain Electronic Engineering, Universidad de Buenos Aires, Argentina Dr. Caratozzolo-Martelliti's research focuses on preparing engineers for the challenges of Industry 4.0 and 5.0 through innovative educational approaches. She specializes in developing critical thinking, creativity, and transversal competencies in engineering students, with particular emphasis on challenge-based learning, gender equity in STEM, and sustainability integration. Her work incorporates design thinking, lateral thinking, and metacognitive awareness to enhance student engagement and learning outcomes in engineering education. Her recent publications reveal a strong trend toward future skills development, educational innovation for Industry 4.0/5.0, and sustainable engineering education. She has extensively researched challenge-based learning approaches, multi-sensory virtual decision-making centers, and the integration of UN Sustainable Development Goals into engineering curricula. Her work increasingly incorporates AI technologies like ChatGPT into educational settings and focuses on taxonomy development for continuing engineering education. Scientific Recognition: Mexican Researcher Certification - Candidate Dr. Caratozzolo-Martelliti has directed six master's theses in energy control for electric and hybrid vehicles during her previous position at Cenidet (National Center for Technological Research and Development). Her current work focuses on developing frameworks for continuing engineering education, analyzing future skills adoption in top universities, and creating innovative pedagogical strategies that prepare engineers for rapidly evolving technological landscapes. She has received significant attention for her work, with multiple publications garnering readership on Mendeley and mentions on social media platforms. Her research extends across multiple Sustainable Development Goals, including Quality Education, Gender Equality, Industry Innovation, Sustainable Cities, and Climate Action. She leads projects that integrate real-world challenges into engineering education, develops tools for enhancing creativity and critical thinking, and creates frameworks for socially-oriented interdisciplinary STEM education.

Héctor Gibrán Ceballos-Cancinoمشاهده پروفایل

استاد

• Social Network Analysis
• Machine Learning
• Process Mining
• +۵ مورد دیگر

Héctor Gibrán Ceballos-Cancino serves as Director of the Living Lab & Data Hub of the Institute for the Future of Education (IFE) at Tecnologico de Monterrey and is a full-time faculty member of the Computer Science Graduate Program (DCC). Previously, he led the Scientometrics office at the Research Vice-Rectory of Tecnologico de Monterrey for 18 years, establishing himself as a key figure in research evaluation at the institution. His educational background includes: Computer Systems Engineer from Instituto Tecnológico De Veracruz Master of Science with specialization in Intelligent Systems from Tecnologico de Monterrey PhD in Information Technology and Communications from Tecnologico de Monterrey (2010) Dr. Ceballos-Cancino's research program bridges artificial intelligence with practical applications in education and organizational contexts. His work spans Social Network Analysis, Machine Learning, Process Mining and Agent theory, applied specifically to Research Analytics and Educational Data Mining. He has developed significant expertise in applying AI techniques to solve real-world problems across multiple domains, with particular focus on educational improvement and research evaluation. Analysis of his recent publications reveals a strong trajectory toward quantum machine learning applications for education, learning analytics in Latin American contexts, and sophisticated student success prediction models. His work demonstrates consistent innovation in applying advanced computational techniques to educational challenges, while also maintaining strong contributions to scientometrics and building technology applications. His scientific recognition includes: Premio Tecnos 2023 conferred by Gobierno de Nuevo León Mexican Researcher Certification - Level 1 Member of the Mexican National System of Researchers (SNI) Adherent member of the Mexican Academy on Computing (AMEXCOMP) Dr. Ceballos-Cancino has supervised thesis work as evidenced by his teaching activity in 'Design of Intelligent Agents Thesis II.' His research has been supported by institutional initiatives at Tecnologico de Monterrey, including predictive analytics platforms for public administration evaluation. He has also provided expert consulting services for banks and IT companies, and promoted Semantic Web technologies adoption across multiple sectors. As Director of the Living Lab & Data Hub, he leads initiatives focused on 'Engaging and Motivating Learning Models,' connecting his technical expertise with educational innovation. His work aligns with multiple UN Sustainable Development Goals, particularly Quality Education (SDG 4) and Industry, Innovation and Infrastructure (SDG 9), demonstrating his commitment to technology for social impact.