I am Full-Time Researcher
I am Full-Time Researcher
Giner Alor-Hernandez is a full-time researcher of the Division of Research and Postgraduate Studies in Orizaba’s technological institute: Tecnológico de Orizaba. He received a MSc and a PhD in Computer Science from the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV), Mexico. He has led 10 Mexican research projects granted by CONACYT, DGEST and PRODEP.
He is author/coauthor of around 250 journal and conference papers on computer science. Also, he has been a committee program member of around 60 international conferences sponsored by IEEE, ACM, and Springer. He also holds the position of editorial board member of eight indexed journals; he has been guest editor of JCR-indexed journals such as Scientific Programming, Journal of Telematics & Informatics, Mobile Information Systems, Computer Science & Information Systems, Journal of Universal Computer Science, Pervasive and Mobile Computing, Journal of Educational Technology & Society, Science of Computer Programming Journal, International Journal of Software Engineering and Knowledge Engineering, Computational and Mathematical, Methods in Medicine y Journal of Medical Systems. He is the main author of the book entitled Frameworks, Methodologies, and Tools for Developing Rich Internet Applications, published by IGI Global Publishing. He has been editor of the following books: New Perspectives on Enterprise Decision-Making Applying Artificial Intelligence Techniques; Techniques, Tools and Methodologies Applied to Global Supply Chain Ecosystems; Current Trends on Knowledge-Based Systems; Exploring Intelligent Decision Support Systems: Current State and New Trends; Managing Innovation in Highly Restrictive Environments: Lessons from Latin America and Emerging Markets; New Perspectives on Applied Industrial Tools and Techniques; published by Springer Verlag, Handbook of Research on Managerial Strategies for Achieving Optimal Performance in Industrial Processes, published by IGI Global Publishing.
He has given 40 magistral conferences and workshops on Information Technology. He has 29 copyrights and 4 international patents. He has supervised 25 bachelor theses, 35 master theses and 8 Ph.D. theses. His research interests include Semantic Web, Intelligent Systems, Big Data, Internet of Things and Sofware Engineering. He is IEEE Senior Member and ACM Senior member. He is a regular member of the Artificial Intelligence Mexican Society, Computing Mexican Academy and Mexican Society of Computing Science. He is a National Researcher recognized with Level 2 by the National Council of Science & Technology of Mexico (CONACYT). His H-index is 16 in Scopus with more than 1,140 cites. ORCID: 0000-0003-3296-0981, Scopus Author ID: 17433252100, Web of Science ResearcherID: U-9203-2017.
EDUCATION
Ph.D. in Computer Science, Center for Research and Advanced Studies (CINVESTAV),
México, D.F., México.
December 2005
Master of Science in Computer Science, Center for Research and Advanced Studies (CINVESTAV),
México, D.F., México.
September 2001
Bachelor in Computer Science, Facultad de Ciencias de la Computación
Benemérita Universidad Autónoma de Puebla,
Puebla, México
November 1999
The Semantic Web is a mesh of data that are associated in such a way that they can easily be processed by machines instead of human operators. It can be conceived as an extended version of the existing World Wide Web, and it represents an effective means of data representation in the form of a globally linked database. By supporting the inclusion of semantic content in Web pages, the Semantic Web targets the conversion of the presently available Web of unstructured documents to a Web of information/data. The term Semantic Web was coined by Tim Berners-Lee.
Intelligent System (IS) can be defined as the system that incorporates intelligence into applications being handled by machines. Intelligent systems perform search and optimization along with learning capabilities. Different types of machine learning such as supervised, unsupervised and reinforcement learning can be modeled in designing intelligent systems. Intelligent systems also perform complex automated tasks which are not possible by traditional computing paradigm. Various diagnostic, robotics and engineering systems are results of intelligent procedures implemented in Intelligent System Design.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
The internet of things (IoT) is a computing concept that describes the idea of everyday physical objects being connected to the internet and being able to identify themselves to other devices. The term is closely identified with RFID as the method of communication, although it also may include other sensor technologies, wireless technologies or QR codes.
Knowledge-based software engineering is focused in automating the software engineering life cycle, software engineering resources which are shifting towards knowledge acquisition and the automated reuse of expert knowledge for developing software artifacts. Knowledge in software applications is becoming more significant because the domains of many software applications are inherently knowledge-intensive and this knowledge is often not explicitly dealt with in software development.
Machine learning is an artificial intelligence (AI) discipline geared toward the technological development of human knowledge. Machine learning allows computers to handle new situations via analysis, self-training, observation and experience. Machine learning facilitates the continuous advancement of computing through exposure to new scenarios, testing and adaptation, while employing pattern and trend detection for improved decisions in subsequent (though not identical) situations. Machine learning is often confused with data mining and knowledge discovery in databases (KDD), which share a similar methodology.
ACM is widely recognized as the premier membership organization for computing professionals, delivering resources that advance computing as a science and a profession; enable professional development; and promote policies and research that benefit society.
Association for Computing Machinery (6089916).
The Mexican Society of Computer Science A.C. is a scientific society that seeks academic excellence and is committed to research and teaching. The association is made up of various researchers, residents in different cities of the country, who seek to promote research and development activities in Computer Science in Mexico.
Computer Science Mexican Society (030).
ResearcherID is a freely available resource for the global, multi-disciplinary scholarly research community. After registering, you are assigned an individual ID number that stays with you over the course of your career, regardless of name changes or change in institution affiliation.
Web of Science ResearcherID: U-9203-2017.
