Prof. Xabier Basogain Olabe

University of the Basque Country, Spain

Doctor of Telecommunication Engineering. Member of the Systems Engineering and Automation Department of the School of Engineering of Bilbao, Spain.

Prof. Basogain has taught courses in digital systems, microprocessors, digital control, modeling and simulation of discrete events, artificial neural networks, machine learning, virtual and augmented reality, and collaborative tools in education.

Prof. Basogain and his research group are active participants in the field of soft computing and cognitive sciences applied to STEAM (Science, Technology, Engineering, Arts and Mathematics), and the field of learning and teaching technologies applied to online education, including the following areas: a) the design of multimedia content for primary, secondary and college level courses; b) the development of pedagogical methodologies for new digital learning environments; c) the creation and use of technological-based tools applied to teaching and learning.

During the last two decades, Prof. Basogain and his research group have received the support of the Basque government, European Union and the National Council for Science and Technology of Latin-American through the funding of a large number of research and development projects.

Prof. Basogain has published several books and multiple articles in international journals, and has collaborated with international journals and committees. He has established working relationships with members of the MIT Lifelong Kindergarten group and with members of the One Laptop per Child project (OLCP) in the US and in multiple countries of Latin America.

He has established relationships with governmental educational groups of the Ministries of Education of Peru, the Dominican Republic, and Colombia, as well as the educational networks RENATA of Colombia and CONACyT of Paraguay, and research groups at the University of Alicante, University of Extremadura, and University of Salamanca (Spain), Luisíada University (Portugal), University of Silesia (Poland) and LaSalle Bajío University (Mexico).

  • Keynote Speech Abstract

    Speech Title: Fostering STEAM Education Using Computers and Information Technologies

    Abstract: The academic world is witnessing the new opportunities offered by information and computer technologies for STEAM education (Science, Technology, Engineering, Arts and Mathematics). These STEAM subjects, studied in integrated form, are considered essential in the education of citizens of a modern society.

    This talk addresses the development and support of STEAM education that our research team has carried out in recent years in different educational environments that include engineering studies, training of future teachers, primary and secondary education, and outreach to society. We will describe a set of activities that promote STEAM education, including courses (face-to-face courses, online courses, and MOOC courses), and scientific and informative conferences.

    We make use a set of applications of information and computing technologies in the creation and delivery of courses and conferences that include programming languages (ie Matlab, WolframAlpha-Computational Intelligent, Snap and Scratch), learning platforms (Moodle, MiriadaX), resources / tools to interact with the student (motivate face-to-face sessions, video conferences and online tutorials, remote desktops, and website portals, among other resources).

    This talk presents real cases carried out in university educational centers, and in primary and secondary schools. These are examples that show cases of integration of computer science, engineering and education in which information and computer technologies are used to promote STEAM education.


Prof. Jin Wang

Valdosta State University, USA

Dr. Jin Wang is a Professor of Operations Research and a Director of the Data Science Center at Valdosta State University, USA. He received his Ph.D. degree from the School of Industrial Engineering at Purdue University in 1994. His research interests include Data Mining, Machine Learning, Big Data, Modeling and Optimization, Supply Chain, Portfolio Management, Computer Simulation, and Applied Statistics. He has more than 30 years collegiate teaching experience at Purdue University, Florida State University, Auburn University, and Valdosta State University. Dr. Wang has been active in professional research activities. He has authored or co-authored many research papers in the referred journals and conference proceedings. He was invited as keynote speakers and the conference chairs for many Data Science, Big Data, Management Science, and Education conferences. He is an editor-in-chief and department editor of the research journals. He has participated as a principal investigator or co-principal investigator in several research projects funded by federal or industrial agencies, including the National Science Foundation, General Motors, and the National Science Foundation of China. He was invited as a panel member at the National Science Foundation Workshop. Dr. Wang also served as a consultant for financial firms. His analytical mixture of normal method for simulating market data and the two-stage portfolio optimization algorithm have made a great impact in both academic field and finance industry.

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Prof. Yu-Dong Zhang

University of Leicester, UK

Prof. Yu-Dong Zhang received his PhD degree from Southeast University in 2010. He worked as a postdoc from 2010 to 2012 in Columbia University, USA, and as an assistant research scientist from 2012 to 2013 at Research Foundation of Mental Hygiene (RFMH), USA. He served as a full professor from 2013 to 2017 in Nanjing Normal University, where he was the director and founder of Advanced Medical Image Processing Group in NJNU. Now he serves as Professor in Department of Informatics, University of Leicester, UK. He was included in “Most Cited Chinese researchers (Computer Science)” by Elsevier from 2014 to 2018. He was the 2019 recipient of “Highly Cited Researcher” by Web of Science. He won “Emerald Citation of Excellence 2017” and “MDPI Top 10 Most Cited Papers 2015”. He was included in "Top Scientist" in Guide2Research. He published over 160 papers, including 16 “ESI Highly Cited Papers”, and 2 “ESI Hot Papers”. His citation reached 10508 in Google Scholar, and 5634 in Web of Science. He is the fellow of IET (FIET), and the senior members of IEEE and ACM.

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