Department:Computer Science and Information Engineering
University:Chaoyang University of Technology
Chin-Ling Chen was born in Taiwan in 1961. He received a B.S. degree in Computer Science and Engineering from Feng Cha University in 1991; the M.S. degree and Ph.D. in Applied Mathematics at National Chung Hsing University, Taichung, He is a member of the Chinese Association for Information Security and Taiwanese Association for Consumer Electronics. From 1979 to 2005, he was a senior engineer at Chunghwa Telecom Co., Ltd. He is currently a distinguished professor of the Department of Computer Science and Information Engineering at Chaoyang University of Technology, Taiwan.
He also got the honor of Jilin Changbai Mountain Scholars (China) of Changchun Sci-Tech University and Fujian Minjiang Scholar (China) of Xiamen University of Technology. His research interests include Authentication Mechanism,We b Service, M-Commerce, E-Commerce, Digital Signature, Radio Frequency Identification (RFID),Wireless Sensor , Network,Vehicular Ad Hoc Networks (VANET), Ad Hoc Networks, Home Network, Medical Safety Service and Digital Right Management security issues etc. Dr. Chen had published over 90 articles on the above research fields in SCI/SSCI international journals. And he also got 10 Taiwan patents. From 2006 to 2015, he got the reward of the distinguished researcher every year at Chaoyang University of Technology. From 2010 to 2018, he had been invited to review over 240 SCI/ SSI Journal articles.
Computer Science and Information Engineering, Authentication Mechanism,We b Service, M-Commerce, E-Commerce, Digital Signature, Radio Frequency Identification (RFID),Wireless Sensor , Network,Vehicular Ad Hoc Networks (VANET), Ad Hoc Networks, Home Network, Medical Safety Service and Digital Right Management security issues etc.
Department:Sustainable and Renewable Energy Engineering
University:University of Sharjah
Country:United Arab Emirates
Mamdouh EL Haj Assad Associate professor College of Engineering | Sustainable & Renewable Energy Engineering Department Address: University of Sharjah, Department of Sustainable and Renewable Energy Engineering, P. O. Box 27272, United Arab Emirates EDUCATION 1990: B. Sc. in Mechanical Engineering Middle East Technical University, Ankara, Turkey
1992: M. Sc. in Nuclear Engineering Middle East Technical University, Ankara, Turkey 1998: Ph.D. in Mechanical Engineering Helsinki University of Technology, Helsinki, Finland Major subject: Thermal Engineering, minor subject: Power Plant Engineering COURSES TAUGHT 1- Classical thermodynamics 2- Chemical thermodynamics 3- Technical thermodynamics 4- Irreversible thermodynamics 5- Heat transfer 6- Mass transfer 7- Fluid mechanics 8- Geothermal energy systems 9- Solar energy systems 10- Statics and dynamics 11- Engineering management 12- Maintenance 13- Wind energy Lab 14- Heat transfer Lab 15- Energy storage Lab 16- Workshop for mechanical engineers
Geothermal energy, applications of renewable energy in industry, absorption chillers, heat exchangers, artificial neural network analysis of renewable energy systems. RESEARCH INTERESTS Renewable energy systems, energy efficiency, energy and exergy analysis, evaporative cooling, energy conversion systems, and industrial ventilation. COMPUTER SKILLS Microsoft Office, Origin, COMSOL, Maple and Matlab.
Geothermal energy, applications of renewable energy in industry, absorption chillers, heat exchangers, artificial neural network analysis of renewable energy systems.
Renewable energy systems, energy efficiency, energy and exergy analysis, evaporative cooling, energy conversion systems, and industrial ventilation.
Chaoqun Yue is currently a Ph.D. student in the Computer Science & Engineering Department at the University of Connecticut. He received his B.S. degree in Software Engineering from Xi’an Jiaotong University, China in 2011, and M.S. degree in Computer Science from Shanghai Jiao Tong University, China in 2014. His research interests are in the areas of wireless networks and wireless sensing applications.
Areas of wireless networks and wireless sensing applications
Dariusz Jacek Jakóbczak was born in Koszalin, Poland, on December 30, 1965. He graduated in mathematics (numerical methods and programming) from the University of Gdansk, Poland in 1990. He received the Ph.D. degree in 2007 in computer science from the Polish – Japanese Institute of Information Technology, Warsaw, Poland. From 1991 to 1994 he was a civilian programmer in the High Military School in Koszalin. He was a teacher of mathematics and computer science in the Private Economic School in Koszalin from 1995 to 1999.
Since March 1998 he has worked in the Department of Electronics and Computer Science, Koszalin University of Technology, Poland, and since October 2007 he has been an Assistant Professor in the Chair of Computer Science and Management in this department. His research interests connect mathematics with computer science and include computer vision, artificial intelligence, shape representation, curve interpolation, contour reconstruction, and geometric modeling, numerical methods, probabilistic methods, game theory, operational research, and discrete mathematics.
Computer Science and Management, His research interests connect mathematics with computer science and include computer vision, artificial intelligence, shape representation, curve interpolation, contour reconstruction, and geometric modeling, numerical methods, probabilistic methods, game theory, operational research, and discrete mathematics.
Department:Medical and Biological Cybernetics, Pediatrics & Child Surgery
University:Federal Research Center “Computer Science and Control” of Russian Academy of Science
Boris A. Kobrinskii, PhD., professor was born in 1944 in Moscow (Russia). In 1970 he graduated from the 2nd Moscow State Pirogov Medical Institute (now N.I. Pirogov Russian National Research Medical University (Moscow, Russia), in 1987 – Department of Medical and Biological Cybernetics of Moscow Institute (now the Technical University) of Radioengineering, Electronic and Automation. In 1973 began to apply computer science in medical diagnostic. In 1975 – 2015 worked in the Moscow Research Institute for Pediatrics and Children's Surgery (Russia), since 1983 head the new information technologies center.
Currently working head of the clinical decision support systems laboratory of Problem Artificial Intelligence Institute of Federal Research Center “Computer Science and Control” of Russian Academy Science. In 1989 – 1996 he taught computer science in medicine in the department of health and social problems of maternal and child health of the Central Institute for Postgraduate Doctors (later the Russian Medical Academy Postgraduate Education), since 2007 professor of Medical Cybernetics and Informatics departments of Pirogov Russian National Research Medical University.
The scientific works of prof. BA Kobrinskii contributed significantly to solving the problems of medical cybernetics and informatics for clinical genetics and monitoring the health of children. As a result of research at the crossroads of pediatrics and informatics created a new scientific direction for a comprehensive dynamic analysis of child health in the process of monitoring computer. He moved the concept of the continuum – transition states of the developing organism and proposed its implementation on the basis a single information, medical and social space using complex mathematical methods and models. The proposed approach was the development of the doctrine of the predisposition to disease. Under the guidance and with his participation created: computer system of medical examination of the child population DIDENAS, Russia's first computer genetic register (1990), the first domestic expert system for the diagnosis of hereditary diseases children DIAGEN. In 1999 organized a Russian computer monitoring of congenital malformations.
In 2002 carried out the development and implemented at all levels of health care software system. Formed a federal database that includes information about the health of nearly 30 million children. Since that time, monitoring permits to obtain new information about the features of the prevalence of diseases and their dynamics, the effectiveness of interventions. In 2001 under his leadership and active personal participation was implemented first national disaster telemedicine system and organized regular teleconsultation support field hospital physicians. The main directions of research is the development of theoretical and applied aspects of the development of Intelligent decision support systems (knowledge engineering, argumentation, fuzzy logic). Under his leadership, made 6 doctoral and 13 master's theses. He is the author/co-author of over 300 articles, 11 monographs, reference book, 3 textbooks.
Engineering, argumentation, fuzzy logic, Artificial Intelligence, Computer Science and Control, Pediatrics & Child Surgery
Dr. Enrique Arribas Full professor Applied Physics Department University of de Castilla-La Mancha Avenida de España s/n 02071 ALBACETE (Spain) Research fields: Radiofrequency waves Science Education Active Learning Physics Unstable Systems Mathematical and Computer Physics and Chemistry Nonlinear Systems.
Unstable Enzymatic Systems
Mathematical and Computer Chemistry
2007 Ph.D., Chemical Physics, University of Castilla-La Mancha, Spain
1978 M.Sc., Theoretical Physics, University of Valencia, Spain
Skills and Expertise
Teaching and Learning Enzymes Kinetics Analysis Data Analysis Education Science Physical Chemistry Theoretical Physics Biochemistry Higher Education
Radiofrequency waves Physics Education Active Learning Physics Unstable Systems Mathematical and Computer Physics and Chemistry Nonlinear Systems
GEORGE Olawunmi, Graduate Teaching/Research Assistant, Computer Science, Marquette University, Milwaukee, USA. A distinguished software engineer and machine learning researcher with proven skills in core programming languages such as Java, Python, R, PHP, and a number of other well-known languages.
Passionate about AI and voraciously researching with ML tools. Enthusiastic and ever-actively seeking to provide machine-intelligent solutions to problems in any area of life endeavor, particularly in computer vision and the Brain-Computer Interfaces field. Skilled with the knowledge and practical use of ML frameworks such as Keras, FB prophet, and Tensorflow. Worked on personal, research, and industry projects with a core understanding of the model and business requirements and the ability to come up with metrics depending on the business need.
Ph.D. in Computer Science, Expected 2021 Marquette University, Milwaukee, Wisconsin. Research Area & Interests: Machine learning, Deep learning, Big data, and Data Analytics, Brain-Computer Interfaces, Blockchain. Courses: Business Analytics, Advanced databases, Elements of software engineering, Machine learning, Parallel & distributed programming, Business Intelligence, Cybersecurity, Chaotic Signal Processing, Advanced Machine Learning. Research: Researching in mental health, with the use of mobile apps and machine learning techniques, to reduce the suicide rate amongst US army veterans.
Motor imagery-based Brain-Computer Interfaces (BCI) and covert attention-based BCIs. The use of techniques, such as machine learning to classify motor imagery and predict the focus of attention for communication. BSc. in Computer Engineering, Dec 2011 Obafemi Awolowo University, Ile-Ife, Nigeria. 2 nd class Upper Division Courses: Object-oriented programming, Data structures, Statistics for engineers, Databases.
Built a Billing Data Aggregator iOS app, using Swift, for creation of invoices, payment of a due amount, and viewing other client information. ? Added features needed to the company’s legacy validation apps for organizations including MasterCard and the Nigerian Postal Service. The Android validation apps were used to verify POS terminals in Nigeria. ? Further developed the incomplete Trips.ng mobile app for launch. The app was built for handling corporate bookings of flights, hotels, and cabs. Researched data science tools and techniques, preliminary use of the ELK stack; setting up of last alerts, to monitor incoming data.
Machine learning, Deep learning, Big data, and Data Analytics, Brain-Computer Interfaces, Blockchain