Key Notes and Speakers

Prof. dr. Wolfram Hardt

Prof. Dr. Wolfram Hardt is Professor for Computer Engineering and Dean of the Faculty for Computer Science at the Chemnitz University of Technology. He received the German Diploma degree (Equal to M.Sc.) in Computer Science and Ph.D. degree from the University of Paderborn. In 1996 Hardt joined C-LAB - Cooperative Computing & Communication Laboratory and word on new technologies for high performance controllers and he submitted his habilitation thesis on asynchronous architectures for embedded systems.

In 2003 Prof. Hardt became Chair of Computer Engineering Dept. at the Chemnitz University of technology. Furthermore, since 2006 until 2013 he was Dean of Faculty for Computer Science. Currently he is again Dean of Faculty of Computer Science. Since 2006 he is the Director of the University Computing Centre at the Chemnitz University of Technology. He is the editor of a scientific book series about self-organizing embedded systems and has published more than 100 papers, graduated 15 PhDs and supervises over 50 master thesis per year. Prof. Hardt is member of the Association for Electrical, Electronic and Information Technologies (VDI/VDE), the Association for Computer Science (GI) and the Association for Computing Machinery. He is committee member of several conferences on design methodology for embedded systems.

His research interests include Hardware/Software Codesign, Self-organizing Systems and Robust Embedded Systems. Research results are applied to automotive systems and avionics. Prof. Hardt's lab runs complex demonstrators, e.g. Car2X applications are implemented on AUTOSAR based controllers and test methods for driver assistance functions are developed. For avionic systems adaptive flight control applications are in the research focus. Methods for high performance image processing are developed to detect flight targets, e.g. landing lane or objects subject to inspection. Implementations are tested and demonstrated on multicopter drone platforms.

Digitalisation and Industry 4.0

(TO BE PREPARED...)

 


 

Assoc. prof. dr. Seifedine Kadry

Seifedine Kadry, PhD, is currently Associate Professor at Beirut Arab University, Faculty of Sciences, Beirut, Lebanon. He worked as Head of Software Support and Analysis Unit of First National Bank where he designed and implemented the data warehouse and business intelligence; he has published several books in Elsevier, Springer, CRC and other publishers. He is the author of more than 200 papers and 10 books on applied math, computer science, and stochastic systems in peer-reviewed journals. He has Bachelor degree in computer science from the Lebanese university, MS degree in computation form EPFL – Lausanne, and received a PhD in computational and applied mathematics in 2007 from the Blaise Pascal University (Clermont-II) - Clermont-Ferrand in France. In 2017, he defended his habilitation thesis in the Rouen University, France. He is IEEE distinguish speaker, IET Fellow, IETE Fellow, IACSIT Fellow, Google certified Educator and Microsoft Innovation Educator. He is ABET program evaluator, ACBSP program reviewer and FIBAA expert. At present his research focuses on smart learning in smart cities, social network analysis, and E-systems.

Big Data and Smart Cities

Smarter cities are turning big data into insight. Smart cities face serious challenges prior to widespread acceptance, but the expansion of big data and the evolution of Internet of Things (IoT) technologies and other technologies to solve contemporary urban issues should eventually lead to their adoption and have played an important role in the feasibility of smart city initiatives. In this talk, we will discuss the latest research and practice in how big data analytics support smart cities and identify business and technological research challenges.

 

Prof. dr. Patrick S. P. Wang

Prof. Patrick S.P. Wang, PhD. Fellow, IAPR, ISIBM, WASE, and IEEE & ISIBM Outstanding Achievement Awardee, is Tenured Full Professor, Northeastern University, USA, Adjunct Faculty at Harvard University and MIT, iCORE (Informatics Circle of Research Excellence) Visiting Professor, University of Calgary, Canada, Otto-Von-Guericke Distinguished Guest Professor, Magdeburg University, Germany, Zijiang Visiting Chair, ECNU, Shanghai, China, as well as honorary advisory professor of several key universities in China, including Sichuan University, Xiamen University, East China Normal University, Shanghai, and Guangxi Normal University, Guilin, China. 
Prof. Wang received his BSEE from National Chiao Tung University (Jiaotong University), MSEE from National Taiwan University, MSICS from Georgia Institute of Technology, and PhD, Computer Science from Oregon State University. Dr. Wang has published over 26 books, 200 technical papers, 3 USA/European Patents, in PR/AI/TV/Cybernetics/Imaging, and is currently founding Editor-in-Chief of IJPRAI(International Journal of Pattern Recognition and Artificial Intelligence), and Book Series of MPAI, WSP. In addition to his technical interests, Dr. Wang also published a prose book, “HarvardMeditation Melody”, “Cambridge Rhapsody” and many articles and poems regarding Du Fu and Li Bai’s poems, Beethoven, Brahms, Mozart andTchaikovsky’s symphonies, and Bizet, Verdi, Puccini and Rossini’s operas.

AI & PR and Applications for Greener and Safer World

This talk is concerned with fundamental aspects of Intelligent Pattern Recognition (IPR) andapplications. It basically includes the following: Basic Concept of Automata, Grammars, Trees,Graphs and Languages. Ambiguity and its Importance, Brief Overview of Artificial Intelligence(AI), Brief Overview of Pattern Recognition (PR), What is Intelligent Pattern Recognition (IPR)? Interactive Pattern Recognition Concept, Importance of Measurement and Ambiguity, How it works, Modeling and Simulation, Basic Principles and Applications to Computer Vision, Security, Road Sign Design, Safer Traffic and Robot Driving with Vision, Ambiguous (Dangerous and Bad) design of Road Signs vs Unambiguous (Good) Road Signs, How to Disambiguate an Ambiguous Road Sign? What is Big Data? and more Examples and Applications of Learning and GreenerWorld using Computer Vision. Finally, some future research directions are discussed.

Assoc. prof. dr. Eric T. Matson

Eric T. Matson, Ph.D., is an Associate Professor in the Department of Computer and Information Technology in the at Purdue University, West Lafayette. He is a Purdue University Faculty Scholar and member of the Board on Army Science and Technology for the National Academies of Science, Medicine and Engineering. Prof. Matson was an International Faculty Scholar in the Department of Electrical Engineering at Kyung Hee University, Yongin City, Korea. He was also formerly a Visiting Professor with the LISSI, University of Paris Est, Paris, France, Visiting Professor, Department of Computer Science and Engineering, Dongguk University, Seoul, South Korea and in the School of Informatics at Incheon National University in Incheon, South Korea. He is the Director of the Robotic Innovation, Commercialization and Education (RICE) Research Center, Director of the Korean Software Square at Purdue and the co-founder of the M2M Lab at Purdue University, which performs research at the areas of multiagent systems, cooperative robotics and wireless communication. The application areas are focused on safety and security robotics and agricultural robotics and systems.

Prior to his position at Purdue University, Prof. Matson was in industrial and commercial software development where he developed and lead numerous large software engineering projects dealing with intelligent systems, applied artificial intelligence,  distributed object technologies, enterprise resource planning and product data management implementations.  Prof. Matson has a Ph.D. in Computer Science and Engineering from the University of Cincinnati, M.B.A in Operations Management from Ohio State University and B.S. and M.S.E. degrees in Computer Science from Kansas State University.

Development of Self-organizing Counter Autonomous Systems with the HARMS Integration Model 

The future in the enhancement of cyber-physical system and robotic functionalities lies not only in the mechanical and electronic improvement of the robots’ sensors, mobility, stability and kinematics, but also, if not mostly, in their ability to connect to other actors (human, agents, robots, machines, and sensors HARMS). The capability to communicate openly, to coordinate their goals, to optimize the division of labor, to share their intelligence, to be fully aware of the entire situation, and thus to optimize their fully coordinated actions will be necessary. Additionally, the ability for two actors to work together without preference for any specific type of actor, but simply from necessity of capability, is provided by a requirement of indistiguishability, similar to the discernment feature of rough sets.

Once all of these actors can effectively communicate, they can take on group rational decision making, such as choosing which action to take that optimizes a group’s effectiveness or utility. Given group decision making, optimized capability-based organization can take place to enable human-like organizational behavior. Similar to human organizations, artificial collections with the capability to organize will exhibit emergent normative behavior. In this session, we will show how these models are applied to real world problems in security, first response, defense and agriculture.