The 3G and 4G mobile communications had been developed for many years. The 5G mobile communication is scheduled to be launched in 2020. In the future, a wireless network is of various size of cells and different type of communication technologies, forming a special architecture of Heterogeneous Networks (HetNet). Under the complex network architecture, interference and handover problems are critical challenges in access network. How to efficiently manage small cells and to choose an adequate access mechanism for the better quality of service is a vital research issue. Traditional network architecture can no longer support existing network requirements. It is necessary to develop a novel network architecture. Therefore, this keynote speech will share a solution of deep learning-based B5G mobile network which can enhance and improve communication performance through combing some specific technologies. e.g., deep learning, fog computing, cloud computing, cloud radio access network (C-RAN) and fog radio access network (F-RAN).


Han-Chieh Chao received his M.S. and Ph.D. degrees in Electrical Engineering from Purdue University, West Lafayette, Indiana, in 1989 and 1993, respectively. He is currently a professor with the Department of Electrical Engineering, National Dong Hwa University, where he also serves as president. He is also with the Department of Computer Science and Information Engineering and the Department of Electronic Engineering, National Ilan University, Taiwan; College of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, China, and Fujian University of Technology, Fuzhou, China.  He was the Director of the Computer Center for Ministry of Education Taiwan from September 2008 to July 2010. His research interests include IPv6, Cross-Layer Design, Cloud Computing, IoT, and 5G Mobile Networks. He has authored or co-authored 4 books and has published about 400 refereed professional research papers. He has completed more than 150 MSEE thesis students and 11 Ph.D. students. Dr. Chao has been invited frequently to give talks at national and international conferences and research organizations. He serves as the Editor-in-Chief for the Institution of Engineering and Technology Networks, the Journal of Internet Technology, the International Journal of Internet Protocol Technology, and the International Journal of Ad Hoc and Ubiquitous Computing. He is a Fellow of IET (IEE) and a Chartered Fellow of the British Computer Society. Due to Dr. Chao’s contribution of suburban ICT education, he has been awarded the US President's Lifetime Achievement Award and International Albert Schweitzer Foundation Human Contribution Award in 2016.

Prof. Han-Chieh Chao

President National Dong Hwa University, Taiwan


  • Department of Electrical Engineering, National Dong Hwa University, Halien, Taiwan

  • Department of Computer Science and Information Engineering and the Department of Electronic Engineering, National Ilan University, I-Lan, Taiwan


Keynote title: Deep Learning Platform for B5G Mobile Network



It has been a dream to have robots that can perform services for the well-being of humans. There are many key challenges, that need to be addressed, in order to make the dream comes true. The challenges include 1) generating multiple functions (like, locomotion, obstacle avoidance, and navigation) for the robots, 2) implementing learning ability that allows the robots to adapt to unexpected and complex situations, and 3) creating a natural, timely, and smooth human‐robot interactions. In this talk, I will introduce our bio-inspired artificial intelligence approach to deal with the challenges. Additionally, I will present our ongoing projects that employ the approach to develop our service robots for inspection, disabled people assistance, and elderly care.



Dr. Poramate Manoonpong received his Ph.D. in Electrical Engineering and Computer Science from the University of Siegen, Germany, in 2006. He currently holds several positions including an Associate Professor of Embodied AI & Robotics at the University of Southern Denmark (SDU), Denmark and a Professor of School of Information Science & Technology at Vidyasirimedhi Institute of Science & Technology (VISTEC), Thailand. In 2017, he was elected in Young 1000 Talents of China and appointed as a Professor of Neuro-Robotic Technology at Nanjing University of Aeronautics and Astronautics (NUAA). He is also a co-PI of Bio-inspired Robotics and Neural engineering (BRAIN) lab at VISTEC and Embodied AI & Neurorobotics Lab at SDU.


His central research agenda is “to understand how neural mechanisms and biomechanics can be realized in artificial agents (like biologically-inspired robots) so they can become more like living creatures in their level of performance". According to this, his team has developed bio-inspired behaving systems with general neural control architectures and could show that these agents can acquire complex behaviors with learning and adaptation (resulting in high level contribution to Nature Physics). Additionally, his team also focuses on transferring biomechanical and neural developments of robots to other applications, like brain-machine interface, human-machine interaction, and exoskeleton and orthosis control. He has been PI or co-PI of 13 funded projects. Currently he serves on an Associate Editor of Frontiers in Neuroscience (Neurorobotics) and the editorial board of International Journal of Advanced Robotic Systems (ARS), (Topic: Bioinspired Robotics) and Advances in Robotics Research, Techno press.


His research interests include embodied artificial intelligence, machine learning for robotics, bio-inspired robotics, biomechanics, neural locomotion control, neurodynamics, learning/plasticity, embodied cognitive robotics, lower-limb active orthosis and exoskeleton control, brain-machine interface, and human-machine interaction, and service robotics.

Poramate Manoonpong

Keynote title: Bio-inspired Artificial Intelligence for Service Robots


How Microsoft and Commercial Software Engineering are using research, open source software and the Azure cloud to help scientists further their understanding of our natural world.


- Microsoft 5 years 7 months Machine Learning Engineer, Commercial Software Engineering September 2017 - Present 

I architect and code scalable machine learning pipelines for fast and slow data from edge to cloud and conduct bespoke machine learning analysis.

- Premier Field Engineer, Microsoft Services May 2013 - September 2017 (4 years 5 months) Helping enterprise solution delivery teams deliver intelligent, secure and scalable hybrid applications.


Steve van Bodegraven

Machine Learning Engineer at Microsoft Darwin, Northern Territory, Australia


Keynote title: AI and the Natural World – From Research to AI Apps using the Azure Cloud



The Wiener index was first proposed in chemistry for characterizing molecular structures based on the count of path distances between carbon atoms. Latter, it was defined in graph theory as follows. The Wiener index of a graph is the sum of all pairwise distances of vertices of the graph. In this talk, we consider the Wiener index spanning tree problem. Given a graph G, the maximum (minimum) Wiener index spanning tree problem on G is to find a spanning tree T of G such that the Wiener index of T is the maximum (minimum) among all possible spanning trees of G. Recently, it has been shown that the minimum Wiener index spanning tree of a wireless sensor network is better than its minimum spanning tree while considering the routing issue. In this talk, we consider the algorithmic results for the Wiener index spanning tree problem.


Sheng-Lung Peng is a full Professor of the Department of Computer Science and Information Engineering at National Dong Hwa University, Taiwan. He received the BS degree in Mathematics from National Tsing Hua University, and the MS and PhD degrees in Computer Science and Information Engineering from the National Chung Cheng University and National Tsing Hua University, Taiwan, respectively. His research interests are in designing and analyzing algorithms for Bioinformatics, Combinatorics, Data Mining, and Networks.


Dr. Peng has edited several special issues for journals, such as Soft Computing, Journal of Internet Technology, Journal of Computers and MDPI Algorithms. He is also a reviewer for many journals such as IEEE Transactions on Emerging Topics in Computing, Theoretical Computer Science, Journal of Computer and System Sciences, Journal of Combinatorial Optimization, Journal of Modelling in Management, Soft Computing, Information Processing Letters, Discrete Mathematics, Discrete Applied Mathematics, Discussiones Mathematicae Graph Theory, and so on. He published more than 100 international conferences and journal papers.


Dr. Peng is now the Dean of the Library and Information Services Office of NDHU, an honorary Professor of Beijing Information Science and Technology University of China, and a visiting Professor of Ningxia Institute of Science and Technology of China. He is a director of Institute of Information and Computing Machinery (IICM), and of Taiwan Association of Cloud Computing (TACC) in Taiwan. He is also a supervisor of Chinese Information Literacy Association, of Association of Algorithms and Computation Theory (AACT), and of Interlibrary Cooperation Association in Taiwan. He has been serving as a secretary general of TACC from 2011 to 2015, of AACT from 2013 to 2016, and of IICM from 2015 to 2018. He was a convener of the East Region of Service Science Society of Taiwan from 2014 to 2016. He was also the regional director of the 2017 ACM-ICPC Contest Council for Taiwan.


Sheng-Lung Peng

Department of Computer Science and Information Engineering,
National Dong Hwa University, Hualien 974, Taiwan


Keynote title: On the Wiener Index Spanning Tree Problem