Speaker

Professor Lakhmi C.Jain

PhD | ME | BE(Hons)Fellow(Engineers Aust)

Founder KES International                                                                          

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Abstract

Biography

Lakhmi C. Jain,BE(Hons),ME, PhD, Fellow (Engineers Australia), serves as a Visiting Professor in Bournemouth University, United Kingdom and Adjunct Professor in the Faculty of Education, Science, Technology & Mathematics In the University of Canberra, Australia.

DrJain founded the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation and teaming. Involving around 5,000 researchers drawn from universities and companies world-wide, KES facilitates international cooperation and generate synergy in teaching and research. KES regularly provides networking opportunities for professional community through one of the largest conferences of its kind in the area of KES.

His interests focus on the artificial intelligence paradigms and their applications in complex systems, security, e-education, e-healthcare, unmanned air vehicles and intelligent systems.

 

 

 

 

 

 

Speaker

Dr.Abolfazl Razi

Northern Arizona University,USA

Topic

Predictive communications for UAV networks: the intersection of machine learning and wireless communications

Abstract

Unmanned Arial Vehicle (UAV) networking is an emerging technology that has already enabled a wide range of civilian and military applications including transportation, navigation and traffic control, border patrolling and surveillance, fire control, precision agriculture, with many more yet to come. It is expected that the commercial UAV market value hits a record of $2 billion by 2022.The future trend of UAV technology is known to be utilizing swarms of small-scale cooperative UAVs to accomplish complicated tasks, simply because a single UAV with a relatively short communication range and limited sensing, computation and operation equipment is not capable of completing intricate tasks in a limited time. Developing UAV swarms requires a distributed version of control and communication algorithms that accommodate extremely dynamic topologies. This talk explores recent developments in communication protocols designed for UAV networks. This includes two parts. In the first part, we review mobility models used for UAVs in order to predict network topology changes by processing motion trajectories. We will cover model-based methods as well as data driven fuzzy methods. In the second part, we review the impact of mobility and topology change on different key communication performance metrics such as data throughput, delay, and connectivity. In particular, we will review reactive, proactive and predictive routing algorithms in terms of flexibility, performance and optimality. The focus will be on the new generation of predictive protocols designed based on incorporating predicted network topologies into communication protocols.

Biography

Dr. Abolfazl Razi is an Assistant Professor in the School of Informatics, Computing and Cyber Systems at Northern Arizona University (NAU). He received his BSs, MSc, and PhD in Electrical Engineering, respectively from Sharif University of Technology (1998), Tehran Polytechnic (2001), and University of Maine (2013). His PhDresearch focused on developing distributed source and channel coding for hybrid sensor networks under dynamic conditions. In 2013-14, He held a Postdoctoral Associate position at Duke University working on machine learning, Bayesian inference and nonlinear inverse problems. Prior to joining NAU, he was a Postdoctoral fellow at Case Western Reserve University with focus on developing network-based integrative models to analyze cancer genomics. He also served as project manager, and R&D researcher for 8 years in wireless industry (2001-2009), where he obtained several training certificates from leading wireless companies including Ericsson, Nokia, Siemens, ST incard, microelectronic, Gemplus, and Aircom.He also served as organizing committee, TPC member for several IEEE conferences including WiSEE2014-17, CCNC 2019, WiOPT 2016, PiMRC2018, VTC 2018, SECON 2018, and CISS2014.His current research centers on the interplay of wireless networking, machine learning and graph theory. In particular, he is interested in developing predictive communication protocols for UAV networks. His research is published in more than 45 IEEE journal and conference papers.He received the best paper award in IEEE/CaneusWokshop on Fly by Wirelessfor his work on passive sensors. His current research is supported by NSF, NIH, Arizona board of regents, and US Airforce research laboratory.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Speaker

Prof.Zhi-sheng Duan

PhD supervisor

Professorof Department of mechanics and engineering science, school of engineering, Peking University,

National Outstanding Youth Fund winner

Yangtze River Scholar Professor

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Abstract

Biography

In July 2000, he received the Ph.D. degree in general mechanics from Peking University. He stayed in school to teach after his postdoctoral program from2002.He has visited Australia's Monash University many times and conducted collaborative research with University of Hong Kong.He has been engaging in the research of control theory and its application, and published more than 100 papers in SCI retrieval, making contributions specifically in robust control problem of the simultaneous perturbation of the controller and the object, the coordinated control of the associated system, the multi redundant input coordination control and the complex network. His research achievements were widely quoted by colleagues at home and abroad. In 2015, he was awarded as the world's highly cited scientist in Thomson Reuters.He hosted and participated in a number of National Natural Science Foundation projects. He successively servesas an editorial board member of several domestic and foreign journals,  a member of the Control Theory Professional Committee, a member of the Complex Network Professional Committee, and a member of the General Mechanics Professional Committee.His main research interests have been in the areas ofrobust control, large system stability, coordinated control of related systems, redundant input control, complex dynamic network synchronization and the unity of multi intelligence system.

In 2001, he won the 7th Guan Zhizhi Excellent Paper Award. In 2011, he was selected by the Ministry of Education for the New Century Excellent Talent Support Program. In 2011, he was awarded the first prize for science in the Ministry of Education (the first person to finish). In 2012, he was awarded the National Outstanding Youth Fund and the Outstanding Ph.D. Dissertation with Dr. Li Zhongkui, who was jointly trained by Academician Huang Lin. He won the Second Prize of the National Natural Science Award in 2015 (the first finisher). He is currently the distinguished professor of the Yangtze River Award Program of the Ministry of Education.

 

 

 

 

Speaker

Prof.Peng Wang

Peng Wang is a Professor at School of Computer Science, Northwestern Polytechnical University, China.

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Biography

He was with the Australian Centre for Visual Technologies (ACVT) of the University of Adelaide for about four years. His research interests are computer vision, machine learning and artificial intelligence. He received a Bachelor in electrical engineering and automation, and a PhD in control science and engineering from Beihang University (China) in 2004 and 2011, respectively.

 

Speaker

Prof.Ting,Kai Ming

Topic

Data Dependent Similarities: Why they are better than Euclidean distance

Abstract

Distance measures are used in many aspects of machine learning tasks, including classification, clustering, anomaly detection and information retrieval.
Euclidean distance and Gaussian kernel are typical data independent metrics traditionally used in machine learning algorithms because they allow for interpretation as a geometric model and mathematical analysis.
This talk presents recent works on data dependent similarities and Isolation Kernel, and the conditions under which they are better than data independent Euclidean distance and Gaussian kernel in classification and clustering tasks.This includes a recent work published in KDD2018:http://www.kdd.org/kdd2018/accepted-papers/view/isolation-kernel-and-its-effect-on-svm

Biography

After receiving his PhD from the University of Sydney, Kai Ming Ting had worked at te University of Waikato, Deakin University and Monash University. He joins Federation University Australia since 2014. He had previously held visiting positions at Osaka University, Nanjing University, and Chinese University of Hong Kong. His current research interests are in the areas of mass estimation, mass-based dissimilarity, anomaly detection, ensemble approaches, data streams, data mining and machine learning in general. He has served as a program committee co-chair for the Twelfth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2008). He was a member of the program committee for a number of international conferences including ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, and International Conference on Machine Learning. He has received research funding from Australian Research Council, US Air Force of Scientific Research (AFOSR/AOARD), Toyota InfoTechnology Center, and Australian Institute of Sports. Awards received include the Runner-up Best Paper Award in 2008 IEEE ICDM (for Isolation Forest), and the Best Paper Award in 2006 PAKDD. He is the creator of isolation techniques, mass-based similarity and isolation kernel.

 

Speaker

M.S.Shu-jie Ma
Shu-jie Ma, Master of Business Administration at  Chinese University of Hong Kong and Tsinghua University, Researcher in Engineering Technology. He is currently the party secretary, chairman and president of Taihua Wisdom Industry Group Co., Ltd.

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Biography

Shandong Taishan Industry Leaders.
Top ten leading figures in Shandong software industry.
One hundred outstanding builders of socialism with Chinese characteristics in Shandong Province.
The most influential person in the field of smart cities in China.
Excellent Communist Party member of non-industrial enterprises in Shandong Province.
The top ten meritorious private entrepreneurs in Jinan City.
Jinan May 1st Labor Medal. Excellent grassroots party committee secretary of Jinan High-tech Zone.
Secretary-General of China Smart City Industry Alliance;
Member of the Enterprise Joint Group and member of the expert group of the China National Center for Smart City Development Research Center;
Executive director of China Electronics Chamber of Commerce;
Chairman of the Smart City Industrial Technology Innovation Strategic Alliance of Shandong Province;
Vice President of Shandong Electronic Chamber of Commerce;
Standing Committee Member of Shandong Federation of Industry and Commerce;
Vice President of the Overseas Chinese Chamber of Commerce in Shandong Province;
Vice President of Jinan Overseas Chinese Chamber of Commerce;
President of Jinan High-tech Zone Capital Market Association;
Chairman of the Overseas Chinese Federation of Jinan High-tech Zone;
Adjunct professor at Shandong Normal University;
Adjunct professor of Shandong University of Science and Technology;
Adjunct professor of Shandong Administration College;
Adjunct professor at Shandong Jianzhu University.