The 2nd International Conference on Electronic Information Engineering and Computer Technology (EIECT 2022)

Speakers

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Prof. Steven Guan

Professor and the Director for Research Institute of Big Data Analytics

           Xi'an Jiaotong-Liverpool University (XJTLU), China

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Reasearch Area: Machine Learning, Computational Intelligence, Big Data Analytics, Mobile Commerce, Modeling,Networking, Personalization, Security, and Pseudorandom Number Generation.


Steven Guan received his BSc. from Tsinghua University and M.Sc. (1987) & Ph.D. from the University of North Carolina at Chapel Hill. He is currently a Professor and the Director for Research Institute of Big Data Analytics at Xi'an Jiaotong-Liverpool University (XJTLU).He served the head of department position at XJTLU for 4.5 years, creating the department from scratch and now in shape. Before joining XJTLU, he was a tenured professor and chair in intelligent systems at Brunel University, UK. Prof. Guan has worked in a prestigious R&D organization for several years, serving as a design engineer, project leader, and departmentmanager. After leaving the industry, he joined the academia for three and half years. He served as deputy director for the ComputingCenter and the chairman for the Department of Information & Communication Technology. Later he joined the Electrical & ComputerEngineering Department at National University of Singapore as an associate professor for 8 years.

Prof. Guan has worked in a prestigious R&D organization for several years, serving as a design engineer, project leader, and department manager. After leaving the industry, he joined the academia for three and half years. He served as deputy director for the Computing Center and the chairman for the Department of Information & Communication Technology. Later he joined the Electrical & Computer Engineering Department at National University of Singapore as an associate professor for 8 years. Prof. Guan’s research interests include: machine learning, computational intelligence, big data analytics, mobile commerce, modeling, networking, personalization, security, and pseudorandom number generation. He has published extensively in these areas, with 130+ journal papers and 180+ book chapters or conference papers. He has chaired, delivered keynote speech for 80+ international conferences and served in 180+ international conference committees and 20+ editorial boards. There are quite a few inventions from Prof. Guan including Generalized Minimum Distance Decoding for Majority Logic Decodable Codes, Prioritized Petri Nets, SelfModifiable Color Petri Nets, Dynamic Petri Net Model for Iterative and Interactive Distributed Multimedia Presentation, Incremental Feature Learning, Ordered Incremental Input/Output Feature Learning, Input/Output Space Partitioning for Machine Learning, Recursive Supervised Learning, Reduced Pattern Training using Pattern Distributor, Contribution Based Feature Selection, Incremental Genetic Algorithms, Incremental Multi-Objective Genetic Algorithms, Decremental Multi-objective Optimization, Multi-objective Optimization with Objective Replacement, Incremental Hyperplane Partitioning for Classification, Incremental Hyper-sphere Partitioning for Classification, Controllable Cellular Automata for Pseudorandom Number Generation, Self Programmable Cellular Automata, Configurable Cellular Automata, Layered Cellular Automata, Transformation Sequencing of Cellular Automata for Pseudorandom Number Generation, Open Communication with Self-Modifying Protocols, etc.

Keynote Speech Topic

Input Space Partitioning for Machine Learning

Abstract 

This talk introduces an input attribute grouping method to improve the performance of learning. During training for a specific problem, the input attributes are partitioned into groups according to the degree of inter‐attribute promotion or correlation that quantifies the supportive or negative interactions between attributes. After partitioning, multiple sub‐networks are trained by taking each group of attributes as their respective inputs. The final classification result is obtained by integrating the results from each sub‐network. Experimental results on several UCI datasets demonstrate the effectiveness of the proposed method.




人员2.pngProf. Yulin Wang

Wuhan University, China未标题-3.png


Reasearch AreaImage and Video Processing, Digital Rights Management, Information Security, Intelligent System, E-Commerce, IoT, Code Clone

Yulin Wang is a full professor in the School of Computer Science, Wuhan University, China. His research interests include image and video processing, digital rights management, information security, intelligent system, e-commerce, IoT, code clone and so on.

He got his PhD degree from University of London, UK. He got his master and bachelor degree from Huazhong University of Science and Technology(HUST)and Xi-Dian University respectively, both in China.

Prof. Wang served as EiC of 2 international journals and reviewer of top IEEE and ACM journals. He also served as reviewer of Innovative talents projects and national  research funds, including National High Technology Research and Development Program of China. Prof. Wang was the external PhD advisor of Dublin City University, Ireland during 2008-2010.

In recently 10 years, Prof. Wang served as chairman of more than 10 international conferences, and keynote speakers in more than 20 international conferences. Besides UK, he visited US, France,Italy, Portugal,Croatia, Australia, Germany, korea, Ireland,Singapore, Malaysia, Japan, and Hong Kong. In addition, Prof. Wang has been appointed as the deputy director of Hubei provincial science and technology commission (CAPD) since 2014.

Keynote Speech Topic: 

Drone(UAV): from bionic flight to brain like autonomous navigation

Abstract:

Animals have strong individual and group navigation ability, which can realize the direct output from the original perceptual information input to the accurate, reliable and flexible navigation action. This end-to-end intelligent behavior has always been one of the focuses in the field of artificial intelligence (AI). In recent years, with the development of brain and neuroscience, researchers have gradually revealed the brain navigation mechanism of insects, mammals and their groups. Inspired by their navigation mechanisms, a new bionic navigation technology "brain like navigation" has been greatly developed with intelligent algorithms and computing power, showing the characteristics of autonomous environment perception, spatial cognition, intelligent navigation.




人员2.pngProf. Dr. Fuyi Li

College of Information Engineering, Northwest A&F University, China


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Reasearch AreaMachine learning, Data Mining, Bioinformatics


Fuyi Li was initially trained in software engineering during bachelor's and master's studies. His previous research mainly focused on the development of data mining algorithms. Since he commenced his PhD research at Monash University in 2017, he have experienced a dramatic transition from a computer scientist to a computational biologist in terms of his knowledge structure and way of thinking. Prof. Li used every source he could to build his understanding of the complex biological problems and proposed data-driven machine learning-based approaches to address these problems and provide solutions. Since his PhD conferral in 2020/05, he joined the Peter Doherty Institute for Infection and Immunity and worked as a bioinformatics research officer (Level B). After that, Prof. Li  was promoted to a full professor position on 2022/06 at the College of Information Engineering, Northwest A&F University. He can seamlessly communicate with both biologists and computer scientists and bridge the gap between them, to accurately describe the biological problem and propose appropriate ways to address it. 

Prof. Li's current research interests are large-scale data mining, machine learning, bioinformatics, and computational biomedicine. More specifically, his research focuses on machine learning, sequence analysis, structural analysis, DNA/RNA modifications and protein post-translational modification prediction, and antimicrobial resistance phenotype prediction. He have extensive expertise, skill sets, and experiences in sequence analysis, structural bioinformatics, machine learning-based modelling, and biomedical data analytics. He have published 54 research papers (46 are JCR Q1 journal papers), including 13 first-author papers, 9 corresponding author papers, and 7 co-first author papers in top-tier bioinformatics peer-reviewed journals, such as Briefings in Bioinformatics (23 papers), Bioinformatics (8 papers), BMC Bioinformatics (2 papers), and Genomics Proteomics & Bioinformatics (1 paper). Prof. Li's Google Scholar citation is 2437, h-index 24 and i10-index 36 (Aug 2022). Among his publications, 11 papers were selected as Clarivate Highly Cited Paper and his publications have been cited in prestigious peer-reviewed journals such as Cell, Nature Chemical Biology, PNAS, Nucleic Acid Research, Bioinformatics, and Briefings in Bioinformatics.


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人员2.pngProf. Xincheng Ren

Yanan University / School of Physics and Electronic Information


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Reasearch AreaThe characteristics of propagation and scattering of electromagnetic (optical) wave in complex systems and random medium, Computational electromagnetics, Theory and technology of wireless communication


Xincheng Ren is  a member of IEEE, a senior member of the chinese institute of electronics, a senior member of the chinese institute of communications, a member of the physics teaching research association of the chinese education society, a member of the northwest subcommittee of the physics teaching steering committee of the education ministry, a member of the electromagnetic scattering and inverse scattering professional committee of the antenna branch of the chinese institute of electronics, a member of the "Smart Ecology" professional technology group of the internet of things committee of the china institute of communications, executive director of the Shaanxi provincial physics society, executive director of the Shaanxi provincial signal processing society, director of the Shaanxi provincial institute of communications, a member of the high performance computing professional committee of Shaanxi computer society, chairman of Yan'an physics society, executive vice chairman of Yan'an information network security association. He was selected into the science and technology expert database of the China institute of communications. He is an evaluation expert of the National Natural Science Foundation of China, an evaluation expert of the State Council's degree and postgraduate education dissertation, and an evaluation expert of scientific research projects of the Science and Technology Department of Chongqing City, Jiangxi Province, and Anhui Province.

He is currently a Professor with the school of physics and electronic information, Yanan University. He has authored over 200 papers. His research interests include propagation and scattering of electromagnetic (optical) waves in complex systems and random medium, computational electromagnetics, theory and technology of wireless communication.

He is currently the director of the Shaanxi Key laboratory of intelligent processing for energy big data, the director of the Shaanxi electronic information experimental teaching demonstration center, the deputy director of the Shaanxi physics experimental teaching demonstration center, and the director of the Yanan Key laboratory of information processing and measurement and control technology. He used to serve as the secretary of teaching and research, associate dean, and dean of the school of physics and electronic information, the director of the institute of radio waves and the director of the institute of information and communication engineering of Yanan University.


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